wehub-resource-sync
136 lines
4.5 KiB
C++
136 lines
4.5 KiB
C++
// Copyright (c) 2025 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.
|
|
|
|
#include "paddle/phi/kernels/masked_scatter_grad_kernel.h"
|
|
|
|
#include <cstring>
|
|
|
|
#include "paddle/phi/core/kernel_registry.h"
|
|
#include "paddle/phi/kernels/expand_kernel.h"
|
|
#include "paddle/phi/kernels/full_kernel.h"
|
|
#include "paddle/phi/kernels/funcs/common_infer_shape_functions.h"
|
|
#include "paddle/phi/kernels/funcs/elementwise_base.h"
|
|
#include "paddle/phi/kernels/reduce_sum_kernel.h"
|
|
|
|
namespace phi {
|
|
|
|
template <typename T, typename Context>
|
|
void MaskedScatterGradKernel(const Context& dev_ctx,
|
|
const DenseTensor& x,
|
|
const DenseTensor& mask,
|
|
const DenseTensor& value,
|
|
const DenseTensor& out_grad,
|
|
DenseTensor* x_grad,
|
|
DenseTensor* value_grad) {
|
|
if (out_grad.numel() == 0 || mask.numel() == 0) {
|
|
if (x_grad) {
|
|
phi::Full<T, Context>(dev_ctx,
|
|
phi::IntArray(common::vectorize(x_grad->dims())),
|
|
static_cast<T>(0),
|
|
x_grad);
|
|
}
|
|
if (value_grad) {
|
|
phi::Full<T, Context>(
|
|
dev_ctx,
|
|
phi::IntArray(common::vectorize(value_grad->dims())),
|
|
static_cast<T>(0),
|
|
value_grad);
|
|
}
|
|
return;
|
|
}
|
|
|
|
auto out_grad_dims = out_grad.dims();
|
|
auto mask_dims = mask.dims();
|
|
auto expanded_size =
|
|
vectorize(funcs::BroadcastTwoDims(out_grad_dims, mask_dims, -1));
|
|
DDim expanded_dims = make_ddim(expanded_size);
|
|
|
|
DenseTensor mask_expand;
|
|
if (mask_dims != expanded_dims) {
|
|
ExpandKernel<bool, Context>(
|
|
dev_ctx, mask, IntArray(expanded_size), &mask_expand);
|
|
} else {
|
|
mask_expand = mask;
|
|
}
|
|
|
|
auto* mask_data = mask_expand.data<bool>();
|
|
auto* out_grad_data = out_grad.data<T>();
|
|
int64_t total = out_grad.numel();
|
|
|
|
if (x_grad) {
|
|
auto x_grad_dims = x_grad->dims();
|
|
if (x_grad_dims == out_grad_dims) {
|
|
// No broadcast happened, compute directly into x_grad.
|
|
dev_ctx.template Alloc<T>(x_grad);
|
|
auto* x_grad_data = x_grad->data<T>();
|
|
for (int64_t i = 0; i < total; i++) {
|
|
x_grad_data[i] = mask_data[i] ? static_cast<T>(0) : out_grad_data[i];
|
|
}
|
|
} else {
|
|
// Broadcast happened: compute at broadcast shape, then reduce-sum.
|
|
DenseTensor x_grad_broadcast;
|
|
x_grad_broadcast.Resize(expanded_dims);
|
|
dev_ctx.template Alloc<T>(&x_grad_broadcast);
|
|
auto* x_grad_broadcast_data = x_grad_broadcast.data<T>();
|
|
for (int64_t i = 0; i < total; i++) {
|
|
x_grad_broadcast_data[i] =
|
|
mask_data[i] ? static_cast<T>(0) : out_grad_data[i];
|
|
}
|
|
std::vector<int> reduce_dims =
|
|
funcs::GetReduceDim(x_grad_dims, expanded_dims, -1);
|
|
phi::SumKernel<T, Context>(dev_ctx,
|
|
x_grad_broadcast,
|
|
reduce_dims,
|
|
x_grad_broadcast.dtype(),
|
|
false,
|
|
x_grad);
|
|
}
|
|
}
|
|
|
|
if (value_grad) {
|
|
dev_ctx.template Alloc<T>(value_grad);
|
|
auto* value_grad_data = value_grad->data<T>();
|
|
int64_t value_numel = value_grad->numel();
|
|
std::memset(value_grad_data, 0, value_numel * sizeof(T));
|
|
|
|
int64_t count = 0;
|
|
for (int64_t i = 0; i < total; i++) {
|
|
if (mask_data[i]) {
|
|
if (count < value_numel) {
|
|
value_grad_data[count] = out_grad_data[i];
|
|
}
|
|
count++;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
} // namespace phi
|
|
|
|
PD_REGISTER_KERNEL(masked_scatter_grad,
|
|
CPU,
|
|
ALL_LAYOUT,
|
|
phi::MaskedScatterGradKernel,
|
|
float,
|
|
double,
|
|
int,
|
|
int64_t,
|
|
int16_t,
|
|
int8_t,
|
|
uint8_t,
|
|
phi::float16,
|
|
phi::bfloat16) {
|
|
kernel->InputAt(1).SetDataType(phi::DataType::BOOL);
|
|
}
|