-
-
Save johndpope/7be8b9b365050ad9615938ae15c36ac4 to your computer and use it in GitHub Desktop.
metagraph file with cyclic errors.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
(lldb) po metagraphFile.graphDef | |
▿ Bender.Tensorflow_GraphDef: | |
node { | |
name: "Placeholder" | |
op: "Placeholder" | |
attr { | |
key: "shape" | |
value { | |
shape { | |
} | |
} | |
} | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "pack" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\001\000\000\000\000Z\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "zeros/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "zeros" | |
op: "Fill" | |
input: "pack" | |
input: "zeros/Const" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "transpose/perm" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 3 | |
} | |
} | |
tensor_content: "\001\000\000\000\000\000\000\000\002\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "transpose" | |
op: "Transpose" | |
input: "Placeholder" | |
input: "transpose/perm" | |
attr { | |
key: "Tperm" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/Shape" | |
op: "Shape" | |
input: "transpose" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "out_type" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice/pack" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice/pack_1" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [2] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice/pack_2" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice" | |
op: "StridedSlice" | |
input: "RNN/Shape" | |
input: "RNN/strided_slice/pack" | |
input: "RNN/strided_slice/pack_1" | |
input: "RNN/strided_slice/pack_2" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "begin_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "ellipsis_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "shrink_axis_mask" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "end_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "new_axis_mask" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_1/pack" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_1/pack_1" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [2] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_1/pack_2" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_1" | |
op: "StridedSlice" | |
input: "RNN/Shape" | |
input: "RNN/strided_slice_1/pack" | |
input: "RNN/strided_slice_1/pack_1" | |
input: "RNN/strided_slice_1/pack_2" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "begin_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "ellipsis_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "shrink_axis_mask" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "end_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "new_axis_mask" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "RNN/Shape_1" | |
op: "Shape" | |
input: "transpose" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "out_type" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_2/pack" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_2/pack_1" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_2/pack_2" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_2" | |
op: "StridedSlice" | |
input: "RNN/Shape_1" | |
input: "RNN/strided_slice_2/pack" | |
input: "RNN/strided_slice_2/pack_1" | |
input: "RNN/strided_slice_2/pack_2" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "begin_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "ellipsis_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "shrink_axis_mask" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "end_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "new_axis_mask" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_3/pack" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_3/pack_1" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [2] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_3/pack_2" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_3" | |
op: "StridedSlice" | |
input: "RNN/Shape_1" | |
input: "RNN/strided_slice_3/pack" | |
input: "RNN/strided_slice_3/pack_1" | |
input: "RNN/strided_slice_3/pack_2" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "begin_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "ellipsis_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "shrink_axis_mask" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "end_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "new_axis_mask" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "RNN/pack/1" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [512] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/pack" | |
op: "Pack" | |
input: "RNN/strided_slice_3" | |
input: "RNN/pack/1" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "axis" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "RNN/zeros/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/zeros" | |
op: "Fill" | |
input: "RNN/pack" | |
input: "RNN/zeros/Const" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/time" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArray" | |
op: "TensorArray" | |
input: "RNN/strided_slice_2" | |
attr { | |
key: "dynamic_size" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "clear_after_read" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "tensor_array_name" | |
value { | |
s: "RNN/dynamic_rnn/output_0" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArray/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArray_1" | |
op: "TensorArray" | |
input: "RNN/strided_slice_2" | |
attr { | |
key: "dynamic_size" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "clear_after_read" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "tensor_array_name" | |
value { | |
s: "RNN/dynamic_rnn/input_0" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArray_1/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/Shape" | |
op: "Shape" | |
input: "transpose" | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "out_type" | |
value { | |
type: DT_INT32 | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/strided_slice/pack" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/strided_slice/pack_1" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/strided_slice/pack_2" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/strided_slice" | |
op: "StridedSlice" | |
input: "RNN/TensorArrayPack/Shape" | |
input: "RNN/TensorArrayPack/strided_slice/pack" | |
input: "RNN/TensorArrayPack/strided_slice/pack_1" | |
input: "RNN/TensorArrayPack/strided_slice/pack_2" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "begin_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "ellipsis_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "shrink_axis_mask" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "end_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "new_axis_mask" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/range/start" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/range/delta" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/range" | |
op: "Range" | |
input: "RNN/TensorArrayPack/range/start" | |
input: "RNN/TensorArrayPack/strided_slice" | |
input: "RNN/TensorArrayPack/range/delta" | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "Tidx" | |
value { | |
type: DT_INT32 | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/TensorArrayScatter" | |
op: "TensorArrayScatter" | |
input: "RNN/TensorArray_1" | |
input: "RNN/TensorArrayPack/range" | |
input: "transpose" | |
input: "RNN/TensorArray_1/Const" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/TensorArray/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Enter" | |
op: "Enter" | |
input: "RNN/time" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Enter_1" | |
op: "Enter" | |
input: "RNN/TensorArray/Const" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Enter_2" | |
op: "Enter" | |
input: "zeros" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Merge" | |
op: "Merge" | |
input: "RNN/while/Enter" | |
input: "RNN/while/NextIteration" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Merge_1" | |
op: "Merge" | |
input: "RNN/while/Enter_1" | |
input: "RNN/while/NextIteration_1" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Merge_2" | |
op: "Merge" | |
input: "RNN/while/Enter_2" | |
input: "RNN/while/NextIteration_2" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Less/Enter" | |
op: "Enter" | |
input: "RNN/strided_slice_2" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Less" | |
op: "Less" | |
input: "RNN/while/Merge" | |
input: "RNN/while/Less/Enter" | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/LoopCond" | |
op: "LoopCond" | |
input: "RNN/while/Less" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Switch" | |
op: "Switch" | |
input: "RNN/while/Merge" | |
input: "RNN/while/LoopCond" | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/while/Merge" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Switch_1" | |
op: "Switch" | |
input: "RNN/while/Merge_1" | |
input: "RNN/while/LoopCond" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/while/Merge_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Switch_2" | |
op: "Switch" | |
input: "RNN/while/Merge_2" | |
input: "RNN/while/LoopCond" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/while/Merge_2" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Identity" | |
op: "Identity" | |
input: "RNN/while/Switch:1" | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Identity_1" | |
op: "Identity" | |
input: "RNN/while/Switch_1:1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Identity_2" | |
op: "Identity" | |
input: "RNN/while/Switch_2:1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/TensorArrayRead/RefEnter" | |
op: "RefEnter" | |
input: "RNN/TensorArray_1" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/TensorArrayRead/Enter" | |
op: "Enter" | |
input: "RNN/TensorArrayPack/TensorArrayScatter" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/TensorArrayRead" | |
op: "TensorArrayRead" | |
input: "RNN/while/TensorArrayRead/RefEnter" | |
input: "RNN/while/Identity" | |
input: "RNN/while/TensorArrayRead/Enter" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice/begin" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\000\000\000\000\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice/size" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000\b\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice" | |
op: "Slice" | |
input: "RNN/while/Identity_2" | |
input: "RNN/while/AttentionCellWrapper/Slice/begin" | |
input: "RNN/while/AttentionCellWrapper/Slice/size" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice_1/begin" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\000\000\000\000\b\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice_1/size" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice_1" | |
op: "Slice" | |
input: "RNN/while/Identity_2" | |
input: "RNN/while/AttentionCellWrapper/Slice_1/begin" | |
input: "RNN/while/AttentionCellWrapper/Slice_1/size" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice_2/begin" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\000\000\000\000\n\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice_2/size" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000P\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice_2" | |
op: "Slice" | |
input: "RNN/while/Identity_2" | |
input: "RNN/while/AttentionCellWrapper/Slice_2/begin" | |
input: "RNN/while/AttentionCellWrapper/Slice_2/size" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 20480 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Reshape/shape" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 3 | |
} | |
} | |
tensor_content: "\377\377\377\377(\000\000\000\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Reshape" | |
op: "Reshape" | |
input: "RNN/while/AttentionCellWrapper/Slice_2" | |
input: "RNN/while/AttentionCellWrapper/Reshape/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "J\002\000\000J\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.071550362] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.071550362] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Linear/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Linear/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/Linear/concat/concat_dim" | |
input: "RNN/while/TensorArrayRead" | |
input: "RNN/while/AttentionCellWrapper/Slice_1" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 586 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Linear/MatMul/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Linear/MatMul" | |
op: "MatMul" | |
input: "RNN/while/AttentionCellWrapper/Linear/concat" | |
input: "RNN/while/AttentionCellWrapper/Linear/MatMul/Enter" | |
attr { | |
key: "transpose_b" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "transpose_a" | |
value { | |
b: false | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Bias" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Bias/Initializer/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
dim { | |
size: 74 | |
} | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Bias/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/Linear/Bias/Initializer/Const" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Bias/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/Linear/Bias" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/add/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/Linear/Bias/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/add" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/Linear/MatMul" | |
input: "RNN/while/AttentionCellWrapper/add/Enter" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice/begin" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\000\000\000\000\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice/size" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000\004\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice" | |
op: "Slice" | |
input: "RNN/while/AttentionCellWrapper/Slice" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice/begin" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice/size" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1024 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split/split_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split" | |
op: "Split" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split/split_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "num_split" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "J\002\000\000\000\b\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.071550362] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.071550362] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/concat/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split:1" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 586 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/MatMul/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/MatMul" | |
op: "MatMul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/MatMul/Enter" | |
attr { | |
key: "transpose_b" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "transpose_a" | |
value { | |
b: false | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/Initializer/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
dim { | |
size: 2048 | |
} | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/Initializer/Const" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/MatMul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add/Enter" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1/split_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1" | |
op: "Split" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1/split_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "num_split" | |
value { | |
i: 4 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_1/y" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_1" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1:2" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_1/y" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid" | |
op: "Sigmoid" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid_1" | |
op: "Sigmoid" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Tanh" | |
op: "Tanh" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1:1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul_1" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid_1" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Tanh" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_2" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Tanh_1" | |
op: "Tanh" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_2" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid_2" | |
op: "Sigmoid" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1:3" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul_2" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Tanh_1" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid_2" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/concat/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_2" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul_2" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1024 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice/begin" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\000\000\000\000\004\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice/size" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000\004\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice" | |
op: "Slice" | |
