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111 lines
4.4 KiB
111 lines
4.4 KiB
/* Copyright (c) 2016 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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#pragma once
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#include <algorithm>
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#include <type_traits>
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#include "paddle/fluid/platform/device_context.h"
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#include "paddle/fluid/platform/enforce.h"
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#include "paddle/fluid/platform/hostdevice.h"
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#include "paddle/fluid/platform/place.h"
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#ifdef __NVCC__
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#include <thrust/execution_policy.h>
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#include <thrust/transform.h>
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#include "paddle/fluid/platform/details/cuda_transform_iterator_cast.h"
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#endif
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namespace paddle {
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namespace platform {
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// Transform applys a unary or a binary functor on each element in a
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// range defined by a pair of iterators.
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//
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// - The specialization for CPU calls std::transform.
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// - The specialization for CUDA calls thrust::tranform.
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//
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// NOTE: We need to define InputIter and OutputIter defined as
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// different types, because the InputIter points op's inputs and
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// OutputIter pints to op's outputs.
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//
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// NOTE: We don't assume that InputIter to be const InputType* and
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// OutputIter to be OutputType*, because we might use a iterator
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// class, paddle::fluid::operators::RowwiseTRansformIterator.
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template <typename DeviceContext>
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struct Transform {
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// The unary version.
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template <typename InputIter, typename OutputIter, typename UnaryOperation>
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void operator()(const DeviceContext& context, InputIter first, InputIter last,
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OutputIter result, UnaryOperation op);
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// The binary version.
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template <typename InputIter1, typename InputIter2, typename OutputIter,
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typename BinaryOperation>
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void operator()(const DeviceContext& context, InputIter1 first1,
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InputIter1 last1, InputIter2 first2, OutputIter result,
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BinaryOperation op);
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};
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template <>
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struct Transform<platform::CPUDeviceContext> {
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template <typename InputIter, typename OutputIter, typename UnaryOperation>
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void operator()(const platform::CPUDeviceContext& context, InputIter first,
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InputIter last, OutputIter result, UnaryOperation op) {
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std::transform(first, last, result, op);
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}
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template <typename InputIter1, typename InputIter2, typename OutputIter,
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typename BinaryOperation>
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void operator()(const platform::CPUDeviceContext& context, InputIter1 first1,
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InputIter1 last1, InputIter2 first2, OutputIter result,
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BinaryOperation op) {
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std::transform(first1, last1, first2, result, op);
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}
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};
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#ifdef __NVCC__
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template <>
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struct Transform<platform::CUDADeviceContext> {
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template <typename InputIter, typename OutputIter, typename UnaryOperation>
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void operator()(const platform::CUDADeviceContext& context, InputIter first,
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InputIter last, OutputIter result, UnaryOperation op) {
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auto place = context.GetPlace();
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PADDLE_ENFORCE(is_gpu_place(place), "It must use GPU place.");
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thrust::transform(thrust::cuda::par.on(context.stream()),
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details::CastToCUDATransformIterator(first),
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details::CastToCUDATransformIterator(last),
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details::CastToCUDATransformIterator(result), op);
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}
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template <typename InputIter1, typename InputIter2, typename OutputIter,
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typename BinaryOperation>
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void operator()(const platform::CUDADeviceContext& context, InputIter1 first1,
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InputIter1 last1, InputIter2 first2, OutputIter result,
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BinaryOperation op) {
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auto place = context.GetPlace();
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PADDLE_ENFORCE(is_gpu_place(place), "It must use GPU place.");
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thrust::transform(thrust::cuda::par.on(context.stream()),
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details::CastToCUDATransformIterator(first1),
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details::CastToCUDATransformIterator(last1),
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details::CastToCUDATransformIterator(first2),
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details::CastToCUDATransformIterator(result), op);
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}
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};
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#endif
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} // namespace platform
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} // namespace paddle
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