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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/cumprod_kernel.h"
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/funcs/complex_functors.h"
#include "paddle/phi/kernels/funcs/cumprod.h"
#include "paddle/phi/kernels/funcs/elementwise_functor.h"
#include "paddle/phi/kernels/funcs/exclusive_scan.h"
#include "paddle/phi/kernels/funcs/inclusive_scan.h"
namespace phi {
template <typename T, typename Context>
void CumprodKernel(const Context &dev_ctx,
const DenseTensor &input,
int dim,
bool exclusive,
bool reverse,
DenseTensor *out) {
const auto *x = &input;
auto *y = out;
size_t outer_dim, mid_dim, inner_dim;
GetCumprodDimInfo(x->dims(), dim, &outer_dim, &mid_dim, &inner_dim);
if (x->dims().size() == 0) {
Copy<Context>(dev_ctx, input, dev_ctx.GetPlace(), false, out);
return;
}
const auto *x_data = x->data<T>();
auto *y_data = dev_ctx.template Alloc<T>(y);
if (!exclusive) {
funcs::InclusiveScan(x_data,
y_data,
outer_dim,
mid_dim,
inner_dim,
static_cast<T>(1),
funcs::MultiplyFunctor<T>(),
/*reverse=*/reverse,
dev_ctx);
} else {
funcs::ExclusiveScan(x_data,
y_data,
outer_dim,
mid_dim,
inner_dim,
static_cast<T>(1),
funcs::MultiplyFunctor<T>(),
/*reverse=*/reverse,
dev_ctx);
}
}
} // namespace phi
PD_REGISTER_KERNEL(cumprod,
GPU,
ALL_LAYOUT,
phi::CumprodKernel,
float,
double,
int,
int64_t,
phi::float16,
phi::bfloat16,
phi::complex64,
phi::complex128) {}