---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-73-c3dd6f60d80f> in <module>
     23
     24 # Evaluate untrained policy
---> 25 evaluations= [evaluate_policy(local_env, policy)]
     26
     27 total_timesteps = 0

/duckietown/utils/helpers.py in evaluate_policy(env, policy, eval_episodes, max_timesteps)
    216         step = 0
    217         while not done and step < max_timesteps:
--> 218             action = policy.predict(np.array(obs))
    219             obs, reward, done, _ = env.step(action)
    220             avg_reward += reward

<ipython-input-70-08969eb656c1> in predict(self, state)
     24         state = torch.FloatTensor(np.expand_dims(state, axis=0)).to(device)
     25         print(state)
---> 26         return self.actor(state).cpu().data.numpy().flatten() # Make back into column?
     27
     28     def train(self, replay_buffer, iterations, batch_size=64, discount=0.99):

/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
    487             result = self._slow_forward(*input, **kwargs)
    488         else:
--> 489             result = self.forward(*input, **kwargs)
    490         for hook in self._forward_hooks.values():
    491             hook_result = hook(self, input, result)

<ipython-input-61-a7209547df79> in forward(self, x)
     34         x = x.view(x.size(0), -1)  # flatten, does not modify size
     35         x = self.dropout(x)  # Make some elements zero (regularlization), does not modify size.
---> 36         x = self.relu(self.lin1(x)) # Therefore this must accept 32. BUG self.lr changes to self.relu
     37
     38         x = self.lin2(x)

/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
    487             result = self._slow_forward(*input, **kwargs)
    488         else:
--> 489             result = self.forward(*input, **kwargs)
    490         for hook in self._forward_hooks.values():
    491             hook_result = hook(self, input, result)

/usr/local/lib/python3.6/dist-packages/torch/nn/modules/linear.py in forward(self, input)
     65     @weak_script_method
     66     def forward(self, input):
---> 67         return F.linear(input, self.weight, self.bias)
     68
     69     def extra_repr(self):

/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py in linear(input, weight, bias)
   1350     if input.dim() == 2 and bias is not None:
   1351         # fused op is marginally faster
-> 1352         ret = torch.addmm(torch.jit._unwrap_optional(bias), input, weight.t())
   1353     else:
   1354         output = input.matmul(weight.t())

RuntimeError: size mismatch, m1: [1 x 31968], m2: [32 x 100] at /pytorch/aten/src/TH/generic/THTensorMath.cpp:940