input: "RNN/while/AttentionCellWrapper/Slice" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice/begin" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice/size" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1024 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split/split_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split" | |
op: "Split" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split/split_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "num_split" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\004\000\000\000\b\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.054126587] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.054126587] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/concat/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul_2" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split:1" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1024 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/MatMul/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/MatMul" | |
op: "MatMul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/MatMul/Enter" | |
attr { | |
key: "transpose_b" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "transpose_a" | |
value { | |
b: false | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/Initializer/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
dim { | |
size: 2048 | |
} | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/Initializer/Const" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/MatMul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add/Enter" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1/split_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1" | |
op: "Split" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1/split_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "num_split" | |
value { | |
i: 4 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_1/y" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_1" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1:2" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_1/y" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid" | |
op: "Sigmoid" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid_1" | |
op: "Sigmoid" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Tanh" | |
op: "Tanh" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1:1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul_1" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid_1" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Tanh" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_2" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Tanh_1" | |
op: "Tanh" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_2" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid_2" | |
op: "Sigmoid" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1:3" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul_2" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Tanh_1" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid_2" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/concat/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_2" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul_2" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1024 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/concat/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/concat" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 4 | |
} | |
} | |
tensor_content: "\001\000\000\000\001\000\000\000\000\002\000\000\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 4 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.076546557] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.076546557] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [512] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-1.7320508] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [1.7320508] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape/shape" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 4 | |
} | |
} | |
tensor_content: "\377\377\377\377(\000\000\000\001\000\000\000\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 4 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape" | |
op: "Reshape" | |
input: "RNN/while/AttentionCellWrapper/Reshape" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Conv2D/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Conv2D" | |
op: "Conv2D" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape" | |
input: "RNN/while/AttentionCellWrapper/Attention/Conv2D/Enter" | |
attr { | |
key: "data_format" | |
value { | |
s: "NHWC" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "use_cudnn_on_gpu" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "padding" | |
value { | |
s: "SAME" | |
} | |
} | |
attr { | |
key: "strides" | |
value { | |
list { | |
i: [1, 1, 1, 1] | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\b\000\000\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.038273279] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.038273279] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Linear/MatMul/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Linear/MatMul" | |
op: "MatMul" | |
input: "RNN/while/AttentionCellWrapper/concat" | |
input: "RNN/while/AttentionCellWrapper/Attention/Linear/MatMul/Enter" | |
attr { | |
key: "transpose_b" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "transpose_a" | |
value { | |
b: false | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Bias/Initializer/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
dim { | |
size: 512 | |
} | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Bias/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias/Initializer/Const" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Bias/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/add/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/add" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/Attention/Linear/MatMul" | |
input: "RNN/while/AttentionCellWrapper/Attention/add/Enter" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape_1/shape" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 4 | |
} | |
} | |
tensor_content: "\377\377\377\377\001\000\000\000\001\000\000\000\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 4 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape_1" | |
op: "Reshape" | |
input: "RNN/while/AttentionCellWrapper/Attention/add" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_1/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/add_1" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/Attention/Conv2D" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Tanh" | |
op: "Tanh" | |
input: "RNN/while/AttentionCellWrapper/Attention/add_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/mul/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/mul" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/Attention/mul/Enter" | |
input: "RNN/while/AttentionCellWrapper/Attention/Tanh" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Sum/reduction_indices" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\002\000\000\000\003\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Sum" | |
op: "Sum" | |
input: "RNN/while/AttentionCellWrapper/Attention/mul" | |
input: "RNN/while/AttentionCellWrapper/Attention/Sum/reduction_indices" | |
attr { | |
key: "keep_dims" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "Tidx" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Softmax" | |
op: "Softmax" | |
input: "RNN/while/AttentionCellWrapper/Attention/Sum" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape_2/shape" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 4 | |
} | |
} | |
tensor_content: "\377\377\377\377(\000\000\000\001\000\000\000\001\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 4 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape_2" | |
op: "Reshape" | |
input: "RNN/while/AttentionCellWrapper/Attention/Softmax" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_2/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/mul_1" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_2" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Sum_1/reduction_indices" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\001\000\000\000\002\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Sum_1" | |
op: "Sum" | |
input: "RNN/while/AttentionCellWrapper/Attention/mul_1" | |
input: "RNN/while/AttentionCellWrapper/Attention/Sum_1/reduction_indices" | |
attr { | |
key: "keep_dims" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "Tidx" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape_3/shape" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape_3" | |
op: "Reshape" | |
input: "RNN/while/AttentionCellWrapper/Attention/Sum_1" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_3/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Slice/begin" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 3 | |
} | |
} | |
tensor_content: "\000\000\000\000\001\000\000\000\000\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Slice/size" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 3 | |
} | |
} | |
tensor_content: "\377\377\377\377\377\377\377\377\377\377\377\377" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Slice" | |
op: "Slice" | |
input: "RNN/while/AttentionCellWrapper/Reshape" | |
input: "RNN/while/AttentionCellWrapper/Attention/Slice/begin" | |
input: "RNN/while/AttentionCellWrapper/Attention/Slice/size" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 39 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\004\000\000\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.054126587] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.054126587] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/concat/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul_2" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_3" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1024 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/MatMul/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/MatMul" | |
op: "MatMul" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/concat" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/MatMul/Enter" | |
attr { | |
key: "transpose_b" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "transpose_a" | |
value { | |
b: false | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/Initializer/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
dim { | |
size: 512 | |
} | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/Initializer/Const" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/AttnOutputProjection/add/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/AttnOutputProjection/add" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/MatMul" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/add/Enter" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/ExpandDims/dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/ExpandDims" | |
op: "ExpandDims" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/add" | |
input: "RNN/while/AttentionCellWrapper/ExpandDims/dim" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tdim" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/concat_1/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/concat_1" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/concat_1/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/Attention/Slice" | |
input: "RNN/while/AttentionCellWrapper/ExpandDims" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Reshape_1/shape" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000P\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Reshape_1" | |
op: "Reshape" | |
input: "RNN/while/AttentionCellWrapper/concat_1" | |
input: "RNN/while/AttentionCellWrapper/Reshape_1/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 20480 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/concat_2/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/concat_2" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/concat_2/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/concat" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_3" | |
input: "RNN/while/AttentionCellWrapper/Reshape_1" | |
attr { | |
key: "N" | |
value { | |
i: 3 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/TensorArrayWrite/RefEnter" | |
op: "RefEnter" | |
input: "RNN/TensorArray" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/TensorArrayWrite" | |
op: "TensorArrayWrite" | |
input: "RNN/while/TensorArrayWrite/RefEnter" | |
input: "RNN/while/Identity" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/add" | |
input: "RNN/while/Identity_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/TensorArray_2/Const" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/add/y" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/add" | |
op: "Add" | |
input: "RNN/while/Identity" | |
input: "RNN/while/add/y" | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/NextIteration" | |
op: "NextIteration" | |
input: "RNN/while/add" | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/NextIteration_1" | |
op: "NextIteration" | |
input: "RNN/while/TensorArrayWrite" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/NextIteration_2" | |
op: "NextIteration" | |
input: "RNN/while/AttentionCellWrapper/concat_2" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Exit" | |
op: "Exit" | |
input: "RNN/while/Switch" | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Exit_1" | |
op: "Exit" | |
input: "RNN/while/Switch_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Exit_2" | |
op: "Exit" | |
input: "RNN/while/Switch_2" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack_1/TensorArraySize" | |
op: "TensorArraySize" | |
input: "RNN/TensorArray" | |
input: "RNN/while/Exit_1" | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack_1/range/start" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack_1/range/delta" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack_1/range" | |
op: "Range" | |
input: "RNN/TensorArrayPack_1/range/start" | |
input: "RNN/TensorArrayPack_1/TensorArraySize" | |
input: "RNN/TensorArrayPack_1/range/delta" | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "Tidx" | |
value { | |
type: DT_INT32 | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack_1/TensorArrayGather" | |
op: "TensorArrayGather" | |
input: "RNN/TensorArray" | |
input: "RNN/TensorArrayPack_1/range" | |
input: "RNN/while/Exit_1" | |
attr { | |
key: "element_shape" | |
value { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/transpose/perm" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 3 | |
} | |
} | |
tensor_content: "\001\000\000\000\000\000\000\000\002\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/transpose" | |
op: "Transpose" | |
input: "RNN/TensorArrayPack_1/TensorArrayGather" | |
input: "RNN/transpose/perm" | |
attr { | |
key: "Tperm" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Reshape/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Reshape" | |
op: "Reshape" | |
input: "RNN/transpose" | |
input: "Reshape/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/Shape" | |
op: "Shape" | |
input: "Reshape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "out_type" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/unpack" | |
op: "Unpack" | |
input: "fully_connected/Shape" | |
attr { | |
key: "num" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "axis" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\002\000\000(\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.1042572] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.1042572] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "fully_connected/weights/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "fully_connected/weights/Initializer/random_uniform/max" | |
input: "fully_connected/weights/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "fully_connected/weights/Initializer/random_uniform/RandomUniform" | |
input: "fully_connected/weights/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform" | |
op: "Add" | |
input: "fully_connected/weights/Initializer/random_uniform/mul" | |
input: "fully_connected/weights/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Assign" | |
op: "Assign" | |
input: "fully_connected/weights" | |
input: "fully_connected/weights/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/read" | |
op: "Identity" | |
input: "fully_connected/weights" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/MatMul" | |
op: "MatMul" | |
input: "Reshape" | |
input: "fully_connected/weights/read" | |
attr { | |
key: "transpose_b" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "transpose_a" | |
value { | |
b: false | |
} | |
} | |
} | |
node { | |
name: "fully_connected/biases" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "fully_connected/biases/Initializer/zeros" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
dim { | |
size: 40 | |
} | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/biases/Assign" | |
op: "Assign" | |
input: "fully_connected/biases" | |
input: "fully_connected/biases/Initializer/zeros" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "fully_connected/biases/read" | |
op: "Identity" | |
input: "fully_connected/biases" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/BiasAdd" | |
op: "BiasAdd" | |
input: "fully_connected/MatMul" | |
input: "fully_connected/biases/read" | |
attr { | |
key: "data_format" | |
value { | |
s: "NHWC" | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Placeholder_1" | |
op: "Placeholder" | |
attr { | |
key: "shape" | |
value { | |
shape { | |
} | |
} | |
} | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Fill/dims" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [40] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Fill" | |
op: "Fill" | |
input: "Fill/dims" | |
input: "Placeholder_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Div" | |
op: "Div" | |
input: "fully_connected/BiasAdd" | |
input: "Fill" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Softmax" | |
op: "Softmax" | |
input: "Div" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Reshape_1/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 3 | |
} | |
} | |
tensor_content: "\001\000\000\000\377\377\377\377(\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Reshape_1" | |
op: "Reshape" | |
input: "Softmax" | |
input: "Reshape_1/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "model" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/save/tensor_names" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
dim { | |
size: 14 | |
} | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnV" | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnW" | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
string_val: "fully_connected/biases" | |
string_val: "fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 14 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/save/shapes_and_slices" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
dim { | |
size: 14 | |
} | |
} | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 14 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/save" | |
op: "SaveSlices" | |
input: "save/Const" | |
input: "save/save/tensor_names" | |
input: "save/save/shapes_and_slices" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
input: "fully_connected/biases" | |
input: "fully_connected/weights" | |
attr { | |
key: "T" | |
value { | |
list { | |
type: [DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT] | |
} | |
} | |
} | |
} | |
node { | |
name: "save/control_dependency" | |
op: "Identity" | |
input: "save/Const" | |
input: "^save/save" | |
attr { | |
key: "T" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@save/Const" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice/tensor_name" | |
input: "save/restore_slice/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV" | |
input: "save/restore_slice" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_1/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_1/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_1" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_1/tensor_name" | |
input: "save/restore_slice_1/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_1" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW" | |
input: "save/restore_slice_1" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_2/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_2/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_2" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_2/tensor_name" | |
input: "save/restore_slice_2/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_2" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
input: "save/restore_slice_2" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_3/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_3/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_3" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_3/tensor_name" | |
input: "save/restore_slice_3/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_3" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
input: "save/restore_slice_3" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_4/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_4/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_4" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_4/tensor_name" | |
input: "save/restore_slice_4/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_4" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
input: "save/restore_slice_4" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_5/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_5/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_5" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_5/tensor_name" | |
input: "save/restore_slice_5/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_5" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
input: "save/restore_slice_5" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_6/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_6/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_6" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_6/tensor_name" | |
input: "save/restore_slice_6/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_6" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Linear/Bias" | |
input: "save/restore_slice_6" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_7/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_7/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_7" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_7/tensor_name" | |
input: "save/restore_slice_7/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_7" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix" | |
input: "save/restore_slice_7" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_8/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_8/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_8" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_8/tensor_name" | |
input: "save/restore_slice_8/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_8" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
input: "save/restore_slice_8" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_9/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_9/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_9" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_9/tensor_name" | |
input: "save/restore_slice_9/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_9" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
input: "save/restore_slice_9" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_10/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_10/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_10" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_10/tensor_name" | |
input: "save/restore_slice_10/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_10" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
input: "save/restore_slice_10" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_11/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_11/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_11" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_11/tensor_name" | |
input: "save/restore_slice_11/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_11" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
input: "save/restore_slice_11" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_12/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_12/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_12" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_12/tensor_name" | |
input: "save/restore_slice_12/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_12" | |
op: "Assign" | |
input: "fully_connected/biases" | |
input: "save/restore_slice_12" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_13/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_13/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_13" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_13/tensor_name" | |
input: "save/restore_slice_13/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_13" | |
op: "Assign" | |
input: "fully_connected/weights" | |
input: "save/restore_slice_13" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_all" | |
op: "NoOp" | |
input: "^save/Assign" | |
input: "^save/Assign_1" | |
input: "^save/Assign_2" | |
input: "^save/Assign_3" | |
input: "^save/Assign_4" | |
input: "^save/Assign_5" | |
input: "^save/Assign_6" | |
input: "^save/Assign_7" | |
input: "^save/Assign_8" | |
input: "^save/Assign_9" | |
input: "^save/Assign_10" | |
input: "^save/Assign_11" | |
input: "^save/Assign_12" | |
input: "^save/Assign_13" | |
} | |
node { | |
name: "save_1/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "model" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/save/tensor_names" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
dim { | |
size: 14 | |
} | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnV" | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnW" | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
string_val: "fully_connected/biases" | |
string_val: "fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 14 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/save/shapes_and_slices" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
dim { | |
size: 14 | |
} | |
} | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 14 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/save" | |
op: "SaveSlices" | |
input: "save_1/Const" | |
input: "save_1/save/tensor_names" | |
input: "save_1/save/shapes_and_slices" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
input: "fully_connected/biases" | |
input: "fully_connected/weights" | |
attr { | |
key: "T" | |
value { | |
list { | |
type: [DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT] | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/control_dependency" | |
op: "Identity" | |
input: "save_1/Const" | |
input: "^save_1/save" | |
attr { | |
key: "T" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@save_1/Const" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice/tensor_name" | |
input: "save_1/restore_slice/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV" | |
input: "save_1/restore_slice" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_1/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_1/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_1" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_1/tensor_name" | |
input: "save_1/restore_slice_1/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_1" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW" | |
input: "save_1/restore_slice_1" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_2/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_2/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_2" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_2/tensor_name" | |
input: "save_1/restore_slice_2/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_2" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
input: "save_1/restore_slice_2" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_3/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_3/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_3" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_3/tensor_name" | |
input: "save_1/restore_slice_3/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_3" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
input: "save_1/restore_slice_3" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_4/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_4/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_4" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_4/tensor_name" | |
input: "save_1/restore_slice_4/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_4" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
input: "save_1/restore_slice_4" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_5/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_5/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_5" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_5/tensor_name" | |
input: "save_1/restore_slice_5/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_5" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
input: "save_1/restore_slice_5" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_6/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_6/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_6" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_6/tensor_name" | |
input: "save_1/restore_slice_6/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_6" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Linear/Bias" | |
input: "save_1/restore_slice_6" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_7/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_7/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_7" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_7/tensor_name" | |
input: "save_1/restore_slice_7/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_7" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix" | |
input: "save_1/restore_slice_7" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_8/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_8/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_8" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_8/tensor_name" | |
input: "save_1/restore_slice_8/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_8" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
input: "save_1/restore_slice_8" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_9/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_9/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_9" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_9/tensor_name" | |
input: "save_1/restore_slice_9/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_9" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
input: "save_1/restore_slice_9" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_10/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_10/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_10" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_10/tensor_name" | |
input: "save_1/restore_slice_10/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_10" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
input: "save_1/restore_slice_10" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_11/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_11/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_11" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_11/tensor_name" | |
input: "save_1/restore_slice_11/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_11" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
input: "save_1/restore_slice_11" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_12/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_12/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_12" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_12/tensor_name" | |
input: "save_1/restore_slice_12/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_12" | |
op: "Assign" | |
input: "fully_connected/biases" | |
input: "save_1/restore_slice_12" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_13/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_13/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_13" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_13/tensor_name" | |
input: "save_1/restore_slice_13/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_13" | |
op: "Assign" | |
input: "fully_connected/weights" | |
input: "save_1/restore_slice_13" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_all" | |
op: "NoOp" | |
input: "^save_1/Assign" | |
input: "^save_1/Assign_1" | |
input: "^save_1/Assign_2" | |
input: "^save_1/Assign_3" | |
input: "^save_1/Assign_4" | |
input: "^save_1/Assign_5" | |
input: "^save_1/Assign_6" | |
input: "^save_1/Assign_7" | |
input: "^save_1/Assign_8" | |
input: "^save_1/Assign_9" | |
input: "^save_1/Assign_10" | |
input: "^save_1/Assign_11" | |
input: "^save_1/Assign_12" | |
input: "^save_1/Assign_13" | |
} | |
versions { | |
producer: 15 | |
} | |
▿ unknownFields : UnknownStorage | |
▿ data : 0 bytes | |
- count : 0 | |
▿ pointer : 0x0000000170009f00 | |
- pointerValue : 6174056192 | |
- bytes : 0 elements | |
▿ _storage : <(_StorageClass in _C64C6CADE1F94526790CBA989AC0C26A): 0x170288930> | |
(lldb) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
graph1: Optional(Bender.Tensorflow_MetaGraphDef: | |
meta_info_def { | |
stripped_op_list { | |
op { | |
name: "Add" | |
input_arg { | |
name: "x" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "y" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "z" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_HALF, DT_FLOAT, DT_DOUBLE, DT_UINT8, DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_COMPLEX64, DT_COMPLEX128, DT_STRING] | |
} | |
} | |
} | |
} | |
op { | |
name: "Assign" | |
input_arg { | |
name: "ref" | |
type_attr: "T" | |
is_ref: true | |
} | |
input_arg { | |
name: "value" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output_ref" | |
type_attr: "T" | |
is_ref: true | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
attr { | |
name: "validate_shape" | |
type: "bool" | |
default_value { | |
b: true | |
} | |
} | |
attr { | |
name: "use_locking" | |
type: "bool" | |
default_value { | |
b: true | |
} | |
} | |
allows_uninitialized_input: true | |
} | |
op { | |
name: "BiasAdd" | |
input_arg { | |
name: "value" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "bias" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_FLOAT, DT_DOUBLE, DT_INT64, DT_INT32, DT_UINT8, DT_UINT16, DT_INT16, DT_INT8, DT_COMPLEX64, DT_COMPLEX128, DT_QINT8, DT_QUINT8, DT_QINT32, DT_HALF] | |
} | |
} | |
} | |
attr { | |
name: "data_format" | |
type: "string" | |
default_value { | |
s: "NHWC" | |
} | |
allowed_values { | |
list { | |
s: "NHWC" | |
s: "NCHW" | |
} | |
} | |
} | |
} | |
op { | |
name: "Concat" | |
input_arg { | |
name: "concat_dim" | |
type: DT_INT32 | |
} | |
input_arg { | |
name: "values" | |
type_attr: "T" | |
number_attr: "N" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "N" | |
