1207689fa1e6ff2d321ccc182be13825b4e2575e,pytext/models/embeddings/word_embedding.py,WordEmbedding,from_config,#Any#Any#Any#Any#Any#,41

Before Change

                if config.vocab_from_pretrained_embeddings:
                    // pretrained embeddings will get a freq count of 1
                    assert config.min_freq == 1, (
                        "If `vocab_from_pretrained_embeddings` is set, the vocab"s "
                        "`min_freq` must be 1"
                    )
                    if not config.vocab_from_train_data:  // Reset token counter.
                        tensorizer.vocab_builder._counter = collections.Counter()
                    pretrained_vocab = pretrained_embedding.embed_vocab
                    if config.vocab_size:

After Change

            // We don"t need to load pretrained embeddings if we know the
            // embedding weights are going to be loaded from a snapshot.
            if config.pretrained_embeddings_path and not init_from_saved_state:
                if not any(
                    vocab_file.filepath == config.pretrained_embeddings_path
                    for vocab_file in tensorizer.vocab_config.vocab_files
                ):
                    raise ValueError(
                        f"Tensorizer"s vocab files should include pretrained "
                        f"embeddings file {config.pretrained_embeddings_path}."
                    )
                pretrained_embedding = PretrainedEmbedding(
                    config.pretrained_embeddings_path,  // doesn"t support fbpkg
                    lowercase_tokens=config.lowercase_tokens,
                )

Instances