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2026-07-13 12:40:42 +08:00

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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/phi/kernels/exponential_kernel.h"
#include <random>
#include "paddle/phi/backends/cpu/cpu_context.h"
#include "paddle/phi/common/amp_type_traits.h"
#include "paddle/phi/core/generator.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/funcs/distribution_helper.h"
namespace phi {
template <typename T, typename Context>
void ExponentialKernel(const Context& dev_ctx,
const DenseTensor& x,
float lambda,
DenseTensor* out) {
T* out_data = dev_ctx.template Alloc<T>(out);
auto engine = dev_ctx.GetGenerator()->GetCPUEngine();
std::uniform_real_distribution<T> uniform(0.0, 1.0);
funcs::exponential_transform<T> trans(lambda);
for (int64_t i = 0; i < out->numel(); ++i) {
out_data[i] = trans(uniform(*engine));
}
}
} // namespace phi
PD_REGISTER_KERNEL(
exponential, CPU, ALL_LAYOUT, phi::ExponentialKernel, float, double) {}