type: "int" | |
has_minimum: true | |
minimum: 2 | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
} | |
op { | |
name: "Const" | |
output_arg { | |
name: "output" | |
type_attr: "dtype" | |
} | |
attr { | |
name: "value" | |
type: "tensor" | |
} | |
attr { | |
name: "dtype" | |
type: "type" | |
} | |
} | |
op { | |
name: "Conv2D" | |
input_arg { | |
name: "input" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "filter" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_HALF, DT_FLOAT, DT_DOUBLE] | |
} | |
} | |
} | |
attr { | |
name: "strides" | |
type: "list(int)" | |
} | |
attr { | |
name: "use_cudnn_on_gpu" | |
type: "bool" | |
default_value { | |
b: true | |
} | |
} | |
attr { | |
name: "padding" | |
type: "string" | |
allowed_values { | |
list { | |
s: "SAME" | |
s: "VALID" | |
} | |
} | |
} | |
attr { | |
name: "data_format" | |
type: "string" | |
default_value { | |
s: "NHWC" | |
} | |
allowed_values { | |
list { | |
s: "NHWC" | |
s: "NCHW" | |
} | |
} | |
} | |
} | |
op { | |
name: "Div" | |
input_arg { | |
name: "x" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "y" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "z" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_HALF, DT_FLOAT, DT_DOUBLE, DT_UINT8, DT_INT8, DT_UINT16, DT_INT16, DT_INT32, DT_INT64, DT_COMPLEX64, DT_COMPLEX128] | |
} | |
} | |
} | |
} | |
op { | |
name: "Enter" | |
input_arg { | |
name: "data" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
attr { | |
name: "frame_name" | |
type: "string" | |
} | |
attr { | |
name: "is_constant" | |
type: "bool" | |
default_value { | |
b: false | |
} | |
} | |
attr { | |
name: "parallel_iterations" | |
type: "int" | |
default_value { | |
i: 10 | |
} | |
} | |
} | |
op { | |
name: "Exit" | |
input_arg { | |
name: "data" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
} | |
op { | |
name: "ExpandDims" | |
input_arg { | |
name: "input" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "dim" | |
type_attr: "Tdim" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
attr { | |
name: "Tdim" | |
type: "type" | |
default_value { | |
type: DT_INT32 | |
} | |
allowed_values { | |
list { | |
type: [DT_INT32, DT_INT64] | |
} | |
} | |
} | |
} | |
op { | |
name: "Fill" | |
input_arg { | |
name: "dims" | |
type: DT_INT32 | |
} | |
input_arg { | |
name: "value" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
} | |
op { | |
name: "Identity" | |
input_arg { | |
name: "input" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
} | |
op { | |
name: "Less" | |
input_arg { | |
name: "x" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "y" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "z" | |
type: DT_BOOL | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64, DT_UINT8, DT_INT16, DT_INT8, DT_UINT16, DT_HALF] | |
} | |
} | |
} | |
} | |
op { | |
name: "LoopCond" | |
input_arg { | |
name: "input" | |
type: DT_BOOL | |
} | |
output_arg { | |
name: "output" | |
type: DT_BOOL | |
} | |
} | |
op { | |
name: "MatMul" | |
input_arg { | |
name: "a" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "b" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "product" | |
type_attr: "T" | |
} | |
attr { | |
name: "transpose_a" | |
type: "bool" | |
default_value { | |
b: false | |
} | |
} | |
attr { | |
name: "transpose_b" | |
type: "bool" | |
default_value { | |
b: false | |
} | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_HALF, DT_FLOAT, DT_DOUBLE, DT_INT32, DT_COMPLEX64, DT_COMPLEX128] | |
} | |
} | |
} | |
} | |
op { | |
name: "Merge" | |
input_arg { | |
name: "inputs" | |
type_attr: "T" | |
number_attr: "N" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "value_index" | |
type: DT_INT32 | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
attr { | |
name: "N" | |
type: "int" | |
has_minimum: true | |
minimum: 1 | |
} | |
} | |
op { | |
name: "Mul" | |
input_arg { | |
name: "x" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "y" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "z" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_HALF, DT_FLOAT, DT_DOUBLE, DT_UINT8, DT_INT8, DT_UINT16, DT_INT16, DT_INT32, DT_INT64, DT_COMPLEX64, DT_COMPLEX128] | |
} | |
} | |
} | |
is_commutative: true | |
} | |
op { | |
name: "NextIteration" | |
input_arg { | |
name: "data" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
} | |
op { | |
name: "NoOp" | |
} | |
op { | |
name: "Pack" | |
input_arg { | |
name: "values" | |
type_attr: "T" | |
number_attr: "N" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "N" | |
type: "int" | |
has_minimum: true | |
minimum: 1 | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
attr { | |
name: "axis" | |
type: "int" | |
default_value { | |
i: 0 | |
} | |
} | |
} | |
op { | |
name: "Placeholder" | |
output_arg { | |
name: "output" | |
type_attr: "dtype" | |
} | |
attr { | |
name: "dtype" | |
type: "type" | |
} | |
attr { | |
name: "shape" | |
type: "shape" | |
default_value { | |
shape { | |
} | |
} | |
} | |
} | |
op { | |
name: "RandomUniform" | |
input_arg { | |
name: "shape" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "dtype" | |
} | |
attr { | |
name: "seed" | |
type: "int" | |
default_value { | |
i: 0 | |
} | |
} | |
attr { | |
name: "seed2" | |
type: "int" | |
default_value { | |
i: 0 | |
} | |
} | |
attr { | |
name: "dtype" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_HALF, DT_FLOAT, DT_DOUBLE] | |
} | |
} | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_INT32, DT_INT64] | |
} | |
} | |
} | |
is_stateful: true | |
} | |
op { | |
name: "Range" | |
input_arg { | |
name: "start" | |
type_attr: "Tidx" | |
} | |
input_arg { | |
name: "limit" | |
type_attr: "Tidx" | |
} | |
input_arg { | |
name: "delta" | |
type_attr: "Tidx" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "Tidx" | |
} | |
attr { | |
name: "Tidx" | |
type: "type" | |
default_value { | |
type: DT_INT32 | |
} | |
allowed_values { | |
list { | |
type: [DT_INT32, DT_INT64] | |
} | |
} | |
} | |
} | |
op { | |
name: "RefEnter" | |
input_arg { | |
name: "data" | |
type_attr: "T" | |
is_ref: true | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
is_ref: true | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
attr { | |
name: "frame_name" | |
type: "string" | |
} | |
attr { | |
name: "is_constant" | |
type: "bool" | |
default_value { | |
b: false | |
} | |
} | |
attr { | |
name: "parallel_iterations" | |
type: "int" | |
default_value { | |
i: 10 | |
} | |
} | |
} | |
op { | |
name: "Reshape" | |
input_arg { | |
name: "tensor" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "shape" | |
type_attr: "Tshape" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
attr { | |
name: "Tshape" | |
type: "type" | |
default_value { | |
type: DT_INT32 | |
} | |
allowed_values { | |
list { | |
type: [DT_INT32, DT_INT64] | |
} | |
} | |
} | |
} | |
op { | |
name: "RestoreSlice" | |
input_arg { | |
name: "file_pattern" | |
type: DT_STRING | |
} | |
input_arg { | |
name: "tensor_name" | |
type: DT_STRING | |
} | |
input_arg { | |
name: "shape_and_slice" | |
type: DT_STRING | |
} | |
output_arg { | |
name: "tensor" | |
type_attr: "dt" | |
} | |
attr { | |
name: "dt" | |
type: "type" | |
} | |
attr { | |
name: "preferred_shard" | |
type: "int" | |
default_value { | |
i: -1 | |
} | |
} | |
} | |
op { | |
name: "SaveSlices" | |
input_arg { | |
name: "filename" | |
type: DT_STRING | |
} | |
input_arg { | |
name: "tensor_names" | |
type: DT_STRING | |
} | |
input_arg { | |
name: "shapes_and_slices" | |
type: DT_STRING | |
} | |
input_arg { | |
name: "data" | |
type_list_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "list(type)" | |
has_minimum: true | |
minimum: 1 | |
} | |
} | |
op { | |
name: "Shape" | |
input_arg { | |
name: "input" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "out_type" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
attr { | |
name: "out_type" | |
type: "type" | |
default_value { | |
type: DT_INT32 | |
} | |
allowed_values { | |
list { | |
type: [DT_INT32, DT_INT64] | |
} | |
} | |
} | |
} | |
op { | |
name: "Sigmoid" | |
input_arg { | |
name: "x" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "y" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_HALF, DT_FLOAT, DT_DOUBLE, DT_COMPLEX64, DT_COMPLEX128] | |
} | |
} | |
} | |
} | |
op { | |
name: "Slice" | |
input_arg { | |
name: "input" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "begin" | |
type_attr: "Index" | |
} | |
input_arg { | |
name: "size" | |
type_attr: "Index" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
attr { | |
name: "Index" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_INT32, DT_INT64] | |
} | |
} | |
} | |
} | |
op { | |
name: "Softmax" | |
input_arg { | |
name: "logits" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "softmax" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_HALF, DT_FLOAT, DT_DOUBLE] | |
} | |
} | |
} | |
} | |
op { | |
name: "Split" | |
input_arg { | |
name: "split_dim" | |
type: DT_INT32 | |
} | |
input_arg { | |
name: "value" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
number_attr: "num_split" | |
} | |
attr { | |
name: "num_split" | |
type: "int" | |
has_minimum: true | |
minimum: 1 | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
} | |
op { | |
name: "StridedSlice" | |
input_arg { | |
name: "input" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "begin" | |
type_attr: "Index" | |
} | |
input_arg { | |
name: "end" | |
type_attr: "Index" | |
} | |
input_arg { | |
name: "strides" | |
type_attr: "Index" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
attr { | |
name: "Index" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_INT32, DT_INT64] | |
} | |
} | |
} | |
attr { | |
name: "begin_mask" | |
type: "int" | |
default_value { | |
i: 0 | |
} | |
} | |
attr { | |
name: "end_mask" | |
type: "int" | |
default_value { | |
i: 0 | |
} | |
} | |
attr { | |
name: "ellipsis_mask" | |
type: "int" | |
default_value { | |
i: 0 | |
} | |
} | |
attr { | |
name: "new_axis_mask" | |
type: "int" | |
default_value { | |
i: 0 | |
} | |
} | |
attr { | |
name: "shrink_axis_mask" | |
type: "int" | |
default_value { | |
i: 0 | |
} | |
} | |
} | |
op { | |
name: "Sub" | |
input_arg { | |
name: "x" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "y" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "z" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_HALF, DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64, DT_COMPLEX64, DT_COMPLEX128] | |
} | |
} | |
} | |
} | |
op { | |
name: "Sum" | |
input_arg { | |
name: "input" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "reduction_indices" | |
type_attr: "Tidx" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
} | |
attr { | |
name: "keep_dims" | |
type: "bool" | |
default_value { | |
b: false | |
} | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_FLOAT, DT_DOUBLE, DT_INT64, DT_INT32, DT_UINT8, DT_UINT16, DT_INT16, DT_INT8, DT_COMPLEX64, DT_COMPLEX128, DT_QINT8, DT_QUINT8, DT_QINT32, DT_HALF] | |
} | |
} | |
} | |
attr { | |
name: "Tidx" | |
type: "type" | |
default_value { | |
type: DT_INT32 | |
} | |
allowed_values { | |
list { | |
type: [DT_INT32, DT_INT64] | |
} | |
} | |
} | |
} | |
op { | |
name: "Switch" | |
input_arg { | |
name: "data" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "pred" | |
type: DT_BOOL | |
} | |
output_arg { | |
name: "output_false" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output_true" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
} | |
op { | |
name: "Tanh" | |
input_arg { | |
name: "x" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "y" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
allowed_values { | |
list { | |
type: [DT_HALF, DT_FLOAT, DT_DOUBLE, DT_COMPLEX64, DT_COMPLEX128] | |
} | |
} | |
} | |
} | |
op { | |
name: "TensorArray" | |
input_arg { | |
name: "size" | |
type: DT_INT32 | |
} | |
output_arg { | |
name: "handle" | |
type: DT_STRING | |
is_ref: true | |
} | |
attr { | |
name: "dtype" | |
type: "type" | |
} | |
attr { | |
name: "dynamic_size" | |
type: "bool" | |
default_value { | |
b: false | |
} | |
} | |
attr { | |
name: "clear_after_read" | |
type: "bool" | |
default_value { | |
b: true | |
} | |
} | |
attr { | |
name: "tensor_array_name" | |
type: "string" | |
default_value { | |
s: "" | |
} | |
} | |
is_stateful: true | |
} | |
op { | |
name: "TensorArrayGather" | |
input_arg { | |
name: "handle" | |
type: DT_STRING | |
is_ref: true | |
} | |
input_arg { | |
name: "indices" | |
type: DT_INT32 | |
} | |
input_arg { | |
name: "flow_in" | |
type: DT_FLOAT | |
} | |
output_arg { | |
name: "value" | |
type_attr: "dtype" | |
} | |
attr { | |
name: "dtype" | |
type: "type" | |
} | |
attr { | |
name: "element_shape" | |
type: "shape" | |
default_value { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
op { | |
name: "TensorArrayRead" | |
input_arg { | |
name: "handle" | |
type: DT_STRING | |
is_ref: true | |
} | |
input_arg { | |
name: "index" | |
type: DT_INT32 | |
} | |
input_arg { | |
name: "flow_in" | |
type: DT_FLOAT | |
} | |
output_arg { | |
name: "value" | |
type_attr: "dtype" | |
} | |
attr { | |
name: "dtype" | |
type: "type" | |
} | |
} | |
op { | |
name: "TensorArrayScatter" | |
input_arg { | |
name: "handle" | |
type: DT_STRING | |
is_ref: true | |
} | |
input_arg { | |
name: "indices" | |
type: DT_INT32 | |
} | |
input_arg { | |
name: "value" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "flow_in" | |
type: DT_FLOAT | |
} | |
output_arg { | |
name: "flow_out" | |
type: DT_FLOAT | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
} | |
op { | |
name: "TensorArraySize" | |
input_arg { | |
name: "handle" | |
type: DT_STRING | |
is_ref: true | |
} | |
input_arg { | |
name: "flow_in" | |
type: DT_FLOAT | |
} | |
output_arg { | |
name: "size" | |
type: DT_INT32 | |
} | |
} | |
op { | |
name: "TensorArrayWrite" | |
input_arg { | |
name: "handle" | |
type: DT_STRING | |
is_ref: true | |
} | |
input_arg { | |
name: "index" | |
type: DT_INT32 | |
} | |
input_arg { | |
name: "value" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "flow_in" | |
type: DT_FLOAT | |
} | |
output_arg { | |
name: "flow_out" | |
type: DT_FLOAT | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
} | |
op { | |
name: "Transpose" | |
input_arg { | |
name: "x" | |
type_attr: "T" | |
} | |
input_arg { | |
name: "perm" | |
type_attr: "Tperm" | |
} | |
output_arg { | |
name: "y" | |
type_attr: "T" | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
attr { | |
name: "Tperm" | |
type: "type" | |
default_value { | |
type: DT_INT32 | |
} | |
allowed_values { | |
list { | |
type: [DT_INT32, DT_INT64] | |
} | |
} | |
} | |
} | |
op { | |
name: "Unpack" | |
input_arg { | |
name: "value" | |
type_attr: "T" | |
} | |
output_arg { | |
name: "output" | |
type_attr: "T" | |
number_attr: "num" | |
} | |
attr { | |
name: "num" | |
type: "int" | |
has_minimum: true | |
} | |
attr { | |
name: "T" | |
type: "type" | |
} | |
attr { | |
name: "axis" | |
type: "int" | |
default_value { | |
i: 0 | |
} | |
} | |
} | |
op { | |
name: "Variable" | |
output_arg { | |
name: "ref" | |
type_attr: "dtype" | |
is_ref: true | |
} | |
attr { | |
name: "shape" | |
type: "shape" | |
} | |
attr { | |
name: "dtype" | |
type: "type" | |
} | |
attr { | |
name: "container" | |
type: "string" | |
default_value { | |
s: "" | |
} | |
} | |
attr { | |
name: "shared_name" | |
type: "string" | |
default_value { | |
s: "" | |
} | |
} | |
is_stateful: true | |
} | |
} | |
} | |
graph_def { | |
node { | |
name: "Placeholder" | |
op: "Placeholder" | |
attr { | |
key: "shape" | |
value { | |
shape { | |
} | |
} | |
} | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "pack" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\001\000\000\000\000Z\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "zeros/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "zeros" | |
op: "Fill" | |
input: "pack" | |
input: "zeros/Const" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "transpose/perm" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 3 | |
} | |
} | |
tensor_content: "\001\000\000\000\000\000\000\000\002\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "transpose" | |
op: "Transpose" | |
input: "Placeholder" | |
input: "transpose/perm" | |
attr { | |
key: "Tperm" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/Shape" | |
op: "Shape" | |
input: "transpose" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "out_type" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice/pack" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice/pack_1" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [2] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice/pack_2" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice" | |
op: "StridedSlice" | |
input: "RNN/Shape" | |
input: "RNN/strided_slice/pack" | |
input: "RNN/strided_slice/pack_1" | |
input: "RNN/strided_slice/pack_2" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "begin_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "ellipsis_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "shrink_axis_mask" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "end_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "new_axis_mask" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_1/pack" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_1/pack_1" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [2] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_1/pack_2" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_1" | |
op: "StridedSlice" | |
input: "RNN/Shape" | |
input: "RNN/strided_slice_1/pack" | |
input: "RNN/strided_slice_1/pack_1" | |
