model.py 文件源码

def __call__(self, X, return_last=False):
        batchsize = X.shape[0]
        seq_length = X.shape[1]
        enmbedding = self.embed(X)
        enmbedding = F.swapaxes(enmbedding, 1, 2)

        out_data = self._forward_layer(0, enmbedding)
        in_data = [out_data]

        for layer_index in range(1, self.num_layers):
            out_data = self._forward_layer(layer_index, F.concat(in_data) if self.densely_connected else in_data[-1])   # dense conv
            in_data.append(out_data)

        out_data = F.concat(in_data) if self.densely_connected else out_data    # dense conv

        if return_last:
            out_data = out_data[:, :, -1, None]

        if self.using_dropout:
            out_data = F.dropout(out_data, ratio=self.dropout)

        out_data = self.fc(out_data)
        out_data = F.reshape(F.swapaxes(out_data, 1, 2), (-1, self.vocab_size))

        return out_data