higgsfield/np-hard-deep-reinforcement-learning

RuntimeError: backward_input can only be called in training mode

MrLinNing opened this issue · 2 comments

In pointer network jupyter notebook,

/pytorch_test/env2/lib/python2.7/site-packages/ipykernel_launcher.py:46: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
Exception NameError: "global name 'FileNotFoundError' is not defined" in <bound method _DataLoaderIter.__del__ of <torch.utils.data.dataloader._DataLoaderIter object at 0x7fdc900d1cd0>> ignored
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-21-0299c228a1ba> in <module>()
     15 
     16         adam.zero_grad()
---> 17         loss.backward()
     18         adam.step()
     19 

/pytorch_test/env2/local/lib/python2.7/site-packages/torch/tensor.pyc in backward(self, gradient, retain_graph, create_graph)
     91                 products. Defaults to ``False``.
     92         """
---> 93         torch.autograd.backward(self, gradient, retain_graph, create_graph)
     94 
     95     def register_hook(self, hook):

/pytorch_test/env2/local/lib/python2.7/site-packages/torch/autograd/__init__.pyc in backward(tensors, grad_tensors, retain_graph, create_graph, grad_variables)
     87     Variable._execution_engine.run_backward(
     88         tensors, grad_tensors, retain_graph, create_graph,
---> 89         allow_unreachable=True)  # allow_unreachable flag
     90 
     91 

RuntimeError: backward_input can only be called in training mode

In neural combinatorial optimization jupyter notebook


TypeError                                 Traceback (most recent call last)
<ipython-input-16-bbf1d00a3be2> in <module>()
----> 1 tsp_20_train.train_and_validate(5)

<ipython-input-14-db3174b84dcf> in train_and_validate(self, n_epochs)
     30                 inputs = inputs.cuda()
     31 
---> 32                 R, probs, actions, actions_idxs = self.model(inputs)
     33 
     34                 if batch_id == 0:

/pytorch_test/env2/local/lib/python2.7/site-packages/torch/nn/modules/module.pyc in __call__(self, *input, **kwargs)
    489             result = self._slow_forward(*input, **kwargs)
    490         else:
--> 491             result = self.forward(*input, **kwargs)
    492         for hook in self._forward_hooks.values():
    493             hook_result = hook(self, input, result)

<ipython-input-10-a637634e5730> in forward(self, inputs)
     34         seq_len    = inputs.size(2)
     35 
---> 36         probs, action_idxs = self.actor(inputs)
     37 
     38         actions = []

/pytorch_test/env2/local/lib/python2.7/site-packages/torch/nn/modules/module.pyc in __call__(self, *input, **kwargs)
    489             result = self._slow_forward(*input, **kwargs)
    490         else:
--> 491             result = self.forward(*input, **kwargs)
    492         for hook in self._forward_hooks.values():
    493             hook_result = hook(self, input, result)

<ipython-input-9-816b31f44515> in forward(self, inputs)
     76 
     77 
---> 78             idxs = probs.multinomial().squeeze(1)
     79             for old_idxs in prev_idxs:
     80                 if old_idxs.eq(idxs).data.any():

TypeError: multinomial() missing 1 required positional arguments: "num_samples"




In pointer network jupyter notebook,

/pytorch_test/env2/lib/python2.7/site-packages/ipykernel_launcher.py:46: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
Exception NameError: "global name 'FileNotFoundError' is not defined" in <bound method _DataLoaderIter.__del__ of <torch.utils.data.dataloader._DataLoaderIter object at 0x7fdc900d1cd0>> ignored
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-21-0299c228a1ba> in <module>()
     15 
     16         adam.zero_grad()
---> 17         loss.backward()
     18         adam.step()
     19 

/pytorch_test/env2/local/lib/python2.7/site-packages/torch/tensor.pyc in backward(self, gradient, retain_graph, create_graph)
     91                 products. Defaults to ``False``.
     92         """
---> 93         torch.autograd.backward(self, gradient, retain_graph, create_graph)
     94 
     95     def register_hook(self, hook):

/pytorch_test/env2/local/lib/python2.7/site-packages/torch/autograd/__init__.pyc in backward(tensors, grad_tensors, retain_graph, create_graph, grad_variables)
     87     Variable._execution_engine.run_backward(
     88         tensors, grad_tensors, retain_graph, create_graph,
---> 89         allow_unreachable=True)  # allow_unreachable flag
     90 
     91 

RuntimeError: backward_input can only be called in training mode

You can add pointer.train() after for batch_id, sample_batch in enumerate(train_loader):, this action will remove the error.