hello, I use the https://github.com/quark0/darts/tree/master/rnn and simplify the train/test/valid data to get a rnn model, I could get the saved pt files then, but always failed to save it to onnx with error like:
ValueError: NestedIOFunction doesn’t know how to process an input object of type torch.LongTensor
What code are you using to save the model to ONNX? I couldn’t find a reference to ONNX in the git you shared.
model_pt_path = "test_1.onnx"
data_1 = torch.randn(23, 64)
hidden_1 = torch.randn(1, 64, 850)
output = torch.onnx.export(model, (data_1, hidden_1), model_onnx_path, verbose=True)
I added code above to try to export the model, thanks a lot!
I’ve just read the project requirements, you probably use PyTorch version 0.3.1 as recommended? Then I think this answer might be relevant.
Try to wrap your tensors data_1 and hidden_1 in torch.Variable() calls, maybe that will work.
PyTorch versions prior to 0.4.0 used Variable to indicate that a Tensor can be “backwarded” upon, whereas normal Tensors cannot.
Alex, thanks a lot!
I modified the code as belew, although the original error gone, but will get a new error:
data_1 = torch.randn(23, 64)
hidden_1 = torch.randn(1, 64, 850)
variable_data_1 = Variable(data_1)
variable_hidden_1 = Variable(hidden_1)
output = torch.onnx.export(model, (variable_data_1, variable_hidden_1), model_onnx_path, verbose=True)
Traceback (most recent call last):
File "/Applications/PyCharm CE.app/Contents/helpers/pydev/pydev_run_in_console.py", line 52, in run_file
pydev_imports.execfile(file, globals, locals) # execute the script
File "/Applications/PyCharm CE.app/Contents/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "/Users/fjbnu/Downloads/darts/rnn/search-EXP-20190515-233237/scripts/train.py", line 145, in <module>
output = torch.onnx.export(model, (variable_data_1, variable_hidden_1), model_onnx_path, verbose=True)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/onnx/__init__.py", line 75, in export
_export(model, args, f, export_params, verbose, training)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/onnx/__init__.py", line 116, in _export
trace, torch_out = torch.jit.trace(model, args)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/jit/__init__.py", line 241, in trace
return TracedModule(f, nderivs=nderivs)(*args, **kwargs)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/nn/modules/module.py", line 357, in __call__
result = self.forward(*input, **kwargs)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/jit/__init__.py", line 268, in forward
trace, (out_vars, out_struct) = traced_inner(in_vars, in_struct)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/jit/__init__.py", line 287, in wrapper
out_vars, out_struct = f(in_vars, in_struct)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/jit/__init__.py", line 262, in traced_inner
return _flatten(self.inner(*args, **kwargs))
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/nn/modules/module.py", line 355, in __call__
result = self._slow_forward(*input, **kwargs)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/nn/modules/module.py", line 345, in _slow_forward
result = self.forward(*input, **kwargs)
File "/Users/fjbnu/Downloads/darts/rnn/search-EXP-20190515-233237/scripts/model.py", line 131, in forward
emb = embedded_dropout(self.encoder, input, dropout=self.dropoute if self.training else 0)
File "/Users/fjbnu/Downloads/darts/rnn/search-EXP-20190515-233237/scripts/utils.py", line 69, in embedded_dropout
embed.scale_grad_by_freq, embed.sparse
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/nn/_functions/thnn/sparse.py", line 59, in forward
output = torch.index_select(weight, 0, indices.view(-1))
TypeError: torch.index_select received an invalid combination of arguments - got (torch.FloatTensor, int, !torch.FloatTensor!), but expected (torch.FloatTensor source, int dim, torch.LongTensor index)
so modified to
data_1 = torch.randn(23, 64).long()
hidden_1 = torch.randn(1, 64, 850).long()
variable_data_1 = Variable(data_1)
variable_hidden_1 = Variable(hidden_1)
output = torch.onnx.export(model, (variable_data_1, variable_hidden_1), model_onnx_path, verbose=True)
will get error:
Traceback (most recent call last):
File "/Users/fjbnu/Downloads/darts/rnn/search-EXP-20190515-233237/scripts/train.py", line 288, in <module>
train()
File "/Users/fjbnu/Downloads/darts/rnn/search-EXP-20190515-233237/scripts/train.py", line 225, in train
output = torch.onnx.export(model, (variable_data_1, variable_hidden_1), model_onnx_path, verbose=True)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/onnx/__init__.py", line 75, in export
_export(model, args, f, export_params, verbose, training)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/onnx/__init__.py", line 116, in _export
trace, torch_out = torch.jit.trace(model, args)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/jit/__init__.py", line 241, in trace
