stacktrace.txt

EXCEPTION
Traceback (most recent call last):
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/tools/torch_export_to_onnx.py", line 209, in <module>
    line: main()
    locals:
      main = <local> <function main at 0x7f638c451750>
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/tools/torch_export_to_onnx.py", line 197, in main
    line: export_func(
              pt_model_fwd,
              (extern_data_raw, {}),
              f=args.out_onnx_filename,
              verbose=True,
              input_names=list(extern_data_raw.keys()),
              output_names=model_outputs_raw_keys,
              dynamic_axes=dynamic_axes,
          )
    locals:
      export_func = <local> <function export at 0x7f638da628c0>
      pt_model_fwd = <local> ForwardModulePT(
                               (model): Model(
                                 (layers): Sequential(
                                   (0): Conv1d(9, 50, kernel_size=(5,), stride=(1,), padding=(2,))
                                   (1): ReLU()
                                   (2): Conv1d(50, 100, kernel_size=(5,), stride=(1,), padding=(2,))
                                   (3): ReLU()
                                   (4): Conv1d(100, 2, kernel_size=(5,), stride=(1,), p...
      extern_data_raw = <local> {'data': tensor([[[ 7.9832e-02, -1.5952e-01,  2.2222e-02, -4.2779e-01, -5.3182e-01,
                                          -1.1748e-01,  2.2208e-01, -7.6798e-01,  1.4246e-01],
                                         [-3.4652e-02,  1.1343e+00, -1.0475e-01, -5.2512e-01,  1.9128e+00,
                                          -2.0267e+00,  1.1194e+00,  7.7919e-01, -1.1011e+00],
                                         [ 1..., len = 6
      f = <not found>
      args = <local> Namespace(config='demos/demo-torch.config', checkpoint='/tmp/icemole/returnn/demos/demo-torch/model.005.pt', out_onnx_filename='/tmp/icemole/returnn/demos/demo-torch/model.005.onnx', verbosity=4, device='cpu')
      args.out_onnx_filename = <local> '/tmp/icemole/returnn/demos/demo-torch/model.005.onnx', len = 52
      verbose = <not found>
      input_names = <not found>
      list = <builtin> <class 'list'>
      extern_data_raw.keys = <local> <built-in method keys of dict object at 0x7f638c2d5080>
      output_names = <not found>
      model_outputs_raw_keys = <local> ['output', 'output:size0', 'output:size1'], _[0]: {len = 6}
      dynamic_axes = <local> {'data': {0: 'batch:data', 1: 'time:var-unk:data'}, 'data:size0': {}, 'data:size1': {0: 'batch:data_dim0_size'}, 'classes': {0: 'batch:classes', 1: 'time:var-unk:classes'}, 'classes:size0': {}, 'classes:size1': {0: 'batch:classes_dim0_size'}, 'output': {0: 'batch:output', 1: 'time:var-unk:output'..., len = 8
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/onnx/utils.py", line 504, in export
    line: _export(
              model,
              args,
              f,
              export_params,
              verbose,
              training,
              input_names,
              output_names,
              operator_export_type=operator_export_type,
              opset_version=opset_version,
              do_constant_folding=do_constant_folding,
              dynamic_axes=dynamic_axes,
              keep_initializers_as_inputs=keep_initializers_as_inputs,
              custom_opsets=custom_opsets,
              export_modules_as_functions=export_modules_as_functions,
          )
    locals:
      _export = <global> <function _export at 0x7f638da63760>
      model = <local> ForwardModulePT(
                        (model): Model(
                          (layers): Sequential(
                            (0): Conv1d(9, 50, kernel_size=(5,), stride=(1,), padding=(2,))
                            (1): ReLU()
                            (2): Conv1d(50, 100, kernel_size=(5,), stride=(1,), padding=(2,))
                            (3): ReLU()
                            (4): Conv1d(100, 2, kernel_size=(5,), stride=(1,), p...
