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 proposals output (L x N x h_width) ==> (N x L x K)
        output = self.lin_out.forward(rnn_output.view(rnn_output.size(0)*rnn_output.size(1), rnn_output.size(2)))
        lin_out = output.view(rnn_output.size(0), rnn_output.size(1), output.size(1))
        final_out = self.nonlin_final(torch.transpose(lin_out,0,1))
        return final_out, rnn_output