def _read_embeddings_from_hdf5(embeddings_filename: str,
                               embedding_dim: int,
                               vocab: Vocabulary,
                               namespace: str = "tokens") -> torch.FloatTensor:
    """
    Reads from a hdf5 formatted file. The embedding matrix is assumed to
    be keyed by 'embedding' and of size ``(num_tokens, embedding_dim)``.
    """
    with h5py.File(embeddings_filename, 'r') as fin:
        embeddings = fin['embedding'][...]

    if list(embeddings.shape) != [vocab.get_vocab_size(namespace), embedding_dim]:
        raise ConfigurationError(
                "Read shape {0} embeddings from the file, but expected {1}".format(
                        list(embeddings.shape), [vocab.get_vocab_size(namespace), embedding_dim]))

    return torch.FloatTensor(embeddings)
Reads from a hdf5 formatted file. The embedding matrix is assumed to
    be keyed by 'embedding' and of size ``(num_tokens, embedding_dim)``.