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April 25, 2021 03:07
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Tensorflow error
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| WARNING:tensorflow:AutoGraph could not transform <function WhileV2.__call__.<locals>.while_fn at 0x7f3eaa4711f0> and will run it as-is. | |
| Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. | |
| Cause: module 'gast' has no attribute 'Index' | |
| To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert | |
| ERROR:tensorflow:Got error while pfor was converting op name: "custom_loss/loop_body/while" | |
| op: "StatelessWhile" | |
| input: "custom_loss/loop_body/while/loop_counter" | |
| input: "custom_loss/loop_body/while/maximum_iterations" | |
| input: "custom_loss/loop_body/GatherV2" | |
| attr { | |
| key: "T" | |
| value { | |
| list { | |
| type: DT_INT32 | |
| type: DT_INT32 | |
| type: DT_FLOAT | |
| } | |
| } | |
| } | |
| attr { | |
| key: "_lower_using_switch_merge" | |
| value { | |
| b: true | |
| } | |
| } | |
| attr { | |
| key: "_num_original_outputs" | |
| value { | |
| i: 3 | |
| } | |
| } | |
| attr { | |
| key: "_read_only_resource_inputs" | |
| value { | |
| list { | |
| } | |
| } | |
| } | |
| attr { | |
| key: "body" | |
| value { | |
| func { | |
| name: "custom_loss_loop_body_while_body_318" | |
| } | |
| } | |
| } | |
| attr { | |
| key: "cond" | |
| value { | |
| func { | |
| name: "custom_loss_loop_body_while_cond_317" | |
| } | |
| } | |
| } | |
| attr { | |
| key: "output_shapes" | |
| value { | |
| list { | |
| shape { | |
| } | |
| shape { | |
| } | |
| shape { | |
| dim { | |
| size: 2 | |
| } | |
| } | |
| } | |
| } | |
| } | |
| attr { | |
| key: "parallel_iterations" | |
| value { | |
| i: 10 | |
| } | |
| } | |
| with inputs (<tf.Tensor 'custom_loss/loop_body/while/loop_counter:0' shape=() dtype=int32>, <tf.Tensor 'custom_loss/loop_body/while/maximum_iterations:0' shape=() dtype=int32>, <tf.Tensor 'custom_loss/loop_body/GatherV2:0' shape=(2,) dtype=float32>) | |
| , converted inputs [WrappedTensor(t=<tf.Tensor 'custom_loss/loop_body/while/loop_counter:0' shape=() dtype=int32>, is_stacked=False, is_sparse_stacked=False), WrappedTensor(t=<tf.Tensor 'custom_loss/loop_body/while/maximum_iterations:0' shape=() dtype=int32>, is_stacked=False, is_sparse_stacked=False), WrappedTensor(t=<tf.Tensor 'custom_loss/loop_body/GatherV2/pfor/GatherV2:0' shape=(None, 2) dtype=float32>, is_stacked=True, is_sparse_stacked=False)] | |
| Shape must be at least rank 2 but is rank 1 for '{{node while/DynamicPartition}} = DynamicPartition[T=DT_INT32, num_partitions=2](while/Placeholder_1, while/Cast)' with input shapes: [?], [?,2]. | |
| Here are the pfor conversion stack traces: | |
| ERROR:tensorflow:name: "custom_loss/loop_body/while" | |
| op: "StatelessWhile" | |
| input: "custom_loss/loop_body/while/loop_counter" | |
| input: "custom_loss/loop_body/while/maximum_iterations" | |
| input: "custom_loss/loop_body/GatherV2" | |
| attr { | |
| key: "T" | |
| value { | |
| list { | |
| type: DT_INT32 | |
| type: DT_INT32 | |
| type: DT_FLOAT | |
| } | |
| } | |
| } | |
| attr { | |
| key: "_lower_using_switch_merge" | |
| value { | |
| b: true | |
| } | |
| } | |
| attr { | |
| key: "_num_original_outputs" | |
| value { | |
| i: 3 | |
| } | |
| } | |
| attr { | |
| key: "_read_only_resource_inputs" | |
| value { | |
| list { | |
| } | |
| } | |
| } | |
| attr { | |
| key: "body" | |
| value { | |
| func { | |
| name: "custom_loss_loop_body_while_body_318" | |
| } | |
| } | |
| } | |
| attr { | |
| key: "cond" | |
| value { | |
| func { | |
| name: "custom_loss_loop_body_while_cond_317" | |
| } | |
| } | |
| } | |
| attr { | |
| key: "output_shapes" | |
| value { | |
| list { | |
| shape { | |
| } | |
| shape { | |
| } | |
| shape { | |
| dim { | |
| size: 2 | |
| } | |
| } | |
| } | |
| } | |
| } | |
| attr { | |
| key: "parallel_iterations" | |
| value { | |
| i: 10 | |
| } | |
| } | |
| created at: | |
| File "./ann.py", line 118, in <module> | |
| train_model(autoencoder, encoder, train_data, test_data) | |
| File "./ann.py", line 85, in train_model | |
| autoencoder_model.fit(x_train, x_train, | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1100, in fit | |
| tmp_logs = self.train_function(iterator) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 828, in __call__ | |
| result = self._call(*args, **kwds) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 871, in _call | |
| self._initialize(args, kwds, add_initializers_to=initializers) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 725, in _initialize | |
| self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2969, in _get_concrete_function_internal_garbage_collected | |
| graph_function, _ = self._maybe_define_function(args, kwargs) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3361, in _maybe_define_function | |
| graph_function = self._create_graph_function(args, kwargs) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3196, in _create_graph_function | |
| func_graph_module.func_graph_from_py_func( | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 990, in func_graph_from_py_func | |
