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在 StaticEmbedding forward 方法中, words = self.drop_word(words) words = self.embedding(words) words = self.dropout(words)
words = self.drop_word(words) words = self.embedding(words) words = self.dropout(words)
drop_word 函数有 self.training 的判断,但是 dropout 没有,导致在推断的时候,同样的 query 预测结果不一致问题
The text was updated successfully, but these errors were encountered:
由于 self.dropout 是nn.Dropout,它本身是受到module的training状态管控的,所以如果调用了 StaticEmbedding.eval() 的话,这个 dropout 就是自动关闭的了。
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在 StaticEmbedding forward 方法中,
words = self.drop_word(words) words = self.embedding(words) words = self.dropout(words)
drop_word 函数有 self.training 的判断,但是 dropout 没有,导致在推断的时候,同样的 query 预测结果不一致问题
The text was updated successfully, but these errors were encountered: