TypeError when passing device

[rafvasq]

I'm not sure why this is happening. I've printed the type of device and find that it's of class torch.device. The relevant code is below (unchanged from Udacity's version aside from the print statement) and the error is below that. Could it be an issue with ML-Agents?

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
print(type(device))

class Agent():
    """Interacts with and learns from the environment."""

    def __init__(self, state_size, action_size, random_seed):
        """Initialize an Agent object.

        Params
        ======
            state_size (int): dimension of each state
            action_size (int): dimension of each action
            random_seed (int): random seed
        """
        self.state_size = state_size
        self.action_size = action_size
        self.seed = random.seed(random_seed)

        # Actor Network (w/ Target Network)
        self.actor_local = Actor(state_size, action_size, random_seed).to(device)
        self.actor_target = Actor(state_size, action_size, random_seed).to(device)
        self.actor_optimizer = optim.Adam(self.actor_local.parameters(), lr=LR_ACTOR)

Traceback (most recent call last):
  File "train.py", line 87, in <module>
    agent_1 = Agent(state_size=48, action_size=action_size, random_seed=0)
  File "C:\Users\Tester\ml-agents\ml-agents\mlagents\trainers\ddpg\ddpg_agent.py", line 39, in __init__
    self.actor_local = Actor(state_size, action_size, random_seed).to(device)
  File "C:\Users\Tester\ml-agents\ml-agents\mlagents\trainers\ddpg\model.py", line 29, in __init__
    self.fc3 = nn.Linear(fc2_units, action_size)
  File "C:\Users\Tester\AppData\Local\conda\conda\envs\ml-agents\lib\site-packages\torch\nn\modules\linear.py", line 51, in __init__
    self.weight = Parameter(torch.Tensor(out_features, in_features))
TypeError: new() received an invalid combination of arguments - got (google.protobuf.pyext._message.RepeatedScalarContainer, int), but expected one of:
 * (torch.device device)
 * (torch.Storage storage)
 * (Tensor other)
 * (tuple of ints size, torch.device device)
      didn't match because some of the arguments have invalid types: (e[31;1mgoogle.protobuf.pyext._message.RepeatedScalarContainere[0m, e[31;1minte[0m)
 * (object data, torch.device device)
      didn't match because some of the arguments have invalid types: (e[31;1mgoogle.protobuf.pyext._message.RepeatedScalarContainere[0m, e[31;1minte[0m)