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fix node2vec neg affinity calculation

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Rex Ying 2018-07-23 17:47:28 -04:00 committed by GitHub
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commit d928dc72f6
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graphsage/models.py
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@ -477,7 +477,7 @@ class Node2VecModel(GeneralizedModel):
def _loss(self): def _loss(self):
aff = tf.reduce_sum(tf.multiply(self.outputs1, self.outputs2), 1) + self.outputs2_bias aff = tf.reduce_sum(tf.multiply(self.outputs1, self.outputs2), 1) + self.outputs2_bias
neg_aff = tf.matmul(self.outputs2, tf.transpose(self.neg_outputs)) + self.neg_outputs_bias neg_aff = tf.matmul(self.outputs1, tf.transpose(self.neg_outputs)) + self.neg_outputs_bias
true_xent = tf.nn.sigmoid_cross_entropy_with_logits( true_xent = tf.nn.sigmoid_cross_entropy_with_logits(
labels=tf.ones_like(aff), logits=aff) labels=tf.ones_like(aff), logits=aff)
negative_xent = tf.nn.sigmoid_cross_entropy_with_logits( negative_xent = tf.nn.sigmoid_cross_entropy_with_logits(