      args = <local> ({'data': tensor([[[ 7.9832e-02, -1.5952e-01,  2.2222e-02, -4.2779e-01, -5.3182e-01,
                               -1.1748e-01,  2.2208e-01, -7.6798e-01,  1.4246e-01],
                              [-3.4652e-02,  1.1343e+00, -1.0475e-01, -5.2512e-01,  1.9128e+00,
                               -2.0267e+00,  1.1194e+00,  7.7919e-01, -1.1011e+00],
                              [ ..., _[0]: {len = 6}
      f = <local> '/tmp/icemole/returnn/demos/demo-torch/model.005.onnx', len = 52
      export_params = <local> True
      verbose = <local> True
      training = <local> <TrainingMode.EVAL: 0>
      input_names = <local> ['data', 'data:size0', 'data:size1', 'classes', 'classes:size0', 'classes:size1'], len = 6
      output_names = <local> ['output', 'output:size0', 'output:size1'], _[0]: {len = 6}
      operator_export_type = <local> <OperatorExportTypes.ONNX: 0>
      opset_version = <local> None
      do_constant_folding = <local> True
      dynamic_axes = <local> {'data': {0: 'batch:data', 1: 'time:var-unk:data'}, 'data:size0': {}, 'data:size1': {0: 'batch:data_dim0_size'}, 'classes': {0: 'batch:classes', 1: 'time:var-unk:classes'}, 'classes:size0': {}, 'classes:size1': {0: 'batch:classes_dim0_size'}, 'output': {0: 'batch:output', 1: 'time:var-unk:output'..., len = 8
      keep_initializers_as_inputs = <local> None
      custom_opsets = <local> None
      export_modules_as_functions = <local> False
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/onnx/utils.py", line 1529, in _export
    line: graph, params_dict, torch_out = _model_to_graph(
              model,
              args,
              verbose,
              input_names,
              output_names,
              operator_export_type,
              val_do_constant_folding,
              fixed_batch_size=fixed_batch_size,
              training=training,
              dynamic_axes=dynamic_axes,
          )
    locals:
      graph = <not found>
      params_dict = <not found>
      torch_out = <not found>
      _model_to_graph = <global> <function _model_to_graph at 0x7f638da63400>
      model = <local> ForwardModulePT(
                        (model): Model(
                          (layers): Sequential(
                            (0): Conv1d(9, 50, kernel_size=(5,), stride=(1,), padding=(2,))
                            (1): ReLU()
                            (2): Conv1d(50, 100, kernel_size=(5,), stride=(1,), padding=(2,))
                            (3): ReLU()
                            (4): Conv1d(100, 2, kernel_size=(5,), stride=(1,), p...
      args = <local> ({'data': tensor([[[ 7.9832e-02, -1.5952e-01,  2.2222e-02, -4.2779e-01, -5.3182e-01,
                               -1.1748e-01,  2.2208e-01, -7.6798e-01,  1.4246e-01],
                              [-3.4652e-02,  1.1343e+00, -1.0475e-01, -5.2512e-01,  1.9128e+00,
                               -2.0267e+00,  1.1194e+00,  7.7919e-01, -1.1011e+00],
                              [ ..., _[0]: {len = 6}
      verbose = <local> True
      input_names = <local> ['data', 'data:size0', 'data:size1', 'classes', 'classes:size0', 'classes:size1'], len = 6
      output_names = <local> ['output', 'output:size0', 'output:size1'], _[0]: {len = 6}
      operator_export_type = <local> <OperatorExportTypes.ONNX: 0>
      val_do_constant_folding = <local> True
      fixed_batch_size = <local> False
      training = <local> <TrainingMode.EVAL: 0>
      dynamic_axes = <local> {'data': {0: 'batch:data', 1: 'time:var-unk:data'}, 'data:size0': {}, 'data:size1': {0: 'batch:data_dim0_size'}, 'classes': {0: 'batch:classes', 1: 'time:var-unk:classes'}, 'classes:size0': {}, 'classes:size1': {0: 'batch:classes_dim0_size'}, 'output': {0: 'batch:output', 1: 'time:var-unk:output'..., len = 8
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/onnx/utils.py", line 1111, in _model_to_graph
    line: graph, params, torch_out, module = _create_jit_graph(model, args)
    locals:
      graph = <not found>
      params = <not found>
      torch_out = <not found>
      module = <not found>
      _create_jit_graph = <global> <function _create_jit_graph at 0x7f638da63130>
      model = <local> ForwardModulePT(
                        (model): Model(
                          (layers): Sequential(
                            (0): Conv1d(9, 50, kernel_size=(5,), stride=(1,), padding=(2,))
                            (1): ReLU()
                            (2): Conv1d(50, 100, kernel_size=(5,), stride=(1,), padding=(2,))
                            (3): ReLU()
                            (4): Conv1d(100, 2, kernel_size=(5,), stride=(1,), p...