return TracedModule(f, nderivs=nderivs)(*args, **kwargs)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/nn/modules/module.py", line 357, in __call__
result = self.forward(*input, **kwargs)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/jit/__init__.py", line 268, in forward
trace, (out_vars, out_struct) = traced_inner(in_vars, in_struct)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/jit/__init__.py", line 287, in wrapper
out_vars, out_struct = f(in_vars, in_struct)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/jit/__init__.py", line 262, in traced_inner
return _flatten(self.inner(*args, **kwargs))
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/nn/modules/module.py", line 355, in __call__
result = self._slow_forward(*input, **kwargs)
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/nn/modules/module.py", line 345, in _slow_forward
result = self.forward(*input, **kwargs)
File "/Users/fjbnu/Downloads/darts/rnn/search-EXP-20190515-233237/scripts/model.py", line 131, in forward
emb = embedded_dropout(self.encoder, input, dropout=self.dropoute if self.training else 0)
File "/Users/fjbnu/Downloads/darts/rnn/search-EXP-20190515-233237/scripts/utils.py", line 69, in embedded_dropout
embed.scale_grad_by_freq, embed.sparse
File "/Users/fjbnu/anaconda2/envs/darts/lib/python3.6/site-packages/torch/nn/_functions/thnn/sparse.py", line 59, in forward
output = torch.index_select(weight, 0, indices.view(-1))
RuntimeError: index out of range at /Users/soumith/minicondabuild3/conda-bld/pytorch_1518385717421/work/torch/lib/TH/generic/THTensorMath.c:277
Also I found that seems PyTorch 0.3.1 does not support rnn model export to onnx very well as https://github.com/pytorch/pytorch/issues/5234
So I used the PyTorch 0.4.1/1.1.0 to have a try, but will get errors :
Traceback (most recent call last):
File "/Applications/PyCharm CE.app/Contents/helpers/pydev/pydev_run_in_console.py", line 52, in run_file
pydev_imports.execfile(file, globals, locals) # execute the script
File "/Applications/PyCharm CE.app/Contents/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "/Users/fjbnu/Downloads/darts/rnn/search-EXP-20190515-233237/scripts/train.py", line 145, in <module>
output = torch.onnx.export(model, (variable_data_1, variable_hidden_1), model_onnx_path, verbose=True)
File "/Users/fjbnu/anaconda2/envs/darts_0.4/lib/python3.6/site-packages/torch/onnx/__init__.py", line 26, in export
return utils.export(*args, **kwargs)
File "/Users/fjbnu/anaconda2/envs/darts_0.4/lib/python3.6/site-packages/torch/onnx/utils.py", line 94, in export
operator_export_type=operator_export_type)
File "/Users/fjbnu/anaconda2/envs/darts_0.4/lib/python3.6/site-packages/torch/onnx/utils.py", line 226, in _export
example_outputs, propagate)
File "/Users/fjbnu/anaconda2/envs/darts_0.4/lib/python3.6/site-packages/torch/onnx/utils.py", line 177, in _model_to_graph
graph, torch_out = _trace_and_get_graph_from_model(model, args, training)
File "/Users/fjbnu/anaconda2/envs/darts_0.4/lib/python3.6/site-packages/torch/onnx/utils.py", line 144, in _trace_and_get_graph_from_model
trace, torch_out = torch.jit.get_trace_graph(model, args)
File "/Users/fjbnu/anaconda2/envs/darts_0.4/lib/python3.6/site-packages/torch/jit/__init__.py", line 77, in get_trace_graph
return LegacyTracedModule(f)(*args, **kwargs)
File "/Users/fjbnu/anaconda2/envs/darts_0.4/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in __call__
result = self.forward(*input, **kwargs)
File "/Users/fjbnu/anaconda2/envs/darts_0.4/lib/python3.6/site-packages/torch/jit/__init__.py", line 109, in forward
out = self.inner(*trace_inputs)
File "/Users/fjbnu/anaconda2/envs/darts_0.4/lib/python3.6/site-packages/torch/nn/modules/module.py", line 475, in __call__
result = self._slow_forward(*input, **kwargs)
File "/Users/fjbnu/anaconda2/envs/darts_0.4/lib/python3.6/site-packages/torch/nn/modules/module.py", line 465, in _slow_forward
result = self.forward(*input, **kwargs)
File "/Users/fjbnu/Downloads/darts/rnn/search-EXP-20190515-233237/scripts/model.py", line 131, in forward
emb = embedded_dropout(self.encoder, input, dropout=self.dropoute if self.training else 0)
File "/Users/fjbnu/Downloads/darts/rnn/search-EXP-20190515-233237/scripts/utils.py", line 67, in embedded_dropout
X = embed._backend.Embedding.apply(words, masked_embed_weight,
File "/Users/fjbnu/anaconda2/envs/darts_0.4/lib/python3.6/site-packages/torch/nn/backends/backend.py", line 10, in __getattr__
raise NotImplementedError
NotImplementedError
The last error with PyTorch 0.4.1 / 1.1.0 is already clearer than the previous ones. Making progress!
This seems like some module in PyTorch isn’t supported by ONNX yet, maybe… The second last line (X = embed._backend...) in your stacktrace appears to call the backend’s Embedding module, and I have no idea what that could be and how to debug it.
I’m afraid that’s as far as I can help you 
Maybe someone else had a similar problem and can comment here?