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PR types
New features
PR changes
OPs
Describe
实现的是upscale_in_train方式的dropout:
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使用
DropOutGenMask
+DropOutDoMask
实现Dropout NPU OP。因为随机性,单测中只测试了dropout_prob = 0 和 dropout_prob = 1的情况。
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手动测试了下dropout_prob = 0.3的输出结果,看scale的比例确实是1.428倍 ( 1 / (1-0.3) = 1.428):
注意:
DropOutGenMask
中需要使用Tensorprob
,在NPU执行时其shape必须为0,这里在runner中做了特殊处理,后面需要优化实现。单测结果:
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log:
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