def forward(self, x):
hidden_inputs = self.hidden(x)
hidden_outputs = self.sigmoid(hidden_inputs)
final_inputs = self.output(hidden_outputs)
final_outputs = self.softmax(final_inputs)
return final_outputs
torch.isnan(self.features).any() # false
label_predict = self.forward(self.features)
torch.isnan(label_predict).any() # true
I checked, and it’s the nn.linear causing the output to be nan. Why is that and how can I fix that?