add dirichlet random sample op in cpu and gpu kernel #38244
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jeff41404
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| #define compat_exp exp | ||
| #define compat_ceil ceil | ||
| #define compat_floor floor | ||
| #define compat_log log | ||
| #define compat_pow pow | ||
| #define compat_sqrt sqrt | ||
| #define compat_tan tan | ||
| #define compat_abs abs | ||
| #define compat_log1p log1p | ||
| #else | ||
| #define compat_exp std::exp | ||
| #define compat_ceil std::ceil | ||
| #define compat_floor std::floor | ||
| #define compat_log std::log | ||
| #define compat_pow std::pow | ||
| #define compat_sqrt std::sqrt | ||
| #define compat_tan std::tan | ||
| #define compat_abs std::abs | ||
| #define compat_log1p std::log1p |
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macro's name use underline delimited all capital charactor nomenclature
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| template <typename DeviceContext, typename T> | ||
| struct DirichletSampler; | ||
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| template <typename scalar_t, typename sampler_t> |
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The first letter of template parameter should be capitalized.
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| #define compat_rand_init curand_init | ||
| #define compat_rand_uniform curand_uniform | ||
| #define compat_rand_normal curand_normal | ||
| #elif defined(PADDLE_WITH_HIP) | ||
| using compatRandStatePhilox4_32_10_t = hiprandStatePhilox4_32_10_t; | ||
| #define compat_rand_init hiprand_init | ||
| #define compat_rand_uniform hiprand_uniform | ||
| #define compat_rand_normal hiprand_normal |
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| template <typename scalar_t, typename accscalar_t, typename uniform_sampler_t, | ||
| typename normal_sampler_t> |
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The first letter of template parameter should be capitalized.
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| namespace paddle { | ||
| namespace operators { | ||
| template <typename T, typename uniform_sampler_t, typename normal_sampler_t> |
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The first letter of template parameter should be capitalized.
* WIP: add dirichlet sample op * add cuda kernel for dirichlet op
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PR types
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Describe
Dirichlet and Beta distribution API need fast dirichlet random generator for draw sample data, we implement it in cpu and cuda backend use reject-accept sample and inverse-transform sample method.