adabf33fa59acb036ddda9a57a4fdf023c1dbaca,deepctr/layers.py,AFMLayer,call,#AFMLayer#Any#,114

Before Change

        embeds_vec_list = inputs
        row = []
        col = []
        num_inputs = len(embeds_vec_list)
        for i in range(num_inputs - 1):
            for j in range(i + 1, num_inputs):
                row.append(i)
                col.append(j)
        p = tf.concat([embeds_vec_list[idx] for idx in row],axis=1)
        q = tf.concat([embeds_vec_list[idx] for idx in col],axis=1)
        inner_product = p * q

        bi_interaction = inner_product

After Change

        if K.ndim(inputs[0]) != 3:
            raise ValueError("Unexpected inputs dimensions %d, expect to be 3 dimensions" % (K.ndim(inputs)))

        embeds_vec_list = inputs
        row = []
        col = []
        // num_inputs = len(embeds_vec_list)
        // for i in range(num_inputs - 1):
        //     for j in range(i + 1, num_inputs):
        //         row.append(i)
        //         col.append(j)
        for r, c in itertools.combinations(embeds_vec_list, 2):
            row.append(r)
            col.append(c)
        //p = tf.concat([embeds_vec_list[idx] for idx in row],axis=1)
        //q = tf.concat([embeds_vec_list[idx] for idx in col], axis=1)
        p = tf.concat(row,axis=1)
        q = tf.concat(col,axis=1)
        inner_product = p * q

Instances