| func_outputs = python_func(*func_args, **func_kwargs) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 634, in wrapped_fn | |
| out = weak_wrapped_fn().__wrapped__(*args, **kwds) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 966, in wrapper | |
| return autograph.converted_call( | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 805, in train_function | |
| return step_function(self, iterator) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 795, in step_function | |
| outputs = model.distribute_strategy.run(run_step, args=(data,)) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py", line 1259, in run | |
| return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py", line 2730, in call_for_each_replica | |
| return self._call_for_each_replica(fn, args, kwargs) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py", line 3417, in _call_for_each_replica | |
| return fn(*args, **kwargs) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 788, in run_step | |
| outputs = model.train_step(data) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 755, in train_step | |
| loss = self.compiled_loss( | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/keras/engine/compile_utils.py", line 203, in __call__ | |
| loss_value = loss_obj(y_t, y_p, sample_weight=sw) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/keras/losses.py", line 152, in __call__ | |
| losses = call_fn(y_true, y_pred) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/keras/losses.py", line 256, in call | |
| return ag_fn(y_true, y_pred, **self._fn_kwargs) | |
| File "./ann.py", line 20, in custom_loss | |
| diff = tf.vectorized_map(wrap, diff) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/control_flow_ops.py", line 489, in vectorized_map | |
| return pfor(loop_fn, batch_size, | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/control_flow_ops.py", line 205, in pfor | |
| outputs = f() | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/control_flow_ops.py", line 187, in f | |
| return _pfor_impl(loop_fn, | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/control_flow_ops.py", line 248, in _pfor_impl | |
| loop_fn_outputs = loop_fn(loop_var) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/control_flow_ops.py", line 472, in loop_fn | |
| return fn(gathered_elems) | |
| File "./ann.py", line 10, in wrap | |
| return tf.while_loop( | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/util/deprecation.py", line 605, in new_func | |
| return func(*args, **kwargs) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2489, in while_loop_v2 | |
| return while_loop( | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2687, in while_loop | |
| return while_v2.while_loop( | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/while_v2.py", line 273, in while_loop | |
| outputs = _build_while_op( | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/while_v2.py", line 432, in _build_while_op | |
| outputs = op_fn( | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/gen_functional_ops.py", line 1001, in stateless_while | |
| _, _, _op, _outputs = _op_def_library._apply_op_helper( | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/op_def_library.py", line 748, in _apply_op_helper | |
| op = g._create_op_internal(op_type_name, inputs, dtypes=None, | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 590, in _create_op_internal | |
| return super(FuncGraph, self)._create_op_internal( # pylint: disable=protected-access | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/ops.py", line 3528, in _create_op_internal | |
| ret = Operation( | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/ops.py", line 1990, in __init__ | |
| self._traceback = tf_stack.extract_stack() | |
| Traceback (most recent call last): | |
| File "./ann.py", line 118, in <module> | |
| train_model(autoencoder, encoder, train_data, test_data) | |
| File "./ann.py", line 85, in train_model | |
| autoencoder_model.fit(x_train, x_train, | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1100, in fit | |
| tmp_logs = self.train_function(iterator) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 828, in __call__ | |
| result = self._call(*args, **kwds) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 871, in _call | |
| self._initialize(args, kwds, add_initializers_to=initializers) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 725, in _initialize | |
| self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2969, in _get_concrete_function_internal_garbage_collected | |
| graph_function, _ = self._maybe_define_function(args, kwargs) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3361, in _maybe_define_function | |
| graph_function = self._create_graph_function(args, kwargs) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3196, in _create_graph_function | |
| func_graph_module.func_graph_from_py_func( | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 990, in func_graph_from_py_func | |
