85 lines
2.7 KiB
C++
85 lines
2.7 KiB
C++
/* Copyright (c) 2022 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 <limits>
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#include "paddle/common/hostdevice.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/kernels/funcs/eigen/common.h"
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namespace phi {
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namespace funcs {
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template <typename T>
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struct TolerableValue {
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HOSTDEVICE T operator()(const T& x) const {
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PADDLE_ENFORCE(std::is_floating_point<T>::value,
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"TolerableValue should be float in cross_entropy.");
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const T kApproInf = 1e20;
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if (x == INFINITY) return kApproInf;
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if (x == -INFINITY) return -kApproInf;
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return x;
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}
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};
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// NOTE(dzh): float16 value clip behave different.
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// 1. Our ValueClipping has a hardcore threshold 1e20
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// for float number. 1e20 will resulting in overflow in float16.
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// 2. float16 should expose the real number overflow to python.
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// because mixed-training depends the inf/nan value to determine
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// if the scale value will be adjusted.
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// Also. In standard implementation of cross entropy, other
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// framework not has the ValueClipping.
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template <>
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struct TolerableValue<phi::float16> {
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HOSTDEVICE phi::float16 operator()(const phi::float16& x) const {
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if (phi::dtype::isfinite(x)) {
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return x;
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} else if (x > static_cast<phi::float16>(0)) {
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return std::numeric_limits<phi::float16>::max();
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} else {
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return std::numeric_limits<phi::float16>::min();
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}
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}
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};
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template <>
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struct TolerableValue<phi::bfloat16> {
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HOSTDEVICE phi::bfloat16 operator()(const phi::bfloat16& x) const {
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if (phi::dtype::isfinite(x)) {
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return x;
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} else if (x > static_cast<phi::bfloat16>(0)) {
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return std::numeric_limits<phi::bfloat16>::max();
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} else {
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return std::numeric_limits<phi::bfloat16>::min();
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}
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}
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};
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template <typename DeviceContext, typename T>
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class CrossEntropyFunctor {
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public:
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void operator()(const DeviceContext& dev_ctx,
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DenseTensor* out,
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const DenseTensor* prob,
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const DenseTensor* labels,
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const bool softLabel,
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const int ignore_index,
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const int64_t axis_dim);
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};
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} // namespace funcs
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} // namespace phi
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