Traceback (most recent call last):


 "tools/pytorch2onnx.py", line 163, in <module>

verify=args.verify)


 "tools/pytorch2onnx.py", line 74, in pytorch2onnx

opset_version=opset_version)


 "/usr/local/lib/python3.6/dist-packages/torch/onnx/__init__.py", line 168, in export

custom_opsets, enable_onnx_checker, use_external_data_format)


 "/usr/local/lib/python3.6/dist-packages/torch/onnx/utils.py", line 69, in export

use_external_data_format=use_external_data_format)


 "/usr/local/lib/python3.6/dist-packages/torch/onnx/utils.py", line 488, in _export

fixed_batch_size=fixed_batch_size)


 "/usr/local/lib/python3.6/dist-packages/torch/onnx/utils.py", line 334, in _model_to_graph

graph, torch_out = _trace_and_get_graph_from_model(model, args, training)


 "/usr/local/lib/python3.6/dist-packages/torch/onnx/utils.py", line 291, in _trace_and_get_graph_from_model

torch.jit._get_trace_graph(model, args, _force_outplace=False, _return_inputs_states=True)


 "/usr/local/lib/python3.6/dist-packages/torch/jit/__init__.py", line 278, in _get_trace_graph

outs = ONNXTracedModule(f, _force_outplace, return_inputs, _return_inputs_states)(*args, **kwargs)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 550, in __call__

result = self.forward(*input, **kwargs)


 "/usr/local/lib/python3.6/dist-packages/torch/jit/__init__.py", line 361, in forward

self._force_outplace,


 "/usr/local/lib/python3.6/dist-packages/torch/jit/__init__.py", line 348, in wrapper

outs.append(self.inner(*trace_inputs))


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 548, in __call__

result = self._slow_forward(*input, **kwargs)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 534, in _slow_forward

result = self.forward(*input, **kwargs)


 "/content/mmaction2/mmaction/models/recognizers/recognizer2d.py", line 93, in forward_dummy

x = self.extract_feat(imgs)


 "/usr/local/lib/python3.6/dist-packages/mmcv/runner/fp16_utils.py", line 84, in new_func

return old_func(*args, **kwargs)


 "/content/mmaction2/mmaction/models/recognizers/base.py", line 72, in extract_feat

x = self.backbone(imgs)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 548, in __call__

result = self._slow_forward(*input, **kwargs)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 534, in _slow_forward

result = self.forward(*input, **kwargs)


 "/content/mmaction2/mmaction/models/backbones/resnet.py", line 541, in forward

x = res_layer(x)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 548, in __call__

result = self._slow_forward(*input, **kwargs)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 534, in _slow_forward

result = self.forward(*input, **kwargs)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/container.py", line 100, in forward

input = module(input)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 548, in __call__

result = self._slow_forward(*input, **kwargs)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 534, in _slow_forward

result = self.forward(*input, **kwargs)


 "/content/mmaction2/mmaction/models/backbones/resnet.py", line 214, in forward

out = _inner_forward(x)


 "/content/mmaction2/mmaction/models/backbones/resnet.py", line 200, in _inner_forward

out = self.conv1(x)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 548, in __call__

result = self._slow_forward(*input, **kwargs)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 534, in _slow_forward

result = self.forward(*input, **kwargs)


 "/usr/local/lib/python3.6/dist-packages/mmcv/cnn/bricks/conv_module.py", line 192, in forward

x = self.conv(x)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 548, in __call__

result = self._slow_forward(*input, **kwargs)


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 534, in _slow_forward

result = self.forward(*input, **kwargs)


 "/content/mmaction2/mmaction/models/backbones/resnet_tsm.py", line 68, in forward

x = self.shift(x, self.num_segments, shift_div=self.shift_div)


 "/content/mmaction2/mmaction/models/backbones/resnet_tsm.py", line 88, in shift

x = x.view(-1, num_segments, c, h * w)
RuntimeError: shape '[-1, 8, 64, 5440]' is invalid for input of size 348160


Traceback (most recent call last):

 "/home/protik/anaconda3/lib/python3.6/site-packages/conda/common/io.py", line 399, in backdown_thread_pool
yield ThreadPoolExecutor(max_workers)

 "/home/protik/anaconda3/lib/python3.6/site-packages/conda/core/index.py", line 214, in get_reduced_index
new_records = query_all(spec)

 "/home/protik/anaconda3/lib/python3.6/site-packages/conda/core/index.py", line 187, in query_all
return tuple(concat(future.result() for future in as_completed(futures)))

 "/home/protik/anaconda3/lib/python3.6/site-packages/conda/core/index.py", line 187, in <genexpr>
return tuple(concat(future.result() for future in as_completed(futures)))

 "/home/protik/anaconda3/lib/python3.6/concurrent/futures/_base.py", line 217, in as_completed
fs = set(fs)

 "/home/protik/anaconda3/lib/python3.6/site-packages/conda/core/index.py", line 186, in <genexpr>
futures = (executor.submit(sd.query, spec) for sd in subdir_datas)

 "/home/protik/anaconda3/lib/python3.6/concurrent/futures/thread.py", line 123, in submit
self._adjust_thread_count()

 "/home/protik/anaconda3/lib/python3.6/concurrent/futures/thread.py", line 142, in _adjust_thread_count
t.start()

 "/home/protik/anaconda3/lib/python3.6/threading.py", line 846, in start
_start_new_thread(self._bootstrap, ())
RuntimeError: can't start new thread