03b0e7061cf477fbeccb9c128ee76603df582d86,scripts/word_embeddings/evaluate_pretrained.py,,,#,159

Before Change

                "Not implemented for binary fastText model.")

        size = min(len(token_embedding._idx_to_token), args_.max_vocab_size)
        token_embedding._idx_to_token = token_embedding._idx_to_token[:size]
        token_embedding._idx_to_vec = token_embedding._idx_to_vec[:size]
        token_embedding._token_to_idx = {
            token: idx
            for idx, token in enumerate(token_embedding._idx_to_token)
        }

    similarity_results = evaluation.evaluate_similarity(
        args_, token_embedding, ctx, logfile=os.path.join(
            args_.logdir, "similarity{}.tsv".format(name)))

After Change

            if t in token_embedding_.unknown_lookup
        ]]

        if len(token_embedding_.idx_to_token) > args_.max_vocab_size:
            logging.warning("Computing embeddings for OOV words that occur "
                            "in the evaluation dataset lead to having "
                            "more words than --max-vocab-size. "
                            "Have %s words (--max-vocab-size %s)",
                            len(token_embedding_.idx_to_token),
                            args_.max_vocab_size)

    similarity_results = evaluation.evaluate_similarity(
        args_, token_embedding_, ctx, logfile=os.path.join(
            args_.logdir, "similarity{}.tsv".format(name)))
    analogy_results = evaluation.evaluate_analogy(

Instances