| func_outputs = python_func(*func_args, **func_kwargs) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 634, in wrapped_fn | |
| out = weak_wrapped_fn().__wrapped__(*args, **kwds) | |
| File "/home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 977, in wrapper | |
| raise e.ag_error_metadata.to_exception(e) | |
| ValueError: in user code: | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:805 train_function * | |
| return step_function(self, iterator) | |
| ./ann.py:20 custom_loss * | |
| diff = tf.vectorized_map(wrap, diff) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/control_flow_ops.py:489 vectorized_map ** | |
| return pfor(loop_fn, batch_size, | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/control_flow_ops.py:205 pfor | |
| outputs = f() | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/control_flow_ops.py:187 f | |
| return _pfor_impl(loop_fn, | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/control_flow_ops.py:288 _pfor_impl | |
| output = converter.convert(loop_fn_output) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/pfor.py:1384 convert | |
| output = self._convert_helper(y) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/pfor.py:1600 _convert_helper | |
| six.reraise(e.__class__, e, sys.exc_info()[2]) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/six.py:703 reraise | |
| raise value | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/pfor.py:1581 _convert_helper | |
| new_outputs = converter(pfor_inputs) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/pfor.py:4570 _convert_while | |
| return converter() | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/pfor.py:4544 __call__ | |
| _ = while_fn.get_concrete_function() | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py:1299 get_concrete_function | |
| concrete = self._get_concrete_function_garbage_collected(*args, **kwargs) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py:1205 _get_concrete_function_garbage_collected | |
| self._initialize(args, kwargs, add_initializers_to=initializers) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py:725 _initialize | |
| self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/function.py:2969 _get_concrete_function_internal_garbage_collected | |
| graph_function, _ = self._maybe_define_function(args, kwargs) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/function.py:3361 _maybe_define_function | |
| graph_function = self._create_graph_function(args, kwargs) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/function.py:3196 _create_graph_function | |
| func_graph_module.func_graph_from_py_func( | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py:990 func_graph_from_py_func | |
| func_outputs = python_func(*func_args, **func_kwargs) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py:634 wrapped_fn | |
| out = weak_wrapped_fn().__wrapped__(*args, **kwds) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py:966 wrapper | |
| return autograph.converted_call( | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/pfor.py:4520 while_fn ** | |
| while_outputs = control_flow_ops.while_loop( | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/control_flow_ops.py:2687 while_loop | |
| return while_v2.while_loop( | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/while_v2.py:192 while_loop | |
| body_graph = func_graph_module.func_graph_from_py_func( | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py:990 func_graph_from_py_func | |
| func_outputs = python_func(*func_args, **func_kwargs) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/while_v2.py:178 wrapped_body | |
| outputs = body(*_pack_sequence_as(orig_loop_vars, args)) | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/pfor.py:4489 body | |
| new_output_tas) = self._process_cond_stacked(conditions, indices, | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/parallel_for/pfor.py:4317 _process_cond_stacked | |
| done_indices, new_indices = data_flow_ops.dynamic_partition( | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/ops/gen_data_flow_ops.py:665 dynamic_partition | |
| _, _, _op, _outputs = _op_def_library._apply_op_helper( | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/op_def_library.py:748 _apply_op_helper | |
| op = g._create_op_internal(op_type_name, inputs, dtypes=None, | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py:590 _create_op_internal | |
| return super(FuncGraph, self)._create_op_internal( # pylint: disable=protected-access | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/ops.py:3528 _create_op_internal | |
| ret = Operation( | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/ops.py:2015 __init__ | |
| self._c_op = _create_c_op(self._graph, node_def, inputs, | |
| /home/hanatok/anaconda3/envs/tf-gpu/lib/python3.8/site-packages/tensorflow/python/framework/ops.py:1856 _create_c_op | |
| raise ValueError(str(e)) | |
| ValueError: Shape must be at least rank 2 but is rank 1 for '{{node while/DynamicPartition}} = DynamicPartition[T=DT_INT32, num_partitions=2](while/Placeholder_1, while/Cast)' with input shapes: [?], [?,2]. |
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