model.py 文件源码

def forward(self, inputs):
        batch_sz = inputs.size(0) # should be batch_sz (~200 in old set-up)
        inputs = torch.transpose(inputs,0,1)
        h0 = self.init_hidden_state(batch_sz)
        rnn_output, h_n = self.rnn.forward(inputs, h0)
        # get "output" after linear layer. 
        output = self.lin_out.forward(rnn_output.view(rnn_output.size(0)*rnn_output.size(1), rnn_output.size(2)))
        L, N = rnn_output.size(0), rnn_output.size(1)
        C = output.size(1)
        assert L*N == output.size(0), "ERROR: mismatch in output tensor dimensions"
        fin_out = output.view(L, N, C) 
        fin_out = torch.transpose(fin_out,0,1) 
        fin_out = fin_out.contiguous().view(N*L, C)
        return fin_out, rnn_output