Created by: Akeepers

我参考paddle官网seq2seq例子 实现了一个seq2seq model

其中的encoder被改为了ernie ，decoder的代码保持不动，仅修改：

• layers.rnn中的initial_states为None：原始代码中的decoder 中的initial_states 为encoder最后一个cell的states，由于采用ernie作为encoder，所以将decoder中的 initial_states设为None

从API文档来看，rnn op的initial_states可以为None，但会报错

代码如下：

def decoder(encoder_output,
            encoder_output_proj,
            encoder_padding_mask,
            trg=None,
            is_train=True):
    """Decoder: GRU with Attention"""
    decoder_cell = DecoderCell(hidden_size=decoder_size)
    trg_embeder = lambda x: fluid.embedding(input=x,
                                            size=[target_dict_size, hidden_dim],
                                            dtype="float32",
                                            param_attr=fluid.ParamAttr(
                                                name="trg_emb_table"))
    output_layer = lambda x: layers.fc(x,
                                       size=target_dict_size,
                                       num_flatten_dims=len(x.shape) - 1,
                                       param_attr=fluid.ParamAttr(name=
                                                                  "output_w"))
    if is_train:
        decoder_output, _ = layers.rnn(
            cell=decoder_cell,
            inputs=trg_embeder(trg),
            initial_states=None,
            time_major=False,
            encoder_output=encoder_output,
            encoder_output_proj=encoder_output_proj,
            encoder_padding_mask=encoder_padding_mask)
        decoder_output = output_layer(decoder_output)
    else:
        encoder_output = layers.BeamSearchDecoder.tile_beam_merge_with_batch(
            encoder_output, beam_size)
        encoder_output_proj = layers.BeamSearchDecoder.tile_beam_merge_with_batch(
            encoder_output_proj, beam_size)
        encoder_padding_mask = layers.BeamSearchDecoder.tile_beam_merge_with_batch(
            encoder_padding_mask, beam_size)
        beam_search_decoder = layers.BeamSearchDecoder(
            cell=decoder_cell,
            start_token=bos_id,
            end_token=eos_id,
            beam_size=beam_size,
            embedding_fn=trg_embeder,
            output_fn=output_layer)
        decoder_output, _ = layers.dynamic_decode(
            decoder=beam_search_decoder,
            inits=None,
            max_step_num=max_length,
            output_time_major=False,
            encoder_output=encoder_output,
            encoder_output_proj=encoder_output_proj,
            encoder_padding_mask=encoder_padding_mask)

    return decoder_output

Error:

Traceback (most recent call last):
  File "run_seq2seq.py", line 136, in <module>
    main(args)
  File "run_seq2seq.py", line 128, in main
    train(args)
  File "run_seq2seq.py", line 61, in train
    logits = model_func(args, inputs, ernie_config, is_train=True)
  File "/home/yangpan/projects/paper_recurrence/PLMEE/ERNIE/ernie/finetune/seq2seq.py", line 208, in model_func
    is_train=is_train)
  File "/home/yangpan/projects/paper_recurrence/PLMEE/ERNIE/ernie/finetune/seq2seq.py", line 156, in decoder
    encoder_padding_mask=encoder_padding_mask)
  File "/home/yangpan/anaconda3/envs/paddle-py2.7/lib/python2.7/site-packages/paddle/fluid/layers/rnn.py", line 428, in rnn
    initial_states = cell.get_initial_states(batch_ref=inputs)
  File "/home/yangpan/anaconda3/envs/paddle-py2.7/lib/python2.7/site-packages/paddle/fluid/layers/rnn.py", line 116, in get_initial_states
    states_shapes = self.state_shape if shape is None else shape
  File "/home/yangpan/anaconda3/envs/paddle-py2.7/lib/python2.7/site-packages/paddle/fluid/layers/rnn.py", line 150, in state_shape
    raise NotImplementedError
NotImplementedError