Traceback (most recent call last):


 "main.py", line 238, in <module>

acc_tmp = val(test_dataset, criterion)


 "main.py", line 157, in val

preds0, preds1 = MORAN(image, length, text, text_rev, test=True)


 "/home/superpc/miniconda2/envs/pytorch-0.3-py2.7-OCR/lib/python2.7/site-packages/torch/nn/modules/module.py", line 357, in __call__

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


 "/home/superpc/miniconda2/envs/pytorch-0.3-py2.7-OCR/lib/python2.7/site-packages/torch/nn/parallel/data_parallel.py", line 73, in forward

outputs = self.parallel_apply(replicas, inputs, kwargs)


 "/home/superpc/miniconda2/envs/pytorch-0.3-py2.7-OCR/lib/python2.7/site-packages/torch/nn/parallel/data_parallel.py", line 83, in parallel_apply

return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])


 "/home/superpc/miniconda2/envs/pytorch-0.3-py2.7-OCR/lib/python2.7/site-packages/torch/nn/parallel/parallel_apply.py", line 67, in parallel_apply

raise output
RuntimeError: tensors are on different GPUs

Traceback (most recent call last):


 "tools/train.py", line 159, in <module>

main()


 "tools/train.py", line 155, in main

meta=meta)


 "/home/ceyang/mmdetection/mmdet/apis/train.py", line 165, in train_detector

runner.run(data_loaders, cfg.workflow, cfg.total_epochs)


 "/home/ceyang/.conda/envs/dt2/lib/python3.7/site-packages/mmcv-0.5.1-py3.7-linux-x86_64.egg/mmcv/runner/runner.py", line 383, in run

epoch_runner(data_loaders[i], **kwargs)


 "/home/ceyang/.conda/envs/dt2/lib/python3.7/site-packages/mmcv-0.5.1-py3.7-linux-x86_64.egg/mmcv/runner/runner.py", line 289, in train

self.call_hook('after_train_iter')


 "/home/ceyang/.conda/envs/dt2/lib/python3.7/site-packages/mmcv-0.5.1-py3.7-linux-x86_64.egg/mmcv/runner/runner.py", line 245, in call_hook

getattr(hook, fn_name)(self)


 "/home/ceyang/.conda/envs/dt2/lib/python3.7/site-packages/mmcv-0.5.1-py3.7-linux-x86_64.egg/mmcv/runner/hooks/optimizer.py", line 21, in after_train_iter

runner.outputs['loss'].backward()


 "/home/ceyang/.conda/envs/dt2/lib/python3.7/site-packages/torch/tensor.py", line 198, in backward

torch.autograd.backward(self, gradient, retain_graph, create_graph)


 "/home/ceyang/.conda/envs/dt2/lib/python3.7/site-packages/torch/autograd/__init__.py", line 100, in backward

allow_unreachable=True)
# allow_unreachable flag
RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.
