pytrochを使い始めたのですが　モデルを動かすとき謎のエラーが出ます

エラーがなぜ起こっているのか全く分かりません
わかる方教えてください

試したこと
printしてみましたが原因は不明

バージョンは１．１５だったはず

class Actor:
    def get_action(self, state, episode, targetQN):  # [C]ｔ＋１での行動を返す
        # 徐々に最適行動のみをとる、ε-greedy法
        epsilon = 0.001 + 0.9 / (1.0 + episode)

        if epsilon <= np.random.uniform(0, 1):
            retTargetQs = targetQN.forward(state)[0]
            action = np.argmax(retTargetQs)  # 最大の報酬を返す行動を選択する

        else:
            action = np.random.choice([0, 1])  # ランダムに行動する

        return action

device = 'cuda' if torch.cuda.is_available() else 'cpu'
mainQN = Network().to(device)
optimizer = optim.Adam(mainQN.parameters(), lr=learning_rate)
criterion = nn.MSELoss()

略

    def forward(self,x,device=device):
        x=torch.from_numpy(x).to(device)
        print(x)
        out = self.dence(x)
         
        return out

出ているエラー

tensor([[ 0.0463,  0.1505,  0.0006, -0.2480]], device='cuda:0',
       dtype=torch.float64)
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-32-24866278c093> in <module>
    182             print(state[0, 0])  # カートのx位置を出力するならコメントはずす
    183 
--> 184         action = actor.get_action(state, episode, mainQN)
    185         next_state, reward, done, info = env.step(action)
    186         next_state = np.reshape(next_state, [1, 4])

<ipython-input-32-24866278c093> in get_action(self, state, episode, targetQN)
    128 
    129         if epsilon <= np.random.uniform(0, 1):
--> 130             retTargetQs = targetQN.forward(state)[0]
    131             action = np.argmax(retTargetQs)  # 最大の報酬を返す行動を選択する
    132 

<ipython-input-32-24866278c093> in forward(self, x, device)
     45         x=torch.from_numpy(x).to(device)
     46         print(x)
---> 47         out = self.dence(x)
     48 
     49         return out

~\Anaconda3\envs\pyflan\lib\site-packages\torch\nn\modules\module.py in __call__(self, *input, **kwargs)
    548             result = self._slow_forward(*input, **kwargs)
    549         else:
--> 550             result = self.forward(*input, **kwargs)
    551         for hook in self._forward_hooks.values():
    552             hook_result = hook(self, input, result)

~\Anaconda3\envs\pyflan\lib\site-packages\torch\nn\modules\container.py in forward(self, input)
     98     def forward(self, input):
     99         for module in self:
--> 100             input = module(input)
    101         return input
    102 

~\Anaconda3\envs\pyflan\lib\site-packages\torch\nn\modules\module.py in __call__(self, *input, **kwargs)
    548             result = self._slow_forward(*input, **kwargs)
    549         else:
--> 550             result = self.forward(*input, **kwargs)
    551         for hook in self._forward_hooks.values():
    552             hook_result = hook(self, input, result)

~\Anaconda3\envs\pyflan\lib\site-packages\torch\nn\modules\linear.py in forward(self, input)
     85 
     86     def forward(self, input):
---> 87         return F.linear(input, self.weight, self.bias)
     88 
     89     def extra_repr(self):

~\Anaconda3\envs\pyflan\lib\site-packages\torch\nn\functional.py in linear(input, weight, bias)
   1608     if input.dim() == 2 and bias is not None:
   1609         # fused op is marginally faster
-> 1610         ret = torch.addmm(bias, input, weight.t())
   1611     else:
   1612         output = input.matmul(weight.t())

RuntimeError: Expected object of scalar type Float but got scalar type Double for argument #2 'mat1' in call to _th_addmm