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layer <network via test_MaskedComputationLayer_beam>/'data' output: Data{'data', [B,T|'time:var:extern_data:data'[B],F|F'feature:data'(5)]}
layer <network via test_MaskedComputationLayer_beam>/'output' output: Data{'output_output', [T|'time:var:extern_data:data'[B&Beam{'output/output'}(3)],B&Beam{'output/output'}(3)], dtype='int32', sparse_dim=DimensionTag{F'classes:sparse-dim'(5)}}
Rec layer 'output' (search True, train False) sub net:
  Input layers moved out of loop: (#: 0)
    None
  Output layers moved out of loop: (#: 0)
    None
  Layers in loop: (#: 5)
    output
    output_prob

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layer <network via test_SliceNdLayer_RangeInAxisLayer>/'data' output: Data{'data', [B,T|'time:var:extern_data:data'[B],F|F'feature:data'(5)]}
layer <network via test_SliceNdLayer_RangeInAxisLayer>/'output' output: Data{'output_output', [T|'time:var:extern_data:data'[B&Beam{'output/output'}(3)],B&Beam{'output/output'}(3)], dtype='int32', sparse=True, dim=5}
Rec layer 'output' (search True, train False) sub net:
  Input layers moved out of loop: (#: 0)
    None
  Output layers moved out of loop: (#: 1)
    slice_range
  Layers in loop: (#: 5)
    slices
    start

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layer <network via test_CompareLayer_in_loop_and_out_loop_sources>/'data' output: Data{'data', [B,T|'time'[B],F|F'feature:data'(5)]}
layer <network via test_CompareLayer_in_loop_and_out_loop_sources>/'data_int' output: Data{'data_int_output', [B,T|'time'[B],F|F'feature:data'(5)], dtype='int32'}
layer <network via test_CompareLayer_in_loop_and_out_loop_sources>/'output' output: Data{'output_output', [T|'time'[B&Beam{'output/output'}(3)],B&Beam{'output/output'}(3)], dtype='int32', sparse_dim=DimensionTag{F'classes:sparse-dim'(5)}}
Rec layer 'output' (search True, train False) sub net:
  Input layers moved out of loop: (#: 0)
    None
  Output layers moved out of loop: (#: 0)
    None
  Layers in loop: (#: 5)
    output

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layer <network via test_concat_new_dim_tag>/'data' output: Data{'data', [B,T|'time'[B],F|F'feature:data'(5)]}
layer <network via test_concat_new_dim_tag>/'data_new' output: Data{'data_new_output', [B,T|'new-time'[?],F|F'feature:data'(5)]}
layer <network via test_concat_new_dim_tag>/'output' output: Data{'output_output', [T|'time'[B&Beam{'output/output'}(3)],B&Beam{'output/output'}(3)], dtype='int32', sparse_dim=DimensionTag{F'classes:sparse-dim'(5)}}
Rec layer 'output' (search True, train False) sub net:
  Input layers moved out of loop: (#: 0)
    None
  Output layers moved out of loop: (#: 0)
    None
  Layers in loop: (#: 7)
    output

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layer <network via test_SliceNdLayer_ReinterpretDataLayer>/'data' output: Data{'data', [B,T|'time:var:extern_data:data'[B],F|F'feature:data'(5)]}
layer <network via test_SliceNdLayer_ReinterpretDataLayer>/'data:classes' output: Data{'classes', [B,T|'time:var:extern_data:classes'[B]], dtype='int32', sparse_dim=DimensionTag{F'classes:sparse-dim'(5)}, available_for_inference=False}
layer <network via test_SliceNdLayer_ReinterpretDataLayer>/'start' output: Data{'start_output', [B,T|'time:var:extern_data:classes'[B]], dtype='int32', available_for_inference=False}
layer <network via test_SliceNdLayer_ReinterpretDataLayer>/'slices' output: Data{'slices_gather_output', [B,T|'time:var:extern_data:classes'[B],'sliced-time:slices'[?],F|F'feature:data'(5)], available_for_inference=False}
layer <network via test_SliceNdLayer_ReinterpretDataLayer>/'output' output: Data{'output_output', [B,T|'time:var:extern_data:classes'[B],'new-slice'[?],F|F'feature:data'(5)], available_for_inference=False}
Exception creating layer <netwo

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meta_info_def {
  stripped_op_list {
    op {
      name: "Add"
      input_arg {
        name: "x"
        type_attr: "T"
      }
      input_arg {
        name: "y"

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Create graph...
Loading network, train flag False, eval flag False, search flag False
DEPRECATION WARNING: Missing "from" in layer definition: root/source
This will be disallowed with behavior_version 1.
layer root/'data' output: Data{'data', [B,T|'time'[B],F|F'feature:data'(40)]}
layer root/'source' output: Data{'data', [B,T|'time'[B],F|F'feature:data'(40)]}
layer root/'source0' output: Data{'source0_output', [B,T|'time'[B],F'feature:data'(40),F|F'source0_split_dims1'(1)]}
DEPRECATION WARNING: Explicitly specify in_spatial_dims when there is more than one spatial dim in the input.
This will be disallowed with behavior_version 8.
layer root/'conv0' output: Data{'conv0_output', [B,T|'time'[B],F'feature:data'(40),F|F'conv0:channel'(32)]}

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TypeError creating layer /'lstm0_pool' of class PoolLayer with opts:
{'_name': 'lstm0_pool',
 '_network': <TFNetwork '' train=<tf.Tensor 'globals/train_flag:0' shape=() dtype=bool>>,
 'mode': 'max',
 'name': 'lstm0_pool',
 'network': <TFNetwork '' train=<tf.Tensor 'globals/train_flag:0' shape=() dtype=bool>>,
 'padding': 'same',
 'pool_size': (6,),
 'sources': [<RecLayer 'lstm0_fw' out_type=Data{[T|'time'[B],B,F|F'lstm0_fw:feature'(512)]}>,
             <RecLayer 'lstm0_bw' out_type=Data{[T|'time'[B],B,F|F'lstm0_bw:feature'(512)]}>]}

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#!rnn.py


from returnn.tf.util.data import Dim
import os
import numpy as np
from subprocess import check_output, CalledProcessError


def _mask(x, batch_axis, axis, pos, max_amount, mask_value=0.0):

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meta_info_def {
  stripped_op_list {
    op {
      name: "Add"
      input_arg {
        name: "x"
        type_attr: "T"
      }
      input_arg {
        name: "y"