      args = <local> ({'data': tensor([[[ 7.9832e-02, -1.5952e-01,  2.2222e-02, -4.2779e-01, -5.3182e-01,
                               -1.1748e-01,  2.2208e-01, -7.6798e-01,  1.4246e-01],
                              [-3.4652e-02,  1.1343e+00, -1.0475e-01, -5.2512e-01,  1.9128e+00,
                               -2.0267e+00,  1.1194e+00,  7.7919e-01, -1.1011e+00],
                              [ ..., _[0]: {len = 6}
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/onnx/utils.py", line 987, in _create_jit_graph
    line: graph, torch_out = _trace_and_get_graph_from_model(model, args)
    locals:
      graph = <not found>
      torch_out = <not found>
      _trace_and_get_graph_from_model = <global> <function _trace_and_get_graph_from_model at 0x7f638da62f80>
      model = <local> ForwardModulePT(
                        (model): Model(
                          (layers): Sequential(
                            (0): Conv1d(9, 50, kernel_size=(5,), stride=(1,), padding=(2,))
                            (1): ReLU()
                            (2): Conv1d(50, 100, kernel_size=(5,), stride=(1,), padding=(2,))
                            (3): ReLU()
                            (4): Conv1d(100, 2, kernel_size=(5,), stride=(1,), p...
      args = <local> ({'data': tensor([[[ 7.9832e-02, -1.5952e-01,  2.2222e-02, -4.2779e-01, -5.3182e-01,
                               -1.1748e-01,  2.2208e-01, -7.6798e-01,  1.4246e-01],
                              [-3.4652e-02,  1.1343e+00, -1.0475e-01, -5.2512e-01,  1.9128e+00,
                               -2.0267e+00,  1.1194e+00,  7.7919e-01, -1.1011e+00],
                              [ ..., _[0]: {len = 6}
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/onnx/utils.py", line 891, in _trace_and_get_graph_from_model
    line: trace_graph, torch_out, inputs_states = torch.jit._get_trace_graph(
              model,
              args,
              strict=False,
              _force_outplace=False,
              _return_inputs_states=True,
          )
    locals:
      trace_graph = <not found>
      torch_out = <not found>
      inputs_states = <not found>
      torch = <global> <module 'torch' from '/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/__init__.py'>
      torch.jit = <global> <module 'torch.jit' from '/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/jit/__init__.py'>
      torch.jit._get_trace_graph = <global> <function _get_trace_graph at 0x7f638dc13490>
      model = <local> ForwardModulePT(
                        (model): Model(
                          (layers): Sequential(
                            (0): Conv1d(9, 50, kernel_size=(5,), stride=(1,), padding=(2,))
                            (1): ReLU()
                            (2): Conv1d(50, 100, kernel_size=(5,), stride=(1,), padding=(2,))
                            (3): ReLU()
                            (4): Conv1d(100, 2, kernel_size=(5,), stride=(1,), p...
      args = <local> ({'data': tensor([[[ 7.9832e-02, -1.5952e-01,  2.2222e-02, -4.2779e-01, -5.3182e-01,
                               -1.1748e-01,  2.2208e-01, -7.6798e-01,  1.4246e-01],
                              [-3.4652e-02,  1.1343e+00, -1.0475e-01, -5.2512e-01,  1.9128e+00,
                               -2.0267e+00,  1.1194e+00,  7.7919e-01, -1.1011e+00],
                              [ ..., _[0]: {len = 6}
      strict = <not found>
      _force_outplace = <not found>
      _return_inputs_states = <not found>
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/jit/_trace.py", line 1184, in _get_trace_graph
    line: outs = ONNXTracedModule(f, strict, _force_outplace, return_inputs, _return_inputs_states)(*args, **kwargs)
    locals:
      outs = <not found>
      ONNXTracedModule = <global> <class 'torch.jit._trace.ONNXTracedModule'>
      f = <local> ForwardModulePT(
                    (model): Model(
                      (layers): Sequential(
                        (0): Conv1d(9, 50, kernel_size=(5,), stride=(1,), padding=(2,))
                        (1): ReLU()
                        (2): Conv1d(50, 100, kernel_size=(5,), stride=(1,), padding=(2,))
                        (3): ReLU()
                        (4): Conv1d(100, 2, kernel_size=(5,), stride=(1,), p...
