wehub-resource-sync
78 lines
2.5 KiB
Plaintext
78 lines
2.5 KiB
Plaintext
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#ifdef __NVCC__
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#include <curand_kernel.h>
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#endif
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#ifdef __HIPCC__
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#include <hiprand_kernel.h>
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#endif
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/backends/gpu/gpu_launch_config.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/for_range.h"
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#include "paddle/phi/kernels/poisson_kernel.h"
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namespace phi {
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template <typename T>
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__global__ void GetPoisson(
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const T* in, T* out, const int N, unsigned int seed, unsigned int offset) {
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CUDA_KERNEL_LOOP_TYPE(idx, N, int64_t) {
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#ifdef __NVCC__
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curandStatePhilox4_32_10_t state;
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curand_init(seed, idx, offset, &state);
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out[idx] = static_cast<T>(curand_poisson(&state, in[idx]));
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#elif __HIPCC__
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hiprandStatePhilox4_32_10_t state;
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hiprand_init(seed, idx, offset, &state);
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out[idx] = static_cast<T>(hiprand_poisson(&state, in[idx]));
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#endif
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}
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}
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template <typename T, typename Context>
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void PoissonKernel(const Context& dev_ctx,
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const DenseTensor& x,
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DenseTensor* out) {
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const T* x_data = x.data<T>();
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T* out_data = dev_ctx.template Alloc<T>(out);
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const int64_t size = x.numel();
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const int kMaxBlockDim = 256;
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int block_size = std::min(kMaxBlockDim, dev_ctx.GetMaxThreadsPerBlock());
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dim3 dim_block(block_size);
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int64_t grid_max = dev_ctx.GetCUDAMaxGridDimSize()[0];
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int grid = std::min((size + block_size - 1) / block_size, grid_max);
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dim3 dim_grid(grid);
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auto gen_cuda = dev_ctx.GetGenerator();
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auto seed_offset = gen_cuda->IncrementOffset(20);
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uint64_t seed = seed_offset.first;
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uint64_t offset = seed_offset.second;
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GetPoisson<T><<<dim_grid, dim_block>>>(x_data, out_data, size, seed, offset);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(poisson,
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GPU,
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ALL_LAYOUT,
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phi::PoissonKernel,
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float,
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double,
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phi::float16,
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phi::bfloat16) {}
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