Listwise loss代码及Pairwise Loss代码

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于 2025-04-22 13:59:32 发布 · 232 阅读

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#tensorflow #python #人工智能

    def _listwise_loss(self, logits_in, labels_in, masks):
        """
        Copied from Hanshu.
        :param logits_in:
        :param labels_in:
        :param masks: B,B
        :return:
        """
        _EPSILON = 1e-10
        logits_bb = tf.subtract(tf.expand_dims(logits_in, 1), tf.zeros_like(tf.expand_dims(logits_in, 0)))
        logits_bb = tf.squeeze(logits_bb, [2])
        logits_final = tf.where(masks, logits_bb, tf.log(_EPSILON) * tf.ones_like(logits_bb))

        labels_bb = tf.subtract(tf.expand_dims(labels_in, 1), tf.zeros_like(tf.expand_dims(labels_in, 0)))
        labels_bb = tf.squeeze(labels_bb, [2])
        labels_final = tf.where(masks, labels_bb, tf.zeros_like(labels_bb))

        label_sum = tf.reduce_sum(input_tensor=labels_final, axis=0, keep_dims=True)
        nonzero_mask = tf.greater(tf.reshape(label_sum, [-1]), 0.0)
        padded_labels = tf.where(nonzero_mask, labels_final, _EPSILON * tf.ones_like(labels_final)) *