      strict = <local> False
      _force_outplace = <local> False
      return_inputs = <local> False
      _return_inputs_states = <local> True
      args = <local> ({'data': tensor([[[ 7.9832e-02, -1.5952e-01,  2.2222e-02, -4.2779e-01, -5.3182e-01,
                               -1.1748e-01,  2.2208e-01, -7.6798e-01,  1.4246e-01],
                              [-3.4652e-02,  1.1343e+00, -1.0475e-01, -5.2512e-01,  1.9128e+00,
                               -2.0267e+00,  1.1194e+00,  7.7919e-01, -1.1011e+00],
                              [ ..., _[0]: {len = 6}
      kwargs = <local> {}
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in Module._call_impl
    line: return forward_call(*input, **kwargs)
    locals:
      forward_call = <local> <bound method ONNXTracedModule.forward of ONNXTracedModule(
                               (inner): ForwardModulePT(
                                 (model): Model(
                                   (layers): Sequential(
                                     (0): Conv1d(9, 50, kernel_size=(5,), stride=(1,), padding=(2,))
                                     (1): ReLU()
                                     (2): Conv1d(50, 100, kernel_size=(5,), stride=(1,), padding=(...
      input = <local> ({'data': tensor([[[ 7.9832e-02, -1.5952e-01,  2.2222e-02, -4.2779e-01, -5.3182e-01,
                                -1.1748e-01,  2.2208e-01, -7.6798e-01,  1.4246e-01],
                               [-3.4652e-02,  1.1343e+00, -1.0475e-01, -5.2512e-01,  1.9128e+00,
                                -2.0267e+00,  1.1194e+00,  7.7919e-01, -1.1011e+00],
                               [ ..., _[0]: {len = 6}
      kwargs = <local> {}
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/jit/_trace.py", line 127, in ONNXTracedModule.forward
    line: graph, out = torch._C._create_graph_by_tracing(
              wrapper,
              in_vars + module_state,
              _create_interpreter_name_lookup_fn(),
              self.strict,
              self._force_outplace,
          )
    locals:
      graph = <not found>
      out = <not found>
      torch = <global> <module 'torch' from '/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/__init__.py'>
      torch._C = <global> <module 'torch._C' from '/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/_C.cpython-310-x86_64-linux-gnu.so'>
      torch._C._create_graph_by_tracing = <global> <built-in method _create_graph_by_tracing of PyCapsule object at 0x7f641a31cb70>
      wrapper = <local> <function ONNXTracedModule.forward.<locals>.wrapper at 0x7f638c2bf7f0>
      in_vars = <local> [tensor([[[ 7.9832e-02, -1.5952e-01,  2.2222e-02, -4.2779e-01, -5.3182e-01,
                                  -1.1748e-01,  2.2208e-01, -7.6798e-01,  1.4246e-01],
                                 [-3.4652e-02,  1.1343e+00, -1.0475e-01, -5.2512e-01,  1.9128e+00,
                                  -2.0267e+00,  1.1194e+00,  7.7919e-01, -1.1011e+00],
                                 [ 1.1302e+0..., len = 6
      module_state = <local> [Parameter containing:
                             tensor([[[ 0.2969,  0.1807, -0.2058, -0.5377, -0.0236],
                                      [-0.2986,  0.1896,  0.6093,  0.2943,  0.0186],
                                      [-0.0740, -0.2344, -0.1361, -0.0865,  0.1116],
                                      ...,
                                      [-0.0398, -0.2474, -0.2914, -0.2815, -0.3621],
                                      [-0.0245, -0.2042, -0.2577,..., len = 6
      _create_interpreter_name_lookup_fn = <global> <function _create_interpreter_name_lookup_fn at 0x7f638dc124d0>
      self = <local> ONNXTracedModule(
                       (inner): ForwardModulePT(
                         (model): Model(
                           (layers): Sequential(
                             (0): Conv1d(9, 50, kernel_size=(5,), stride=(1,), padding=(2,))
                             (1): ReLU()
                             (2): Conv1d(50, 100, kernel_size=(5,), stride=(1,), padding=(2,))
                             (3): ReLU()
                             (4): Conv...