input: "RNN/strided_slice_1/pack_2" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "begin_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "ellipsis_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "shrink_axis_mask" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "end_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "new_axis_mask" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "RNN/Shape_1" | |
op: "Shape" | |
input: "transpose" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "out_type" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_2/pack" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_2/pack_1" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_2/pack_2" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_2" | |
op: "StridedSlice" | |
input: "RNN/Shape_1" | |
input: "RNN/strided_slice_2/pack" | |
input: "RNN/strided_slice_2/pack_1" | |
input: "RNN/strided_slice_2/pack_2" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "begin_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "ellipsis_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "shrink_axis_mask" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "end_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "new_axis_mask" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_3/pack" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_3/pack_1" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [2] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_3/pack_2" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/strided_slice_3" | |
op: "StridedSlice" | |
input: "RNN/Shape_1" | |
input: "RNN/strided_slice_3/pack" | |
input: "RNN/strided_slice_3/pack_1" | |
input: "RNN/strided_slice_3/pack_2" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "begin_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "ellipsis_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "shrink_axis_mask" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "end_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "new_axis_mask" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "RNN/pack/1" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [512] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/pack" | |
op: "Pack" | |
input: "RNN/strided_slice_3" | |
input: "RNN/pack/1" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "axis" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "RNN/zeros/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/zeros" | |
op: "Fill" | |
input: "RNN/pack" | |
input: "RNN/zeros/Const" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/time" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArray" | |
op: "TensorArray" | |
input: "RNN/strided_slice_2" | |
attr { | |
key: "dynamic_size" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "clear_after_read" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "tensor_array_name" | |
value { | |
s: "RNN/dynamic_rnn/output_0" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArray/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArray_1" | |
op: "TensorArray" | |
input: "RNN/strided_slice_2" | |
attr { | |
key: "dynamic_size" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "clear_after_read" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "tensor_array_name" | |
value { | |
s: "RNN/dynamic_rnn/input_0" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArray_1/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/Shape" | |
op: "Shape" | |
input: "transpose" | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "out_type" | |
value { | |
type: DT_INT32 | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/strided_slice/pack" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/strided_slice/pack_1" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/strided_slice/pack_2" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/strided_slice" | |
op: "StridedSlice" | |
input: "RNN/TensorArrayPack/Shape" | |
input: "RNN/TensorArrayPack/strided_slice/pack" | |
input: "RNN/TensorArrayPack/strided_slice/pack_1" | |
input: "RNN/TensorArrayPack/strided_slice/pack_2" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "begin_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "ellipsis_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "shrink_axis_mask" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "end_mask" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "new_axis_mask" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/range/start" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/range/delta" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/range" | |
op: "Range" | |
input: "RNN/TensorArrayPack/range/start" | |
input: "RNN/TensorArrayPack/strided_slice" | |
input: "RNN/TensorArrayPack/range/delta" | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "Tidx" | |
value { | |
type: DT_INT32 | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/TensorArrayScatter" | |
op: "TensorArrayScatter" | |
input: "RNN/TensorArray_1" | |
input: "RNN/TensorArrayPack/range" | |
input: "transpose" | |
input: "RNN/TensorArray_1/Const" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack/TensorArray/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Enter" | |
op: "Enter" | |
input: "RNN/time" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Enter_1" | |
op: "Enter" | |
input: "RNN/TensorArray/Const" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Enter_2" | |
op: "Enter" | |
input: "zeros" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Merge" | |
op: "Merge" | |
input: "RNN/while/Enter" | |
input: "RNN/while/NextIteration" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Merge_1" | |
op: "Merge" | |
input: "RNN/while/Enter_1" | |
input: "RNN/while/NextIteration_1" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Merge_2" | |
op: "Merge" | |
input: "RNN/while/Enter_2" | |
input: "RNN/while/NextIteration_2" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Less/Enter" | |
op: "Enter" | |
input: "RNN/strided_slice_2" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Less" | |
op: "Less" | |
input: "RNN/while/Merge" | |
input: "RNN/while/Less/Enter" | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/LoopCond" | |
op: "LoopCond" | |
input: "RNN/while/Less" | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Switch" | |
op: "Switch" | |
input: "RNN/while/Merge" | |
input: "RNN/while/LoopCond" | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/while/Merge" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Switch_1" | |
op: "Switch" | |
input: "RNN/while/Merge_1" | |
input: "RNN/while/LoopCond" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/while/Merge_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Switch_2" | |
op: "Switch" | |
input: "RNN/while/Merge_2" | |
input: "RNN/while/LoopCond" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/while/Merge_2" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Identity" | |
op: "Identity" | |
input: "RNN/while/Switch:1" | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Identity_1" | |
op: "Identity" | |
input: "RNN/while/Switch_1:1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Identity_2" | |
op: "Identity" | |
input: "RNN/while/Switch_2:1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/TensorArrayRead/RefEnter" | |
op: "RefEnter" | |
input: "RNN/TensorArray_1" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/TensorArrayRead/Enter" | |
op: "Enter" | |
input: "RNN/TensorArrayPack/TensorArrayScatter" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/TensorArrayRead" | |
op: "TensorArrayRead" | |
input: "RNN/while/TensorArrayRead/RefEnter" | |
input: "RNN/while/Identity" | |
input: "RNN/while/TensorArrayRead/Enter" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray_1" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice/begin" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\000\000\000\000\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice/size" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000\b\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice" | |
op: "Slice" | |
input: "RNN/while/Identity_2" | |
input: "RNN/while/AttentionCellWrapper/Slice/begin" | |
input: "RNN/while/AttentionCellWrapper/Slice/size" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice_1/begin" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\000\000\000\000\b\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice_1/size" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice_1" | |
op: "Slice" | |
input: "RNN/while/Identity_2" | |
input: "RNN/while/AttentionCellWrapper/Slice_1/begin" | |
input: "RNN/while/AttentionCellWrapper/Slice_1/size" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice_2/begin" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\000\000\000\000\n\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice_2/size" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000P\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Slice_2" | |
op: "Slice" | |
input: "RNN/while/Identity_2" | |
input: "RNN/while/AttentionCellWrapper/Slice_2/begin" | |
input: "RNN/while/AttentionCellWrapper/Slice_2/size" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 20480 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Reshape/shape" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 3 | |
} | |
} | |
tensor_content: "\377\377\377\377(\000\000\000\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Reshape" | |
op: "Reshape" | |
input: "RNN/while/AttentionCellWrapper/Slice_2" | |
input: "RNN/while/AttentionCellWrapper/Reshape/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "J\002\000\000J\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.071550362] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.071550362] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Matrix/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Linear/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Linear/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/Linear/concat/concat_dim" | |
input: "RNN/while/TensorArrayRead" | |
input: "RNN/while/AttentionCellWrapper/Slice_1" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 586 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Linear/MatMul/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Linear/MatMul" | |
op: "MatMul" | |
input: "RNN/while/AttentionCellWrapper/Linear/concat" | |
input: "RNN/while/AttentionCellWrapper/Linear/MatMul/Enter" | |
attr { | |
key: "transpose_b" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "transpose_a" | |
value { | |
b: false | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Bias" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Bias/Initializer/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
dim { | |
size: 74 | |
} | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Bias/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/Linear/Bias/Initializer/Const" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Linear/Bias/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/Linear/Bias" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/add/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/Linear/Bias/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/add" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/Linear/MatMul" | |
input: "RNN/while/AttentionCellWrapper/add/Enter" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice/begin" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\000\000\000\000\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice/size" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000\004\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice" | |
op: "Slice" | |
input: "RNN/while/AttentionCellWrapper/Slice" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice/begin" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice/size" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1024 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split/split_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split" | |
op: "Split" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split/split_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "num_split" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "J\002\000\000\000\b\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.071550362] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.071550362] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/concat/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split:1" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 586 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/MatMul/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/MatMul" | |
op: "MatMul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/MatMul/Enter" | |
attr { | |
key: "transpose_b" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "transpose_a" | |
value { | |
b: false | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/Initializer/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
dim { | |
size: 2048 | |
} | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/Initializer/Const" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/MatMul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add/Enter" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1/split_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1" | |
op: "Split" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1/split_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "num_split" | |
value { | |
i: 4 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_1/y" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_1" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1:2" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_1/y" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid" | |
op: "Sigmoid" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid_1" | |
op: "Sigmoid" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Tanh" | |
op: "Tanh" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1:1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul_1" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid_1" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Tanh" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_2" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Tanh_1" | |
op: "Tanh" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_2" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid_2" | |
op: "Sigmoid" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1:3" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul_2" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Tanh_1" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid_2" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/concat/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_2" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul_2" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1024 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice/begin" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\000\000\000\000\004\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice/size" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000\004\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice" | |
op: "Slice" | |
input: "RNN/while/AttentionCellWrapper/Slice" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice/begin" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice/size" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1024 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split/split_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split" | |
op: "Split" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split/split_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "num_split" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\004\000\000\000\b\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.054126587] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.054126587] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/concat/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul_2" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split:1" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1024 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/MatMul/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/MatMul" | |
op: "MatMul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/MatMul/Enter" | |
attr { | |
key: "transpose_b" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "transpose_a" | |
value { | |
b: false | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/Initializer/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
dim { | |
size: 2048 | |
} | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/Initializer/Const" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/MatMul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add/Enter" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1/split_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1" | |
op: "Split" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1/split_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "num_split" | |
value { | |
i: 4 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_1/y" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_1" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1:2" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_1/y" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid" | |
op: "Sigmoid" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid_1" | |
op: "Sigmoid" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Tanh" | |
