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chongminggao avatar chongminggao commented on June 6, 2024

补充疑问： 新建这个DNN是否该放进build()里，而非在call()里?

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shenweichen avatar shenweichen commented on June 6, 2024

是共享的，是我忘记把build里的self.dnn用在这里了
不过目前写在call里实际执行的时候并不会多次新建，对结果是没有影响的~

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xu-song avatar xu-song commented on June 6, 2024

补充两个LAU的疑问

concat

DeepCTR/deepctr/layers/core.py

Lines 101 to 105 in 9564e05

att_input = tf.concat(
[queries, keys, queries - keys, queries * keys], axis=-1)
att_out = self.dnn(att_input, training=training)

请问这里concat的操作是paper里写的吗？paper里好像没体现 q-k

image

softmax

另外，paper里说不需要softmax，是吧？这里为什么默认 self.weight_normalization=true

DeepCTR/deepctr/layers/sequence.py

Lines 278 to 282 in 9564e05

if self.weight_normalization:
outputs = softmax(outputs)
if not self.return_score:
outputs = tf.matmul(outputs, keys)

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zanshuxun avatar zanshuxun commented on June 6, 2024

@xu-song 这两个地方的实现是与DIN作者的开源代码对齐了，与论文中的表述确实不同。具体为什么这样实现，有什么trick，可能还是得去问一下原作者

concat

concat里加入q-k、q*k，论文里没有体现，是作者开源代码里的实现
https://github.com/zhougr1993/DeepInterestNetwork/blob/9765f96202f849e59ff260c8b46931a0ddf01d77/din/model.py#L209

softmax

论文中说不需要限制和为1，但代码里是做了softmax
https://github.com/zhougr1993/DeepInterestNetwork/blob/9765f96202f849e59ff260c8b46931a0ddf01d77/din/model.py#L225

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xu-song avatar xu-song commented on June 6, 2024

感谢

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