      self.strict = <local> False
      self._force_outplace = <local> False
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/venv/lib/python3.10/site-packages/torch/jit/_trace.py", line 118, in ONNXTracedModule.forward.<locals>.wrapper
    line: outs.append(self.inner(*trace_inputs))
    locals:
      outs = <local> []
      outs.append = <local> <built-in method append of list object at 0x7f638c2f8b40>
      self = <local> ONNXTracedModule(
                       (inner): ForwardModulePT(
                         (model): Model(
                           (layers): Sequential(
                             (0): Conv1d(9, 50, kernel_size=(5,), stride=(1,), padding=(2,))
                             (1): ReLU()
                             (2): Conv1d(50, 100, kernel_size=(5,), stride=(1,), padding=(2,))
                             (3): ReLU()
                             (4): Conv...
      self.inner = <local> ForwardModulePT(
                             (model): Model(
                               (layers): Sequential(
                                 (0): Conv1d(9, 50, kernel_size=(5,), stride=(1,), padding=(2,))
                                 (1): ReLU()
                                 (2): Conv1d(50, 100, kernel_size=(5,), stride=(1,), padding=(2,))
                                 (3): ReLU()
                                 (4): Conv1d(100, 2, kernel_size=(5,), stride=(1,), p...
      trace_inputs = <local> ({'data': tensor([[[ 7.9832e-02, -1.5952e-01,  2.2222e-02, -4.2779e-01, -5.3182e-01,
                                       -1.1748e-01,  2.2208e-01, -7.6798e-01,  1.4246e-01],
                                      [-3.4652e-02,  1.1343e+00, -1.0475e-01, -5.2512e-01,  1.9128e+00,
                                       -2.0267e+00,  1.1194e+00,  7.7919e-01, -1.1011e+00],
                                      [ ..., _[0]: {len = 6}
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/tools/torch_export_to_onnx.py", line 87, in ForwardModulePT.__call__
    line: return rf.get_run_ctx().outputs.as_raw_tensor_dict()
    locals:
      rf = <global> <module 'returnn.frontend' from '/home/icemole/Documentos/work/repos/returnn_pytorch/returnn/frontend/__init__.py'>
      rf.get_run_ctx = <global> <function get_run_ctx at 0x7f638c439870>
      outputs = <not found>
      outputs.as_raw_tensor_dict = <not found>
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/returnn/tensor/tensor_dict.py", line 88, in TensorDict.as_raw_tensor_dict
    line: out[key_] = dim.get_dim_value()
    locals:
      out = <local> {'output': tensor([[[  7.4615,  -8.9174],
                             [ 12.0366, -13.1756],
                             [ 27.6231, -29.9030],
                             [ 25.2957, -26.7124],
                             [ 40.0092, -42.1561],
                             [ 24.7264, -26.0574],
                             [ 49.5347, -50.2851],
                             [ 28.1509, -28.4984],
                             [ 42.6256, -44.0171],
                           ...
      key_ = <local> 'output:size0', len = 12
      dim = <local> Dim{B}
      dim.get_dim_value = <local> <bound method _DimMixin.get_dim_value of Dim{B}>
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/returnn/tensor/_dim_extra.py", line 1656, in _DimMixin.get_dim_value
    line: res = self.get_dim_value_tensor()
    locals:
      res = <not found>
      self = <local> Dim{B}
      self.get_dim_value_tensor = <local> <bound method _DimMixin.get_dim_value_tensor of Dim{B}>
  File "/home/icemole/Documentos/work/repos/returnn_pytorch/returnn/tensor/_dim_extra.py", line 1710, in _DimMixin.get_dim_value_tensor
    line: raise Exception("%s: need placeholder, self.dimension or self.dyn_size for dim value" % self)
    locals:
      Exception = <builtin> <class 'Exception'>
      self = <local> Dim{B}
Exception: Dim{B}: need placeholder, self.dimension or self.dyn_size for dim value

Process finished with exit code 1

rwth-i6/returnn#1333 (comment)