I’m runing this piece of code:
    def forward(self, inputs, core_state=()):
        x = inputs["frame"]
        # time x batch x 64 x 64 x 3
        T, B, *_ = x.shape

        # merge time and batch
        # [T*B x 64 x 64 x 3]
        x = torch.flatten(x, 0, 1)

        x = x.float()

        # [T*B x 3 x 64 x 64]
        x = x.transpose(1, 3)

        # x = checkpoint_sequential(self.feat_extract, 2, x)
        x = self.feat_extract(x)
        x = x.view(T*B, -1)

        # core_input = checkpoint_sequential(self.fc, 2, x)
        core_input = self.fc(x)

        core_output = core_input
        core_state = tuple()

        policy_logits = self.policy(core_output)
        baseline = self.baseline(core_output)
        if self.training:
            action = torch.multinomial(F.softmax(policy_logits, dim=1), num_samples=1)
        else:
            action = torch.argmax(policy_logits, dim=1)

        policy_logits = policy_logits.view(T, B, self.num_actions)
        baseline = baseline.view(T, B)
        action = action.view(T, B)

        return dict(policy_logits=policy_logits, baseline=baseline,
                    action=action), core_state

And got this error:

Traceback (most recent call last):
File "/usr/local/easybuild-2019/easybuild/software/compiler/gcccore/8.3.0/python/3.7.4/lib/python3$
self.run()
File "/usr/local/easybuild-2019/easybuild/software/compiler/gcccore/8.3.0/python/3.7.4/lib/python3$
self._target(*self._args, **self._kwargs)
File “/data/gpfs/projects/punim1126/CL-RIDE-master-project/src/utils.py”, line 335, in act
raise e
File “/data/gpfs/projects/punim1126/CL-RIDE-master-project/src/utils.py”, line 287, in act
agent_output, agent_state = model(env_output, agent_state)
File “/home/shizhec/.local/lib/python3.7/site-packages/torch/nn/modules/module.py”, line 722, in _$
result = self.forward(*input, **kwargs)
File “/data/gpfs/projects/punim1126/CL-RIDE-master-project/src/models.py”, line 675, in forward
action = torch.multinomial(F.softmax(policy_logits, dim=1), num_samples=1)
RuntimeError: probability tensor contains either inf, nan or element < 0

I’m using torch 1.6.0, however, when I use torch 1.1.0, I don’t get any error anymore, and I could train the model correctly. Anyone know why this is happening?