op: "Tanh" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1:1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul_1" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid_1" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Tanh" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_2" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Tanh_1" | |
op: "Tanh" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_2" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid_2" | |
op: "Sigmoid" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1:3" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul_2" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Tanh_1" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid_2" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/concat/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_2" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul_2" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1024 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/concat/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/concat" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/concat" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 4 | |
} | |
} | |
tensor_content: "\001\000\000\000\001\000\000\000\000\002\000\000\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 4 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.076546557] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.076546557] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnW/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [512] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-1.7320508] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [1.7320508] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/AttnV/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape/shape" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 4 | |
} | |
} | |
tensor_content: "\377\377\377\377(\000\000\000\001\000\000\000\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 4 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape" | |
op: "Reshape" | |
input: "RNN/while/AttentionCellWrapper/Reshape" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Conv2D/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Conv2D" | |
op: "Conv2D" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape" | |
input: "RNN/while/AttentionCellWrapper/Attention/Conv2D/Enter" | |
attr { | |
key: "data_format" | |
value { | |
s: "NHWC" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "use_cudnn_on_gpu" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "padding" | |
value { | |
s: "SAME" | |
} | |
} | |
attr { | |
key: "strides" | |
value { | |
list { | |
i: [1, 1, 1, 1] | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\b\000\000\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.038273279] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.038273279] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Linear/MatMul/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Linear/MatMul" | |
op: "MatMul" | |
input: "RNN/while/AttentionCellWrapper/concat" | |
input: "RNN/while/AttentionCellWrapper/Attention/Linear/MatMul/Enter" | |
attr { | |
key: "transpose_b" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "transpose_a" | |
value { | |
b: false | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Bias/Initializer/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
dim { | |
size: 512 | |
} | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Bias/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias/Initializer/Const" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/Attention/Linear/Bias/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/add/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/add" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/Attention/Linear/MatMul" | |
input: "RNN/while/AttentionCellWrapper/Attention/add/Enter" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape_1/shape" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 4 | |
} | |
} | |
tensor_content: "\377\377\377\377\001\000\000\000\001\000\000\000\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 4 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape_1" | |
op: "Reshape" | |
input: "RNN/while/AttentionCellWrapper/Attention/add" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_1/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/add_1" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/Attention/Conv2D" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Tanh" | |
op: "Tanh" | |
input: "RNN/while/AttentionCellWrapper/Attention/add_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/mul/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/mul" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/Attention/mul/Enter" | |
input: "RNN/while/AttentionCellWrapper/Attention/Tanh" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Sum/reduction_indices" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\002\000\000\000\003\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Sum" | |
op: "Sum" | |
input: "RNN/while/AttentionCellWrapper/Attention/mul" | |
input: "RNN/while/AttentionCellWrapper/Attention/Sum/reduction_indices" | |
attr { | |
key: "keep_dims" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "Tidx" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Softmax" | |
op: "Softmax" | |
input: "RNN/while/AttentionCellWrapper/Attention/Sum" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape_2/shape" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 4 | |
} | |
} | |
tensor_content: "\377\377\377\377(\000\000\000\001\000\000\000\001\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 4 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape_2" | |
op: "Reshape" | |
input: "RNN/while/AttentionCellWrapper/Attention/Softmax" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_2/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/mul_1" | |
op: "Mul" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_2" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Sum_1/reduction_indices" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\001\000\000\000\002\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Sum_1" | |
op: "Sum" | |
input: "RNN/while/AttentionCellWrapper/Attention/mul_1" | |
input: "RNN/while/AttentionCellWrapper/Attention/Sum_1/reduction_indices" | |
attr { | |
key: "keep_dims" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "Tidx" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape_3/shape" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Reshape_3" | |
op: "Reshape" | |
input: "RNN/while/AttentionCellWrapper/Attention/Sum_1" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_3/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Slice/begin" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 3 | |
} | |
} | |
tensor_content: "\000\000\000\000\001\000\000\000\000\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Slice/size" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 3 | |
} | |
} | |
tensor_content: "\377\377\377\377\377\377\377\377\377\377\377\377" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Attention/Slice" | |
op: "Slice" | |
input: "RNN/while/AttentionCellWrapper/Reshape" | |
input: "RNN/while/AttentionCellWrapper/Attention/Slice/begin" | |
input: "RNN/while/AttentionCellWrapper/Attention/Slice/size" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Index" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 39 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\004\000\000\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.054126587] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.054126587] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/max" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/RandomUniform" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform" | |
op: "Add" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/mul" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/concat/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/concat" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/concat/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul_2" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_3" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1024 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/MatMul/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/MatMul" | |
op: "MatMul" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/concat" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/MatMul/Enter" | |
attr { | |
key: "transpose_b" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "transpose_a" | |
value { | |
b: false | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/Initializer/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
dim { | |
size: 512 | |
} | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/Initializer/Const" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/read" | |
op: "Identity" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/AttnOutputProjection/add/Enter" | |
op: "Enter" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/read" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/AttnOutputProjection/add" | |
op: "Add" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/MatMul" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/add/Enter" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/ExpandDims/dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/ExpandDims" | |
op: "ExpandDims" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/add" | |
input: "RNN/while/AttentionCellWrapper/ExpandDims/dim" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tdim" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/concat_1/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/concat_1" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/concat_1/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/Attention/Slice" | |
input: "RNN/while/AttentionCellWrapper/ExpandDims" | |
attr { | |
key: "N" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 40 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Reshape_1/shape" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000P\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/Reshape_1" | |
op: "Reshape" | |
input: "RNN/while/AttentionCellWrapper/concat_1" | |
input: "RNN/while/AttentionCellWrapper/Reshape_1/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 20480 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/concat_2/concat_dim" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/AttentionCellWrapper/concat_2" | |
op: "Concat" | |
input: "RNN/while/AttentionCellWrapper/concat_2/concat_dim" | |
input: "RNN/while/AttentionCellWrapper/concat" | |
input: "RNN/while/AttentionCellWrapper/Attention/Reshape_3" | |
input: "RNN/while/AttentionCellWrapper/Reshape_1" | |
attr { | |
key: "N" | |
value { | |
i: 3 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/TensorArrayWrite/RefEnter" | |
op: "RefEnter" | |
input: "RNN/TensorArray" | |
attr { | |
key: "parallel_iterations" | |
value { | |
i: 1 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "is_constant" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "frame_name" | |
value { | |
s: "RNN/while/RNN/while/" | |
} | |
} | |
} | |
node { | |
name: "RNN/while/TensorArrayWrite" | |
op: "TensorArrayWrite" | |
input: "RNN/while/TensorArrayWrite/RefEnter" | |
input: "RNN/while/Identity" | |
input: "RNN/while/AttentionCellWrapper/AttnOutputProjection/add" | |
input: "RNN/while/Identity_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/TensorArray_2/Const" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/add/y" | |
op: "Const" | |
input: "^RNN/while/Identity" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/add" | |
op: "Add" | |
input: "RNN/while/Identity" | |
input: "RNN/while/add/y" | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/NextIteration" | |
op: "NextIteration" | |
input: "RNN/while/add" | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/NextIteration_1" | |
op: "NextIteration" | |
input: "RNN/while/TensorArrayWrite" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/NextIteration_2" | |
op: "NextIteration" | |
input: "RNN/while/AttentionCellWrapper/concat_2" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Exit" | |
op: "Exit" | |
input: "RNN/while/Switch" | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Exit_1" | |
op: "Exit" | |
input: "RNN/while/Switch_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/while/Exit_2" | |
op: "Exit" | |
input: "RNN/while/Switch_2" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 23040 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack_1/TensorArraySize" | |
op: "TensorArraySize" | |
input: "RNN/TensorArray" | |
input: "RNN/while/Exit_1" | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack_1/range/start" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack_1/range/delta" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
} | |
int_val: [1] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack_1/range" | |
op: "Range" | |
input: "RNN/TensorArrayPack_1/range/start" | |
input: "RNN/TensorArrayPack_1/TensorArraySize" | |
input: "RNN/TensorArrayPack_1/range/delta" | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "Tidx" | |
value { | |
type: DT_INT32 | |
} | |
} | |
} | |
node { | |
name: "RNN/TensorArrayPack_1/TensorArrayGather" | |
op: "TensorArrayGather" | |
input: "RNN/TensorArray" | |
input: "RNN/TensorArrayPack_1/range" | |
input: "RNN/while/Exit_1" | |
attr { | |
key: "element_shape" | |
value { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/TensorArray" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/transpose/perm" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 3 | |
} | |
} | |
tensor_content: "\001\000\000\000\000\000\000\000\002\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "RNN/transpose" | |
op: "Transpose" | |
input: "RNN/TensorArrayPack_1/TensorArrayGather" | |
input: "RNN/transpose/perm" | |
attr { | |
key: "Tperm" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Reshape/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\377\377\377\377\000\002\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Reshape" | |
op: "Reshape" | |
input: "RNN/transpose" | |
input: "Reshape/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/Shape" | |
op: "Shape" | |
input: "Reshape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "out_type" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/unpack" | |
op: "Unpack" | |
input: "fully_connected/Shape" | |
attr { | |
key: "num" | |
value { | |
i: 2 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
shape { | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "axis" | |
value { | |
i: 0 | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 2 | |
} | |
} | |
tensor_content: "\000\002\000\000(\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform/min" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [-0.1042572] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform/max" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
} | |
float_val: [0.1042572] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform/RandomUniform" | |
op: "RandomUniform" | |
input: "fully_connected/weights/Initializer/random_uniform/shape" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "seed2" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "seed" | |
value { | |
i: 0 | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform/sub" | |
op: "Sub" | |
input: "fully_connected/weights/Initializer/random_uniform/max" | |
input: "fully_connected/weights/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform/mul" | |
op: "Mul" | |
input: "fully_connected/weights/Initializer/random_uniform/RandomUniform" | |
input: "fully_connected/weights/Initializer/random_uniform/sub" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Initializer/random_uniform" | |
op: "Add" | |
input: "fully_connected/weights/Initializer/random_uniform/mul" | |
input: "fully_connected/weights/Initializer/random_uniform/min" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/Assign" | |
op: "Assign" | |
input: "fully_connected/weights" | |
input: "fully_connected/weights/Initializer/random_uniform" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "fully_connected/weights/read" | |
op: "Identity" | |
input: "fully_connected/weights" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/MatMul" | |
op: "MatMul" | |
input: "Reshape" | |
input: "fully_connected/weights/read" | |
attr { | |
key: "transpose_b" | |
value { | |
b: false | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "transpose_a" | |
value { | |
b: false | |
} | |
} | |
} | |
node { | |
name: "fully_connected/biases" | |
op: "Variable" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "container" | |
value { | |
s: "" | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "shape" | |
value { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
attr { | |
key: "shared_name" | |
value { | |
s: "" | |
} | |
} | |
} | |
node { | |
name: "fully_connected/biases/Initializer/zeros" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_FLOAT | |
tensor_shape { | |
dim { | |
size: 40 | |
} | |
} | |
float_val: [0] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/biases/Assign" | |
op: "Assign" | |
input: "fully_connected/biases" | |
input: "fully_connected/biases/Initializer/zeros" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "fully_connected/biases/read" | |
op: "Identity" | |
input: "fully_connected/biases" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "fully_connected/BiasAdd" | |
op: "BiasAdd" | |
