/* Copyright (c) 2023 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. */ #pragma once #include #include #include "paddle/common/hostdevice.h" #include "paddle/phi/backends/all_context.h" #include "paddle/phi/core/enforce.h" #if defined(__NVCC__) || defined(__HIPCC__) #include #include #include "thrust/device_ptr.h" #endif namespace phi { // Transform applies a unary or a binary functor on each element in a // range defined by a pair of iterators. // // - The specialization for CPU calls std::transform. // - The specialization for CUDA calls thrust::transform. // // NOTE: We need to define InputIter and OutputIter defined as // different types, because the InputIter points op's inputs and // OutputIter points to op's outputs. // // NOTE: We don't assume that InputIter to be const InputType* and // OutputIter to be OutputType*, because we might use a iterator // class, phi::RowwiseTransformIterator. template struct Transform { // The unary version. template void operator()(const Context& dev_ctx, InputIter first, InputIter last, OutputIter result, UnaryOperation op); // The binary version. template void operator()(const Context& dev_ctx, InputIter1 first1, InputIter1 last1, InputIter2 first2, OutputIter result, BinaryOperation op); }; // NOTE: After the phi kernel is migrated, it needs to be deleted. template <> struct Transform { template void operator()(const CPUContext& dev_ctx UNUSED, InputIter first, InputIter last, OutputIter result, UnaryOperation op) { std::transform(first, last, result, op); } template void operator()(const CPUContext& dev_ctx UNUSED, InputIter1 first1, InputIter1 last1, InputIter2 first2, OutputIter result, BinaryOperation op) { std::transform(first1, last1, first2, result, op); } }; #if defined(__NVCC__) || defined(__HIPCC__) // PointerToThrustDevicePtr has two specializations, one casts a (CUDA // device) pointer into thrust::device_ptr, the other keeps rest types // un-casted. template struct PointerToThrustDevicePtr; template struct PointerToThrustDevicePtr { using ELEM = typename std::remove_pointer::type; using RTYPE = thrust::device_ptr; inline thrust::device_ptr operator()(ELEM* ele) const { return thrust::device_pointer_cast(ele); } }; template struct PointerToThrustDevicePtr { using RTYPE = T; inline RTYPE operator()(RTYPE it) const { return it; } }; // CastToCUDATransformIterator casts a pointer to thrust::device_ptr // so it could be used as the iterator of thrust::transform. It // doesn't cast other types. // // We need CastToCUDATransformIterator because it is often that we // want to use device memory pointers as transform iterators, e.g., to // transform a block of float32 to float16. In this case, we want // CastToCUDATransformIterator to cast float16/32 pointers to // thrust::device_ptr, otherwise they cannot work as the iterator // required by thrust::transform. At the same time, we don't want to // cast thrust::device_ptr to thrust::device_ptr repeatedly. template auto CastToCUDATransformIterator(T t) -> typename PointerToThrustDevicePtr::value>::RTYPE { PointerToThrustDevicePtr::value> cast; return cast(t); } template <> struct Transform { template void operator()(const GPUContext& dev_ctx, InputIter first, InputIter last, OutputIter result, UnaryOperation op) { auto place = dev_ctx.GetPlace(); #ifndef PADDLE_WITH_CUSTOM_DEVICE PADDLE_ENFORCE_EQ(place.GetType() == phi::AllocationType::GPU, true, common::errors::PreconditionNotMet( "The CUDA Transform must be used in GPU place.")); #else PADDLE_ENFORCE_EQ(place.GetType() == phi::AllocationType::CUSTOM, true, common::errors::PreconditionNotMet( "The CUDA Transform must be used in CUSTOM place.")); #endif #ifdef __HIPCC__ thrust::transform(thrust::hip::par.on(dev_ctx.stream()), CastToCUDATransformIterator(first), CastToCUDATransformIterator(last), CastToCUDATransformIterator(result), op); #else thrust::transform(thrust::cuda::par.on(dev_ctx.stream()), CastToCUDATransformIterator(first), CastToCUDATransformIterator(last), CastToCUDATransformIterator(result), op); #endif } template void operator()(const GPUContext& dev_ctx, InputIter1 first1, InputIter1 last1, InputIter2 first2, OutputIter result, BinaryOperation op) { auto place = dev_ctx.GetPlace(); #ifndef PADDLE_WITH_CUSTOM_DEVICE PADDLE_ENFORCE_EQ(place.GetType() == phi::AllocationType::GPU, true, common::errors::PreconditionNotMet( "The CUDA Transform must be used in GPU place.")); #else PADDLE_ENFORCE_EQ(place.GetType() == phi::AllocationType::CUSTOM, true, common::errors::PreconditionNotMet( "The CUDA Transform must be used in CUSTOM place.")); #endif #ifdef __HIPCC__ thrust::transform(thrust::hip::par.on(dev_ctx.stream()), CastToCUDATransformIterator(first1), CastToCUDATransformIterator(last1), CastToCUDATransformIterator(first2), CastToCUDATransformIterator(result), op); #else thrust::transform(thrust::cuda::par.on(dev_ctx.stream()), CastToCUDATransformIterator(first1), CastToCUDATransformIterator(last1), CastToCUDATransformIterator(first2), CastToCUDATransformIterator(result), op); #endif } }; #endif } // namespace phi