Here is my neural network code, using pytorch:

 class BLSTM(nn.Module):   
     def __init__(self,vocab_size):    
           super(BLSTM,self).__init__()    
           self.Embeddings = nn.Embedding(vocab_size,100)     
           self.LSTM = nn.LSTM(100,128,bidirectional=True)     
           self.fc = nn.Linear(128*2,3)     
           self.dropout = nn.Dropout(0.5)     
           self.tanh = nn.Tanh()     

    def forward(self,X):     
          embed = self.Embeddings(X)     
          print(embed)     
          output , (hidden , cell) = self.LSTM(embed)     
          last_hidden = output[:, -1,:]     
          logits = self.fc(self.dropout(last_hidden))     
          self.tanh(logits)     
          return logits

I am getting cuda assertion error at model.to(“device”). Is there any problem with the dimensions specified or the network. I have checked with the memory allocation it’s fine I will post the error below

Cell In[52], line 10
      7 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
      8 print(device)
---> 10 model.to(device)
     11 X_train = np.squeeze(torch.tensor(X_train,dtype=torch.long))
     12 X_val = np.squeeze(torch.tensor(X_val,dtype=torch.long))

File C:Python312Libsite-packagestorchnnmodulesmodule.py:1340, in Module.to(self, *args, **kwargs)
...
RuntimeError: CUDA error: device-side assert triggered
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.

Can anyone explain the real cause of this one?

I have to train the model with the given network but while allocating the model to gpu I have been facing this error. I can’t figure out. Otherwise they have been showing me error with tensors. The dimension of the tensors is 1.