input: "fully_connected/MatMul" | |
input: "fully_connected/biases/read" | |
attr { | |
key: "data_format" | |
value { | |
s: "NHWC" | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Placeholder_1" | |
op: "Placeholder" | |
attr { | |
key: "shape" | |
value { | |
shape { | |
} | |
} | |
} | |
attr { | |
key: "dtype" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Fill/dims" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 1 | |
} | |
} | |
int_val: [40] | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Fill" | |
op: "Fill" | |
input: "Fill/dims" | |
input: "Placeholder_1" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Div" | |
op: "Div" | |
input: "fully_connected/BiasAdd" | |
input: "Fill" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Softmax" | |
op: "Softmax" | |
input: "Div" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Reshape_1/shape" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_INT32 | |
tensor_shape { | |
dim { | |
size: 3 | |
} | |
} | |
tensor_content: "\001\000\000\000\377\377\377\377(\000\000\000" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 3 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "Reshape_1" | |
op: "Reshape" | |
input: "Softmax" | |
input: "Reshape_1/shape" | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "Tshape" | |
value { | |
type: DT_INT32 | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: -1 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "model" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/save/tensor_names" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
dim { | |
size: 14 | |
} | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnV" | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnW" | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
string_val: "fully_connected/biases" | |
string_val: "fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 14 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/save/shapes_and_slices" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
dim { | |
size: 14 | |
} | |
} | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 14 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/save" | |
op: "SaveSlices" | |
input: "save/Const" | |
input: "save/save/tensor_names" | |
input: "save/save/shapes_and_slices" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
input: "fully_connected/biases" | |
input: "fully_connected/weights" | |
attr { | |
key: "T" | |
value { | |
list { | |
type: [DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT] | |
} | |
} | |
} | |
} | |
node { | |
name: "save/control_dependency" | |
op: "Identity" | |
input: "save/Const" | |
input: "^save/save" | |
attr { | |
key: "T" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@save/Const" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice/tensor_name" | |
input: "save/restore_slice/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV" | |
input: "save/restore_slice" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_1/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_1/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_1" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_1/tensor_name" | |
input: "save/restore_slice_1/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_1" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW" | |
input: "save/restore_slice_1" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_2/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_2/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_2" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_2/tensor_name" | |
input: "save/restore_slice_2/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_2" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
input: "save/restore_slice_2" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_3/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_3/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_3" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_3/tensor_name" | |
input: "save/restore_slice_3/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_3" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
input: "save/restore_slice_3" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_4/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_4/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_4" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_4/tensor_name" | |
input: "save/restore_slice_4/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_4" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
input: "save/restore_slice_4" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_5/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_5/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_5" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_5/tensor_name" | |
input: "save/restore_slice_5/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_5" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
input: "save/restore_slice_5" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_6/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_6/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_6" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_6/tensor_name" | |
input: "save/restore_slice_6/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_6" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Linear/Bias" | |
input: "save/restore_slice_6" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_7/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_7/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_7" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_7/tensor_name" | |
input: "save/restore_slice_7/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_7" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix" | |
input: "save/restore_slice_7" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_8/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_8/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_8" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_8/tensor_name" | |
input: "save/restore_slice_8/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_8" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
input: "save/restore_slice_8" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_9/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_9/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_9" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_9/tensor_name" | |
input: "save/restore_slice_9/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_9" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
input: "save/restore_slice_9" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_10/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_10/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_10" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_10/tensor_name" | |
input: "save/restore_slice_10/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_10" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
input: "save/restore_slice_10" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_11/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_11/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_11" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_11/tensor_name" | |
input: "save/restore_slice_11/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_11" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
input: "save/restore_slice_11" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_12/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_12/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_12" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_12/tensor_name" | |
input: "save/restore_slice_12/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_12" | |
op: "Assign" | |
input: "fully_connected/biases" | |
input: "save/restore_slice_12" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_13/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_13/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/restore_slice_13" | |
op: "RestoreSlice" | |
input: "save/Const" | |
input: "save/restore_slice_13/tensor_name" | |
input: "save/restore_slice_13/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save/Assign_13" | |
op: "Assign" | |
input: "fully_connected/weights" | |
input: "save/restore_slice_13" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save/restore_all" | |
op: "NoOp" | |
input: "^save/Assign" | |
input: "^save/Assign_1" | |
input: "^save/Assign_2" | |
input: "^save/Assign_3" | |
input: "^save/Assign_4" | |
input: "^save/Assign_5" | |
input: "^save/Assign_6" | |
input: "^save/Assign_7" | |
input: "^save/Assign_8" | |
input: "^save/Assign_9" | |
input: "^save/Assign_10" | |
input: "^save/Assign_11" | |
input: "^save/Assign_12" | |
input: "^save/Assign_13" | |
} | |
node { | |
name: "save_1/Const" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "model" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/save/tensor_names" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
dim { | |
size: 14 | |
} | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnV" | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnW" | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
string_val: "fully_connected/biases" | |
string_val: "fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 14 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/save/shapes_and_slices" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
dim { | |
size: 14 | |
} | |
} | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 14 | |
} | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/save" | |
op: "SaveSlices" | |
input: "save_1/Const" | |
input: "save_1/save/tensor_names" | |
input: "save_1/save/shapes_and_slices" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
input: "fully_connected/biases" | |
input: "fully_connected/weights" | |
attr { | |
key: "T" | |
value { | |
list { | |
type: [DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT] | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/control_dependency" | |
op: "Identity" | |
input: "save_1/Const" | |
input: "^save_1/save" | |
attr { | |
key: "T" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@save_1/Const" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice/tensor_name" | |
input: "save_1/restore_slice/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/AttnV" | |
input: "save_1/restore_slice" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnV" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_1/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_1/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_1" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_1/tensor_name" | |
input: "save_1/restore_slice_1/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_1" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/AttnW" | |
input: "save_1/restore_slice_1" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/AttnW" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 1 | |
} | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_2/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_2/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_2" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_2/tensor_name" | |
input: "save_1/restore_slice_2/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_2" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
input: "save_1/restore_slice_2" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_3/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_3/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_3" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_3/tensor_name" | |
input: "save_1/restore_slice_3/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_3" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
input: "save_1/restore_slice_3" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Attention/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_4/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_4/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_4" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_4/tensor_name" | |
input: "save_1/restore_slice_4/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_4" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
input: "save_1/restore_slice_4" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_5/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_5/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_5" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_5/tensor_name" | |
input: "save_1/restore_slice_5/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_5" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
input: "save_1/restore_slice_5" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 512 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_6/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_6/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_6" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_6/tensor_name" | |
input: "save_1/restore_slice_6/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_6" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Linear/Bias" | |
input: "save_1/restore_slice_6" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_7/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_7/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_7" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_7/tensor_name" | |
input: "save_1/restore_slice_7/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_7" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/Linear/Matrix" | |
input: "save_1/restore_slice_7" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 74 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_8/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_8/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_8" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_8/tensor_name" | |
input: "save_1/restore_slice_8/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_8" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
input: "save_1/restore_slice_8" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_9/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_9/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_9" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_9/tensor_name" | |
input: "save_1/restore_slice_9/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_9" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
input: "save_1/restore_slice_9" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 586 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_10/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_10/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_10" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_10/tensor_name" | |
input: "save_1/restore_slice_10/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_10" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
input: "save_1/restore_slice_10" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_11/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_11/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_11" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_11/tensor_name" | |
input: "save_1/restore_slice_11/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_11" | |
op: "Assign" | |
input: "RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
input: "save_1/restore_slice_11" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@RNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 1024 | |
} | |
dim { | |
size: 2048 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_12/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_12/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_12" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_12/tensor_name" | |
input: "save_1/restore_slice_12/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_12" | |
op: "Assign" | |
input: "fully_connected/biases" | |
input: "save_1/restore_slice_12" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/biases" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_13/tensor_name" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_13/shape_and_slice" | |
op: "Const" | |
attr { | |
key: "dtype" | |
value { | |
type: DT_STRING | |
} | |
} | |
attr { | |
key: "value" | |
value { | |
tensor { | |
dtype: DT_STRING | |
tensor_shape { | |
} | |
string_val: "" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_slice_13" | |
op: "RestoreSlice" | |
input: "save_1/Const" | |
input: "save_1/restore_slice_13/tensor_name" | |
input: "save_1/restore_slice_13/shape_and_slice" | |
attr { | |
key: "preferred_shard" | |
value { | |
i: -1 | |
} | |
} | |
attr { | |
key: "dt" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
unknown_rank: true | |
} | |
} | |
} | |
} | |
} | |
node { | |
name: "save_1/Assign_13" | |
op: "Assign" | |
input: "fully_connected/weights" | |
input: "save_1/restore_slice_13" | |
attr { | |
key: "validate_shape" | |
value { | |
b: true | |
} | |
} | |
attr { | |
key: "_class" | |
value { | |
list { | |
s: "loc:@fully_connected/weights" | |
} | |
} | |
} | |
attr { | |
key: "_output_shapes" | |
value { | |
list { | |
shape { | |
dim { | |
size: 512 | |
} | |
dim { | |
size: 40 | |
} | |
} | |
} | |
} | |
} | |
attr { | |
key: "T" | |
value { | |
type: DT_FLOAT | |
} | |
} | |
attr { | |
key: "use_locking" | |
value { | |
b: true | |
} | |
} | |
} | |
node { | |
name: "save_1/restore_all" | |
op: "NoOp" | |
input: "^save_1/Assign" | |
input: "^save_1/Assign_1" | |
input: "^save_1/Assign_2" | |
input: "^save_1/Assign_3" | |
