mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-11-01 04:12:58 +08:00
79 lines
2.5 KiB
C++
79 lines
2.5 KiB
C++
// 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 "fastdeploy/function/cumprod.h"
|
|
|
|
namespace fastdeploy {
|
|
namespace function {
|
|
|
|
void GetCumprodDimInfo(const std::vector<int64_t>& dim, int cumprod_dim,
|
|
size_t* outer_dim, size_t* mid_dim, size_t* inner_dim) {
|
|
int dim_size = dim.size();
|
|
FDASSERT(cumprod_dim >= -dim_size,
|
|
"The input dim of CumprodOp should be larger than the opposite "
|
|
"rank of input x which is %d. But received dim = %d",
|
|
-dim_size, cumprod_dim);
|
|
FDASSERT(cumprod_dim < dim_size,
|
|
"The input dim of CumprodOp should be smaller than the "
|
|
"rank of input x which is %d. But received dim = %d",
|
|
dim_size, cumprod_dim);
|
|
if (cumprod_dim < 0)
|
|
cumprod_dim += dim_size;
|
|
|
|
*outer_dim = 1;
|
|
for (int i = 0; i < cumprod_dim; ++i) {
|
|
*outer_dim *= dim[i];
|
|
}
|
|
*mid_dim = dim[cumprod_dim];
|
|
*inner_dim = 1;
|
|
for (int i = cumprod_dim + 1; i < dim_size; ++i) {
|
|
*inner_dim *= dim[i];
|
|
}
|
|
}
|
|
|
|
template <typename T>
|
|
void CumprodKernel(const FDTensor& x, FDTensor* out, int axis) {
|
|
auto* x_data = reinterpret_cast<const T*>(x.Data());
|
|
auto shape = x.Shape();
|
|
|
|
size_t outer_dim = 1;
|
|
size_t mid_dim = 1;
|
|
size_t inner_dim = 1;
|
|
GetCumprodDimInfo(shape, axis, &outer_dim, &mid_dim, &inner_dim);
|
|
|
|
out->Allocate(x.Shape(), x.Dtype());
|
|
auto* out_data = reinterpret_cast<T*>(out->Data());
|
|
|
|
for (size_t i = 0; i < outer_dim; i++) {
|
|
for (size_t j = 0; j < mid_dim; j++) {
|
|
for (size_t k = 0; k < inner_dim; k++) {
|
|
size_t pos = i * mid_dim * inner_dim + j * inner_dim + k;
|
|
if (j == 0) {
|
|
out_data[pos] = x_data[pos];
|
|
} else {
|
|
out_data[pos] = out_data[pos - inner_dim] * x_data[pos];
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void Cumprod(const FDTensor& x, FDTensor* out, int axis) {
|
|
FD_VISIT_INT_FLOAT_TYPES(x.dtype, "CumprodKernel",
|
|
([&] { CumprodKernel<data_t>(x, out, axis); }));
|
|
}
|
|
|
|
} // namespace function
|
|
} // namespace fastdeploy
|