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138 lines
4.3 KiB
138 lines
4.3 KiB
// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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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#define EIGEN_USE_GPU
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#include <array>
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#include "paddle/fluid/platform/enforce.h"
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#include "unsupported/Eigen/CXX11/Tensor"
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namespace paddle {
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namespace framework {
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template <typename T, int Size, T DefaultValue>
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struct DeviceArray {
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const T& operator[](int index) const {
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return data[index];
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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T& operator[](int index) {
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return data[index];
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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceArray() {
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for (int i = 0; i < Size; i++) {
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data[i] = DefaultValue;
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}
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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceArray(T a0) {
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data[0] = a0;
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for (int i = 1; i < Size; i++) {
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data[i] = DefaultValue;
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}
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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceArray(T a0, T a1) {
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data[0] = a0;
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data[1] = a1;
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for (int i = 2; i < Size; i++) {
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data[i] = DefaultValue;
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}
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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceArray(T a0, T a1, T a2) {
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data[0] = a0;
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data[1] = a1;
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data[2] = a2;
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for (int i = 3; i < Size; i++) {
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data[i] = DefaultValue;
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}
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}
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EIGEN_STRONG_INLINE DeviceArray(const std::array<T, Size>& sa) {
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for (int i = 0; i < Size; i++) {
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data[i] = sa[i];
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}
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}
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T data[Size];
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};
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struct Dim3 : DeviceArray<int, 3, 1> {
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typedef DeviceArray<int, 3, 1> Base;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Dim3() : Base() {}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Dim3(int a0, int a1, int a2)
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: Base(a0, a1, a2) {}
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EIGEN_STRONG_INLINE Dim3(const std::array<int, 3>& array) : Base(array) {}
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};
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struct Index3 : DeviceArray<int, 3, 0> {
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typedef DeviceArray<int, 3, 0> Base;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index3() : Base() {}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index3(int a0, int a1, int a2)
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: Base(a0, a1, a2) {}
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};
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// Flat index with real dimension
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int FlatTensorIndex(const Index3& index,
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const Dim3& dims) {
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int flat_index = index[0];
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for (int i = 1; i < 3; i++) {
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flat_index = flat_index * dims[i] + index[i];
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}
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return flat_index;
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}
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// Convert index to tensor index with dimension.
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index3
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ConvertTensorIndex(int index, const Dim3& dims) {
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Index3 tensor_index;
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for (int i = 2; i >= 0; i--) {
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int new_index = index / dims[i];
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tensor_index[i] = index - dims[i] * new_index;
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index = new_index;
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}
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return tensor_index;
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}
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template <typename IntType, bool ceil>
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IntType CeilOrFloor(IntType x, IntType deviser) {
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PADDLE_ENFORCE_GT(deviser, 0, platform::errors::InvalidArgument(
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"deviser should be greater than 0, "
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"but received is:%d",
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deviser));
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PADDLE_ENFORCE_GT(
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x, 0, platform::errors::InvalidArgument("input should be greater than 0, "
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"but received is:%d",
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x));
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const IntType round_to_zero = x / deviser;
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const IntType inte_result = round_to_zero * deviser;
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if (ceil) {
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const bool do_adjustment =
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(round_to_zero >= 0) && (deviser > 0 && x > inte_result);
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const IntType adjustment = static_cast<IntType>(do_adjustment);
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const IntType ceil_val = round_to_zero + adjustment;
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return ceil_val;
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} else {
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const bool do_adjustment =
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(round_to_zero <= 0) && (deviser > 0 && x < inte_result);
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const IntType adjustment = static_cast<IntType>(do_adjustment);
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const IntType floor_val = round_to_zero - adjustment;
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return floor_val;
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}
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}
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} // namespace framework
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} // namespace paddle
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