input: "^save_1/Assign_4" | |
input: "^save_1/Assign_5" | |
input: "^save_1/Assign_6" | |
input: "^save_1/Assign_7" | |
input: "^save_1/Assign_8" | |
input: "^save_1/Assign_9" | |
input: "^save_1/Assign_10" | |
input: "^save_1/Assign_11" | |
input: "^save_1/Assign_12" | |
input: "^save_1/Assign_13" | |
} | |
versions { | |
producer: 15 | |
} | |
} | |
saver_def { | |
filename_tensor_name: "save_1/Const:0" | |
save_tensor_name: "save_1/control_dependency:0" | |
restore_op_name: "save_1/restore_all" | |
max_to_keep: 5 | |
keep_checkpoint_every_n_hours: 10000 | |
version: V1 | |
} | |
collection_def { | |
key: "while_context" | |
value { | |
bytes_list { | |
value: "\n\024RNN/while/RNN/while/\020\001\030\001 \001*\024RNN/while/LoopCond:02\021RNN/while/Merge:0:\024RNN/while/Identity:0B\020RNN/while/Exit:0B\022RNN/while/Exit_1:0B\022RNN/while/Exit_2:0J\273W\n/RNN/AttentionCellWrapper/Attention/AttnV/read:0\n/RNN/AttentionCellWrapper/Attention/AttnW/read:0\n5RNN/AttentionCellWrapper/Attention/Linear/Bias/read:0\n7RNN/AttentionCellWrapper/Attention/Linear/Matrix/read:0\n@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/read:0\nBRNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/read:0\n+RNN/AttentionCellWrapper/Linear/Bias/read:0\n-RNN/AttentionCellWrapper/Linear/Matrix/read:0\nLRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/read:0\nNRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/read:0\nLRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/read:0\nNRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/read:0\n\021RNN/TensorArray:0\n(RNN/TensorArrayPack/TensorArrayScatter:0\n\023RNN/TensorArray_1:0\n\025RNN/strided_slice_2:0\n7RNN/while/AttentionCellWrapper/Attention/Conv2D/Enter:0\n1RNN/while/AttentionCellWrapper/Attention/Conv2D:0\n>RNN/while/AttentionCellWrapper/Attention/Linear/MatMul/Enter:0\n8RNN/while/AttentionCellWrapper/Attention/Linear/MatMul:0\n8RNN/while/AttentionCellWrapper/Attention/Reshape/shape:0\n2RNN/while/AttentionCellWrapper/Attention/Reshape:0\n:RNN/while/AttentionCellWrapper/Attention/Reshape_1/shape:0\n4RNN/while/AttentionCellWrapper/Attention/Reshape_1:0\n:RNN/while/AttentionCellWrapper/Attention/Reshape_2/shape:0\n4RNN/while/AttentionCellWrapper/Attention/Reshape_2:0\n:RNN/while/AttentionCellWrapper/Attention/Reshape_3/shape:0\n4RNN/while/AttentionCellWrapper/Attention/Reshape_3:0\n6RNN/while/AttentionCellWrapper/Attention/Slice/begin:0\n5RNN/while/AttentionCellWrapper/Attention/Slice/size:0\n0RNN/while/AttentionCellWrapper/Attention/Slice:0\n2RNN/while/AttentionCellWrapper/Attention/Softmax:0\n@RNN/while/AttentionCellWrapper/Attention/Sum/reduction_indices:0\n.RNN/while/AttentionCellWrapper/Attention/Sum:0\nBRNN/while/AttentionCellWrapper/Attention/Sum_1/reduction_indices:0\n0RNN/while/AttentionCellWrapper/Attention/Sum_1:0\n/RNN/while/AttentionCellWrapper/Attention/Tanh:0\n4RNN/while/AttentionCellWrapper/Attention/add/Enter:0\n.RNN/while/AttentionCellWrapper/Attention/add:0\n0RNN/while/AttentionCellWrapper/Attention/add_1:0\n4RNN/while/AttentionCellWrapper/Attention/mul/Enter:0\n.RNN/while/AttentionCellWrapper/Attention/mul:0\n0RNN/while/AttentionCellWrapper/Attention/mul_1:0\nIRNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/MatMul/Enter:0\nCRNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/MatMul:0\nNRNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/concat/concat_dim:0\nCRNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/concat:0\n?RNN/while/AttentionCellWrapper/AttnOutputProjection/add/Enter:0\n9RNN/while/AttentionCellWrapper/AttnOutputProjection/add:0\n/RNN/while/AttentionCellWrapper/ExpandDims/dim:0\n+RNN/while/AttentionCellWrapper/ExpandDims:0\n4RNN/while/AttentionCellWrapper/Linear/MatMul/Enter:0\n.RNN/while/AttentionCellWrapper/Linear/MatMul:0\n9RNN/while/AttentionCellWrapper/Linear/concat/concat_dim:0\n.RNN/while/AttentionCellWrapper/Linear/concat:0\nURNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/MatMul/Enter:0\nORNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/MatMul:0\nZRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/concat/concat_dim:0\nORNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/concat:0\nIRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid:0\nKRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid_1:0\nKRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Sigmoid_2:0\nFRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Tanh:0\nHRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Tanh_1:0\nKRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add/Enter:0\nERNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add:0\nIRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_1/y:0\nGRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_1:0\nGRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add_2:0\nSRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/concat/concat_dim:0\nHRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/concat:0\nERNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul:0\nGRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul_1:0\nGRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/mul_2:0\nQRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split/split_dim:0\nGRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split:0\nGRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split:1\nSRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1/split_dim:0\nIRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1:0\nIRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1:1\nIRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1:2\nIRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/split_1:3\n?RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice/begin:0\n>RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice/size:0\n9RNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/Slice:0\nURNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/MatMul/Enter:0\nORNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/MatMul:0\nZRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/concat/concat_dim:0\nORNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/concat:0\nIRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid:0\nKRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid_1:0\nKRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Sigmoid_2:0\nFRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Tanh:0\nHRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Tanh_1:0\nKRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add/Enter:0\nERNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add:0\nIRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_1/y:0\nGRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_1:0\nGRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add_2:0\nSRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/concat/concat_dim:0\nHRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/concat:0\nERNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul:0\nGRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul_1:0\nGRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/mul_2:0\nQRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split/split_dim:0\nGRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split:0\nGRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split:1\nSRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1/split_dim:0\nIRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1:0\nIRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1:1\nIRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1:2\nIRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/split_1:3\n?RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice/begin:0\n>RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice/size:0\n9RNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/Slice:0\n.RNN/while/AttentionCellWrapper/Reshape/shape:0\n(RNN/while/AttentionCellWrapper/Reshape:0\n0RNN/while/AttentionCellWrapper/Reshape_1/shape:0\n*RNN/while/AttentionCellWrapper/Reshape_1:0\n,RNN/while/AttentionCellWrapper/Slice/begin:0\n+RNN/while/AttentionCellWrapper/Slice/size:0\n&RNN/while/AttentionCellWrapper/Slice:0\n.RNN/while/AttentionCellWrapper/Slice_1/begin:0\n-RNN/while/AttentionCellWrapper/Slice_1/size:0\n(RNN/while/AttentionCellWrapper/Slice_1:0\n.RNN/while/AttentionCellWrapper/Slice_2/begin:0\n-RNN/while/AttentionCellWrapper/Slice_2/size:0\n(RNN/while/AttentionCellWrapper/Slice_2:0\n*RNN/while/AttentionCellWrapper/add/Enter:0\n$RNN/while/AttentionCellWrapper/add:0\n2RNN/while/AttentionCellWrapper/concat/concat_dim:0\n'RNN/while/AttentionCellWrapper/concat:0\n4RNN/while/AttentionCellWrapper/concat_1/concat_dim:0\n)RNN/while/AttentionCellWrapper/concat_1:0\n4RNN/while/AttentionCellWrapper/concat_2/concat_dim:0\n)RNN/while/AttentionCellWrapper/concat_2:0\n\021RNN/while/Enter:0\n\023RNN/while/Enter_1:0\n\023RNN/while/Enter_2:0\n\020RNN/while/Exit:0\n\022RNN/while/Exit_1:0\n\022RNN/while/Exit_2:0\n\024RNN/while/Identity:0\n\026RNN/while/Identity_1:0\n\026RNN/while/Identity_2:0\n\026RNN/while/Less/Enter:0\n\020RNN/while/Less:0\n\024RNN/while/LoopCond:0\n\021RNN/while/Merge:0\n\021RNN/while/Merge:1\n\023RNN/while/Merge_1:0\n\023RNN/while/Merge_1:1\n\023RNN/while/Merge_2:0\n\023RNN/while/Merge_2:1\n\031RNN/while/NextIteration:0\n\033RNN/while/NextIteration_1:0\n\033RNN/while/NextIteration_2:0\n\022RNN/while/Switch:0\n\022RNN/while/Switch:1\n\024RNN/while/Switch_1:0\n\024RNN/while/Switch_1:1\n\024RNN/while/Switch_2:0\n\024RNN/while/Switch_2:1\n!RNN/while/TensorArrayRead/Enter:0\n$RNN/while/TensorArrayRead/RefEnter:0\n\033RNN/while/TensorArrayRead:0\n%RNN/while/TensorArrayWrite/RefEnter:0\n\034RNN/while/TensorArrayWrite:0\n\037RNN/while/TensorArray_2/Const:0\n\021RNN/while/add/y:0\n\017RNN/while/add:0\022\247\001\nNRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/read:0\022URNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/MatMul/Enter:0\022Y\n+RNN/AttentionCellWrapper/Linear/Bias/read:0\022*RNN/while/AttentionCellWrapper/add/Enter:0\022g\n/RNN/AttentionCellWrapper/Attention/AttnV/read:0\0224RNN/while/AttentionCellWrapper/Attention/mul/Enter:0\022\233\001\nLRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/read:0\022KRNN/while/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/add/Enter:0\022m\n5RNN/AttentionCellWrapper/Attention/Linear/Bias/read:0\0224RNN/while/AttentionCellWrapper/Attention/add/Enter:0\022\203\001\n@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/read:0\022?RNN/while/AttentionCellWrapper/AttnOutputProjection/add/Enter:0\022e\n-RNN/AttentionCellWrapper/Linear/Matrix/read:0\0224RNN/while/AttentionCellWrapper/Linear/MatMul/Enter:0\022\217\001\nBRNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/read:0\022IRNN/while/AttentionCellWrapper/AttnOutputProjection/Linear/MatMul/Enter:0\022/\n\025RNN/strided_slice_2:0\022\026RNN/while/Less/Enter:0\022M\n(RNN/TensorArrayPack/TensorArrayScatter:0\022!RNN/while/TensorArrayRead/Enter:0\022\233\001\nLRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/read:0\022KRNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/add/Enter:0\022;\n\023RNN/TensorArray_1:0\022$RNN/while/TensorArrayRead/RefEnter:0\022j\n/RNN/AttentionCellWrapper/Attention/AttnW/read:0\0227RNN/while/AttentionCellWrapper/Attention/Conv2D/Enter:0\022y\n7RNN/AttentionCellWrapper/Attention/Linear/Matrix/read:0\022>RNN/while/AttentionCellWrapper/Attention/Linear/MatMul/Enter:0\022:\n\021RNN/TensorArray:0\022%RNN/while/TensorArrayWrite/RefEnter:0\022\247\001\nNRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/read:0\022URNN/while/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/MatMul/Enter:0" | |
} | |
} | |
} | |
collection_def { | |
key: "variables" | |
value { | |
bytes_list { | |
value: "\n(RNN/AttentionCellWrapper/Linear/Matrix:0\022-RNN/AttentionCellWrapper/Linear/Matrix/Assign\032-RNN/AttentionCellWrapper/Linear/Matrix/read:0" | |
value: "\n&RNN/AttentionCellWrapper/Linear/Bias:0\022+RNN/AttentionCellWrapper/Linear/Bias/Assign\032+RNN/AttentionCellWrapper/Linear/Bias/read:0" | |
value: "\nIRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix:0\022NRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Assign\032NRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/read:0" | |
value: "\nGRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias:0\022LRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/Assign\032LRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/read:0" | |
value: "\nIRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix:0\022NRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Assign\032NRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/read:0" | |
value: "\nGRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias:0\022LRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/Assign\032LRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/read:0" | |
value: "\n*RNN/AttentionCellWrapper/Attention/AttnW:0\022/RNN/AttentionCellWrapper/Attention/AttnW/Assign\032/RNN/AttentionCellWrapper/Attention/AttnW/read:0" | |
value: "\n*RNN/AttentionCellWrapper/Attention/AttnV:0\022/RNN/AttentionCellWrapper/Attention/AttnV/Assign\032/RNN/AttentionCellWrapper/Attention/AttnV/read:0" | |
value: "\n2RNN/AttentionCellWrapper/Attention/Linear/Matrix:0\0227RNN/AttentionCellWrapper/Attention/Linear/Matrix/Assign\0327RNN/AttentionCellWrapper/Attention/Linear/Matrix/read:0" | |
value: "\n0RNN/AttentionCellWrapper/Attention/Linear/Bias:0\0225RNN/AttentionCellWrapper/Attention/Linear/Bias/Assign\0325RNN/AttentionCellWrapper/Attention/Linear/Bias/read:0" | |
value: "\n=RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix:0\022BRNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Assign\032BRNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/read:0" | |
value: "\n;RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias:0\022@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/Assign\032@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/read:0" | |
value: "\n\031fully_connected/weights:0\022\036fully_connected/weights/Assign\032\036fully_connected/weights/read:0" | |
value: "\n\030fully_connected/biases:0\022\035fully_connected/biases/Assign\032\035fully_connected/biases/read:0" | |
} | |
} | |
} | |
collection_def { | |
key: "trainable_variables" | |
value { | |
bytes_list { | |
value: "\n(RNN/AttentionCellWrapper/Linear/Matrix:0\022-RNN/AttentionCellWrapper/Linear/Matrix/Assign\032-RNN/AttentionCellWrapper/Linear/Matrix/read:0" | |
value: "\n&RNN/AttentionCellWrapper/Linear/Bias:0\022+RNN/AttentionCellWrapper/Linear/Bias/Assign\032+RNN/AttentionCellWrapper/Linear/Bias/read:0" | |
value: "\nIRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix:0\022NRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/Assign\032NRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix/read:0" | |
value: "\nGRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias:0\022LRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/Assign\032LRNN/AttentionCellWrapper/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias/read:0" | |
value: "\nIRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix:0\022NRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/Assign\032NRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Matrix/read:0" | |
value: "\nGRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias:0\022LRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/Assign\032LRNN/AttentionCellWrapper/MultiRNNCell/Cell1/BasicLSTMCell/Linear/Bias/read:0" | |
value: "\n*RNN/AttentionCellWrapper/Attention/AttnW:0\022/RNN/AttentionCellWrapper/Attention/AttnW/Assign\032/RNN/AttentionCellWrapper/Attention/AttnW/read:0" | |
value: "\n*RNN/AttentionCellWrapper/Attention/AttnV:0\022/RNN/AttentionCellWrapper/Attention/AttnV/Assign\032/RNN/AttentionCellWrapper/Attention/AttnV/read:0" | |
value: "\n2RNN/AttentionCellWrapper/Attention/Linear/Matrix:0\0227RNN/AttentionCellWrapper/Attention/Linear/Matrix/Assign\0327RNN/AttentionCellWrapper/Attention/Linear/Matrix/read:0" | |
value: "\n0RNN/AttentionCellWrapper/Attention/Linear/Bias:0\0225RNN/AttentionCellWrapper/Attention/Linear/Bias/Assign\0325RNN/AttentionCellWrapper/Attention/Linear/Bias/read:0" | |
value: "\n=RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix:0\022BRNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/Assign\032BRNN/AttentionCellWrapper/AttnOutputProjection/Linear/Matrix/read:0" | |
value: "\n;RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias:0\022@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/Assign\032@RNN/AttentionCellWrapper/AttnOutputProjection/Linear/Bias/read:0" | |
value: "\n\031fully_connected/weights:0\022\036fully_connected/weights/Assign\032\036fully_connected/weights/read:0" | |
value: "\n\030fully_connected/biases:0\022\035fully_connected/biases/Assign\032\035fully_connected/biases/read:0" | |
} | |
} | |
} | |
collection_def { | |
key: "final_state" | |
value { | |
node_list { | |
value: "RNN/while/Exit_2:0" | |
} | |
} | |
} | |
collection_def { | |
key: "temperature" | |
value { | |
node_list { | |
value: "Placeholder_1:0" | |
} | |
} | |
} | |
collection_def { | |
key: "initial_state" | |
value { | |
node_list { | |
value: "zeros:0" | |
} | |
} | |
} | |
collection_def { | |
key: "inputs" | |
value { | |
node_list { | |
value: "Placeholder:0" | |
} | |
} | |
} | |
collection_def { | |
key: "model_variables" | |
value { | |
node_list { | |
value: "fully_connected/weights:0" | |
value: "fully_connected/biases:0" | |
} | |
} | |
} | |
collection_def { | |
key: "softmax" | |
value { | |
node_list { | |
value: "Reshape_1:0" | |
} | |
} | |
} | |
) |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment