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[Accuracy diff No.20、61、9-10] Fix accuracy diff for expand_grad API #72992

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Merged
merged 5 commits into from
Jun 12, 2025
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[Accuracy diff No.20、61、9-10] Fix accuracy diff for expand_grad API #72992

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56 changes: 44 additions & 12 deletions paddle/phi/kernels/impl/expand_grad_kernel_impl.h
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,7 @@
#pragma once

#include "paddle/phi/core/tensor_utils.h"
#include "paddle/phi/kernels/cast_kernel.h"
#include "paddle/phi/kernels/full_kernel.h"
#include "paddle/phi/kernels/funcs/eigen/common.h"
#include "paddle/phi/kernels/funcs/eigen/eigen_function.h"
Expand All @@ -32,19 +33,50 @@ void ExpandBackward(const Context& dev_ctx,
dev_ctx.template Alloc<T>(in_grad);
in_grad->data<T>();

auto x_grad = EigenVector<T>::Flatten(*in_grad);
Eigen::DSizes<Eigen::DenseIndex, Dims * 2> reshape_dims;
for (size_t i = 0; i < reshape_size; ++i) {
reshape_dims[i] = reshape_dims_vec[i];
}
Eigen::DSizes<Eigen::DenseIndex, Dims> reduce_dims;
for (size_t i = 0; i < reduce_size; ++i) {
reduce_dims[i] = reduce_dims_vec[i];
if constexpr (std::is_same_v<T, dtype::float16> ||
std::is_same_v<T, dtype::bfloat16>) {
const DenseTensor out_grad_fp32 =
phi::Cast<T, Context>(dev_ctx, out_grad, DataType::FLOAT32);
DenseTensor in_grad_fp32;
in_grad_fp32.Resize(in_grad->dims());
dev_ctx.template Alloc<float>(&in_grad_fp32);

auto x_grad = EigenVector<float>::Flatten(in_grad_fp32);
Eigen::DSizes<Eigen::DenseIndex, Dims * 2> reshape_dims;
for (size_t i = 0; i < reshape_size; ++i) {
reshape_dims[i] = reshape_dims_vec[i];
}
Eigen::DSizes<Eigen::DenseIndex, Dims> reduce_dims;
for (size_t i = 0; i < reduce_size; ++i) {
reduce_dims[i] = reduce_dims_vec[i];
}
const auto out_grad0 = EigenVector<float>::Flatten(out_grad_fp32);
auto& place = *dev_ctx.eigen_device();
phi::funcs::EigenBroadcastGrad<std::decay_t<decltype(place)>, float, Dims>::
Eval(place, x_grad, out_grad0, reduce_dims, reshape_dims);

if constexpr (std::is_same_v<T, dtype::float16>) {
phi::CastKernel<float, Context>(
dev_ctx, in_grad_fp32, DataType::FLOAT16, in_grad);
} else {
phi::CastKernel<float, Context>(
dev_ctx, in_grad_fp32, DataType::BFLOAT16, in_grad);
}
} else {
auto x_grad = EigenVector<T>::Flatten(*in_grad);
Eigen::DSizes<Eigen::DenseIndex, Dims * 2> reshape_dims;
for (size_t i = 0; i < reshape_size; ++i) {
reshape_dims[i] = reshape_dims_vec[i];
}
Eigen::DSizes<Eigen::DenseIndex, Dims> reduce_dims;
for (size_t i = 0; i < reduce_size; ++i) {
reduce_dims[i] = reduce_dims_vec[i];
}
auto out_grad0 = EigenVector<T>::Flatten(out_grad);
auto& place = *dev_ctx.eigen_device();
phi::funcs::EigenBroadcastGrad<std::decay_t<decltype(place)>, T, Dims>::
Eval(place, x_grad, out_grad0, reduce_dims, reshape_dims);
}
auto out_grad0 = EigenVector<T>::Flatten(out_grad);
auto& place = *dev_ctx.eigen_device();
phi::funcs::EigenBroadcastGrad<std::decay_t<decltype(place)>, T, Dims>::Eval(
place, x_grad, out_grad0, reduce_dims, reshape_dims);
}

template <typename T, typename Context>
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