Pytorch 錯誤：輸入應該是標量類型 Long 但發現是 Float

Question

我正在嘗試創建一個深度學習算法來玩蛇。 我正在嘗試使用 PyTorch 來實現這一點。 這是我的（凌亂的，稍后會修復）代碼的片段：

## DOUBLE Q DEEP LEARNING NETWORK
class SnakeNet(nn.Module):
    """mini cnn structure
  input -> (conv2d + relu) x 3 -> flatten -> (dense + relu) x 2 -> output
  """
    def __init__(self, input_dim, output_dim):
        super().__init__()

        self.online = nn.Sequential(
            # nn.Conv2d(in_channels=input_dim, out_channels=32, kernel_size=8, stride=4),
            # nn.ReLU(),
            # nn.Conv2d(in_channels=32, out_channels=64, kernel_size=4, stride=2),
            # nn.ReLU(),
            # nn.Conv2d(in_channels=64, out_channels=64, kernel_size=3, stride=1),
            # nn.ReLU(),
            # nn.Flatten(),
            # nn.Linear(3136, 512),
            # nn.ReLU(),
            # nn.Linear(512, output_dim),
            nn.Linear(input_dim, 200),
            nn.Linear(200, 20),
            nn.Linear(20, 50),
            nn.Linear(50, output_dim),
        )

        self.target = copy.deepcopy(self.online)

        # Q_target parameters are frozen.
        for p in self.target.parameters():
            p.requires_grad = False

    def forward(self, input, model):
        input = input.long()
        if model == "online":
            return self.online(input)
        elif model == "target":
            return self.target(input)

# EXPLOIT
        else:
            state = torch.tensor(state)
            state = state.unsqueeze(0)
            action_values = self.net(state, model="online")
            dir = torch.argmax(action_values, axis=1).item()

我在第 221 行收到一個錯誤： action_values = self.net(state, model="online")

聲明我的輸入（狀態）是一個 Float，雖然它是一個 tensorLong，我通過打印 type() 證明了這一點。 在建議添加state = state.type.tensorLong()這不起作用，主要是因為它已經很長了。

錯誤：

Traceback (most recent call last):
  File "snakeGame.py", line 324, in <module>
    prev_location, action = snake.act(current_state)
  File "snakeGame.py", line 222, in act
    action_values = self.net(state, model="online")
  File "/Users/gavinhartog/opt/anaconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "snakeGame.py", line 57, in forward
    return self.online(input)
  File "/Users/gavinhartog/opt/anaconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/Users/gavinhartog/opt/anaconda3/lib/python3.8/site-packages/torch/nn/modules/container.py", line 141, in forward
    input = module(input)
  File "/Users/gavinhartog/opt/anaconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/Users/gavinhartog/opt/anaconda3/lib/python3.8/site-packages/torch/nn/modules/linear.py", line 103, in forward
    return F.linear(input, self.weight, self.bias)
  File "/Users/gavinhartog/opt/anaconda3/lib/python3.8/site-packages/torch/nn/functional.py", line 1848, in linear
    return torch._C._nn.linear(input, weight, bias)
RuntimeError: expected scalar type Long but found Float

這是 state 的原始內容和形狀，在 torch.tensor 之前：

[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], etc, etc, etc

我嘗試了不同的東西，比如 Conv2d 和不同的損失函數，都是同樣的錯誤。 提前致謝。

Answer 1

錯誤有點混亂。 但我想你已經將state類型轉換為float而不是long

state = state.float()

因為nn.Linear總是需要浮點數。

Answer 2

stats=np.array([1,2,3,4,5,6])
print(type(stats))
stats=torch.tensor(stats).type(torch.LongTensor)
state = stats.unsqueeze(0)
print(type(stats))

你能用這個方法再重復一遍嗎？ 我不想發布答案，但我沒有足夠的聲譽發表評論