fabb8b5bafea7151b48d9dbbeefaeae87b312c34,tools/extract_embeddings.py,,main,#,30

Before Change

                                 feat_padding_idx,
                                 len(tgt_dict),
                                 for_encoder=False)
    decoder = make_decoder(model_opt.decoder_type,
                           model_opt.rnn_type,
                           model_opt.brnn,
                           model_opt.dec_layers,
                           model_opt.rnn_size,
                           model_opt.input_feed,
                           model_opt.global_attention,
                           model_opt.coverage_attn,
                           model_opt.context_gate,
                           model_opt.copy_attn,
                           model_opt.cnn_kernel_width,
                           model_opt.dropout,
                           embeddings)

    encoder_embeddings = encoder.word_lut.weight.data.tolist()
    decoder_embeddings = decoder.word_lut.weight.data.tolist()

After Change

    if opt.cuda:
        torch.cuda.set_device(opt.gpu)

    model_opt = checkpoint["opt"]
    src_dict = checkpoint["dicts"]["src"]
    tgt_dict = checkpoint["dicts"]["tgt"]
    feat_padding_idx = []

    embeddings = make_embeddings(model_opt,
                                 src_dict.stoi[onmt.IO.PAD_WORD],
                                 feat_padding_idx,
                                 len(src_dict),
                                 for_encoder=True)
    encoder = make_encoder(model_opt, embeddings)

    embeddings = make_embeddings(model_opt,
                                 tgt_dict.stoi[onmt.IO.PAD_WORD],
                                 feat_padding_idx,
                                 len(tgt_dict),
                                 for_encoder=False)
    decoder = make_decoder(model_opt, embeddings)

    encoder_embeddings = encoder.word_lut.weight.data.tolist()
    decoder_embeddings = decoder.word_lut.weight.data.tolist()

Instances