PyTorch TypeError:forward()接受1个位置参数,但给出了2个

2024-03-28 16:48:57 发布

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我不明白这个错误是从哪里来的,模型的参数数量似乎是正确的,下面是我的模型:

class MancalaModel(nn.Module):

    def __init__(self, n_inputs=16, n_outputs=16):
        super().__init__()

        n_neurons = 256

        def create_block(n_in, n_out):
            block = nn.ModuleList()
            block.append(nn.Linear(n_in, n_out))
            block.append(nn.ReLU())
            return block

        self.blocks = nn.ModuleList()
        self.blocks.append(create_block(n_inputs, n_neurons))
        for _ in range(6):
            self.blocks.append(create_block(n_neurons, n_neurons))

        self.actor_block = nn.ModuleList()
        self.critic_block = nn.ModuleList()
        for _ in range(2):
            self.actor_block.append(create_block(n_neurons, n_neurons))
            self.critic_block.append(create_block(n_neurons, n_neurons))

        self.actor_block.append(create_block(n_neurons, n_outputs))
        self.critic_block.append(create_block(n_neurons, 1))

        self.apply(init_weights)

    def forward(self, x):
        x = self.blocks(x)
        actor = F.softmax(self.actor_block(x))
        critics = self.critic_block(x)
        return actor, critics

然后我创建一个实例,用随机数向前传递

model = MancalaModel()
x = model(torch.rand(1, 16))

然后我得到了TypeError,说参数的数量不正确:

      2 model = MancalaModel()
----> 3 x = model(torch.rand(1, 16))
      4 # summary(model, (16,), device='cpu')
      5 

d:\environments\python\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
    725             result = self._slow_forward(*input, **kwargs)
    726         else:
--> 727             result = self.forward(*input, **kwargs)
    728         for hook in itertools.chain(
    729                 _global_forward_hooks.values(),

D:\UOM\Year3\AI & Games\KalahPlayer\agents\model_agent.py in forward(self, x)
     54 
     55     def forward(self, x):
---> 56         x = self.blocks(x)
     57         actor = F.softmax(self.actor_block(x))
     58         critics = self.critic_block(x)

d:\environments\python\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
    725             result = self._slow_forward(*input, **kwargs)
    726         else:
--> 727             result = self.forward(*input, **kwargs)
    728         for hook in itertools.chain(
    729                 _global_forward_hooks.values(),

TypeError: forward() takes 1 positional argument but 2 were given

感谢您的帮助,谢谢


Tags: inselfinputmodeldefcreatennblock
1条回答
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1楼 · 发布于 2024-03-28 16:48:57

TL;DR
您正试图通过^{}执行forward-这未定义。 您需要将self.blocks转换为^{}

        def create_block(n_in, n_out):
            # do not work with ModuleList here either.
            block = nn.Sequential(
              nn.Linear(n_in, n_out),
              nn.ReLU()
            )
            return block

        blocks = []  # simple list - not a member of self, for temporal use only.
        blocks.append(create_block(n_inputs, n_neurons))
        for _ in range(6):
            blocks.append(create_block(n_neurons, n_neurons))
        self.blocks = nn.Sequential(*blocks)  # convert the simple list to nn.Sequential

我希望您得到NotImplementedError,而不是这个TypeError,因为您的self.blocksnn.ModuleList类型,其forward方法抛出NotImplementedError。我刚刚做了一个pull request来解决这个令人困惑的问题。
更新(2021年4月22日):PRwas merged。在未来的版本中,当调用nn.ModuleListnn.ModuleDict时,您应该看到NotImplementedError

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