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paddlepaddle--paddle/paddle/phi/kernels/cpu/randint_kernel.cc
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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/randint_kernel.h"
#include <random>
#include "paddle/phi/backends/cpu/cpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
namespace phi {
template <typename T, typename Context>
void RandintKernel(const Context& dev_ctx,
int low,
int high,
const IntArray& shape,
DataType dtype UNUSED,
DenseTensor* out) {
int seed = 0;
out->Resize(shape.GetData());
T* data = dev_ctx.template Alloc<T>(out);
auto numel = out->numel();
std::shared_ptr<std::mt19937_64> engine;
if (seed) {
engine = std::make_shared<std::mt19937_64>();
engine->seed(seed);
} else {
engine = dev_ctx.GetGenerator()->GetCPUEngine();
}
std::uniform_int_distribution<T> dist(low, high - 1);
for (int64_t i = 0; i < numel; ++i) {
data[i] = dist(*engine);
}
}
} // namespace phi
PD_REGISTER_KERNEL(randint, CPU, ALL_LAYOUT, phi::RandintKernel, int, int64_t) {
}