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paddlepaddle--paddle/paddle/phi/kernels/gpu/masked_select_kernel.cu
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// Copyright (c) 2022 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_select_kernel.h"
#include <thrust/device_ptr.h>
#include <thrust/device_vector.h>
#include <thrust/reverse.h>
#include <thrust/scan.h>
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/common/amp_type_traits.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/expand_kernel.h"
#include "paddle/phi/kernels/funcs/common_shape.h"
#include "paddle/phi/kernels/funcs/select_impl.cu.h"
namespace phi {
template <typename MT, typename InT, typename OutT>
struct MaskedSelectFunctor {
HOSTDEVICE MaskedSelectFunctor() = default;
HOSTDEVICE inline void operator()(OutT* out,
const MT* mask,
const InT* value,
int num) {
int store_fix = 0;
for (int idx = 0; idx < num; idx++) {
if (mask[idx]) {
out[store_fix++] = value[idx];
}
}
}
};
template <typename T, typename Context>
void MaskedSelectKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& mask,
DenseTensor* out) {
DenseTensor mask_expand;
DenseTensor x_expand;
if (x.numel() == 0 || mask.numel() == 0) {
out->Resize({0});
dev_ctx.template Alloc<T>(out);
return;
}
auto expanded_size = funcs::MatrixGetBroadcastBatchPortion(
vectorize(x.dims()), vectorize(mask.dims()));
DDim expand_dims = make_ddim(expanded_size);
if (mask.dims() != expand_dims) {
ExpandKernel<bool, Context>(
dev_ctx, mask, IntArray(expanded_size), &mask_expand);
} else {
mask_expand = mask;
}
if (x.dims() != expand_dims) {
ExpandKernel<T, Context>(dev_ctx, x, IntArray(expanded_size), &x_expand);
} else {
x_expand = x;
}
auto input_dim = x_expand.dims();
auto mask_dim = mask_expand.dims();
PADDLE_ENFORCE_EQ(input_dim,
mask_dim,
common::errors::InvalidArgument(
"The dim size of input and mask in OP(masked_selected) "
"must be equal, but got input dim:(%ld), mask dim: "
"(%ld). Please check input "
"value.",
input_dim,
mask_dim));
using Functor = MaskedSelectFunctor<bool, T, T>;
funcs::SelectKernel<bool, T, T, 1, Functor>(
dev_ctx, mask_expand, x_expand, out, Functor());
}
} // namespace phi
PD_REGISTER_KERNEL(masked_select,
GPU,
ALL_LAYOUT,
phi::MaskedSelectKernel,
bool,
float,
double,
int,
int8_t,
int64_t,
int16_t,
uint8_t,
phi::float16,
phi::bfloat16,
phi::complex64,
phi::complex128) {
kernel->InputAt(1).SetDataType(phi::DataType::BOOL);
}