【Hackathon No.62】digamma, dirichlet算子FP16/BF16单测完善 #52604
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你的PR提交成功，感谢你对开源项目的贡献! |
ZzSean
reviewed
Apr 13, 2023
| using MPTypeScalar = typename phi::dtype::MPTypeTrait<ScalarT>::Type; | ||
| using MPTypeAccscalar = typename phi::dtype::MPTypeTrait<AccscalarT>::Type; | ||
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| // AccscalarT scale = 1.0f; |
ZzSean
reviewed
Apr 13, 2023
| @@ -83,33 +87,41 @@ HOSTDEVICE ScalarT | |||
| sample_gamma(ScalarT alpha, | |||
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外部调用这里的时候，是不是也需要把模版参数修改下？
auto sample =
sample_gamma<T, T, decltype(uniform_lambda), decltype(normal_lambda)>(
alpha_[index], standard_uniform, standard_normal);
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没明白这里是什么问题，调用sample_gamma 参数 alpha, gamma都是T类型，sample_gamma定义是ScalarT，AccscalarT两种类型，可以调用
ZzSean
reviewed
Apr 13, 2023
| def init_dtype_type(self): | ||
| self.dtype = np.float16 | ||
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| def test_check_grad_normal(self): |
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digamma, dirichlet算子FP16/BF16单测完善
dirichlet bfloat16 测试值差异在0.3以下
文档修改 PaddlePaddle/docs#5782
已修改digamma文档，没有dirichlet文档