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