My LSTM implementation is below

x_train is a size of torch.Size([129, 252, 4])

```
class LSTM(nn.Module):
def __init__(self,input_size ,hidden_size,num_layers,batch_size,bias):
super(LSTM, self).__init__()
self.input_size = input_size
self.hidden_size = hidden_size
self.num_layers = num_layers
self.bias = bias
self.batch_size = batch_size
self.lstm = nn.LSTM(input_size,hidden_size,num_layers,bias)
self.logsoftmax = torch.nn.LogSoftmax(dim=None)
def forward(self,input):
hidden = (torch.zeros(self.num_layers,self.batch_size,self.hidden_size),torch.zeros(self.num_layers,self.batch_size,self.hidden_size))
lstm_out,hidden = self.lstm(input,hidden)
y_pred = logsoftmax(lstm_out[-1,:,:])
return y_pred
```

when I enter that:

```
model = LSTM(4,2,1,252,bias = "True")
y_pred = model(x_train)
```

colab gives a type error:

```
stm() received an invalid combination of arguments - got (Tensor, tuple, list, str, int, float, bool, bool, bool), but expected one of:
* (Tensor data, Tensor batch_sizes, tuple of Tensors hx, tuple of Tensors params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional)
didn't match because some of the arguments have invalid types: (Tensor, !tuple!, !list!, !str!, !int!, !float!, !bool!, bool, bool)
* (Tensor input, tuple of Tensors hx, tuple of Tensors params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first)
didn't match because some of the arguments have invalid types: (Tensor, !tuple!, !list!, !str!, int, float, bool, bool, bool)
```

sorry for my grammatical mistakes and I am new in forum