matching.py 文件源码

def attentive_matching(input_sentence, att_matrix, weights):
    """
    Parameters
    ----------
    input_sentence: Tensor
        Tensor of shape (batch_size, num_sentence_words, rnn_hidden_dim)

    att_matrix: Tensor
        Tensor of shape (batch_size, num_sentence_words, rnn_hidden_dim)
    """
    def single_instance(inputs):
        # Shapes: (num_sentence_words, rnn_hidden_dim)
        sentence_a_single = inputs[0]
        sentence_b_single_att = inputs[1]

        # Shapes: (num_sentence_words, multiperspective_dims, rnn_hidden_dim)
        expanded_sentence_a_single = multi_perspective_expand_for_2D(
            sentence_a_single, weights)
        expanded_sentence_b_single_att = multi_perspective_expand_for_2D(
            sentence_b_single_att, weights)
        # Shape: (num_sentence_words, multiperspective_dims)
        return cosine_distance(expanded_sentence_a_single,
                               expanded_sentence_b_single_att)

    elems = (input_sentence, att_matrix)
    # Shape: (batch_size, num_sentence_words, multiperspective_dims)
    return tf.map_fn(single_instance, elems, dtype="float")