You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
84 lines
2.5 KiB
84 lines
2.5 KiB
/* Copyright (c) 2020 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. */
|
|
|
|
#pragma once
|
|
|
|
#include <algorithm>
|
|
#include <bitset>
|
|
#include <vector>
|
|
|
|
#include "paddle/fluid/framework/op_registry.h"
|
|
#include "paddle/fluid/framework/operator.h"
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
using Tensor = framework::Tensor;
|
|
|
|
constexpr size_t dim_bitset_size = 64;
|
|
|
|
template <typename DeviceContext, typename T>
|
|
class FlipKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& ctx) const override;
|
|
};
|
|
|
|
template <typename T>
|
|
class FlipKernel<platform::CPUDeviceContext, T>
|
|
: public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& ctx) const override {
|
|
const Tensor* x = ctx.Input<Tensor>("X");
|
|
Tensor* out = ctx.Output<Tensor>("Out");
|
|
auto flip_dims = ctx.template Attr<std::vector<int>>("axis");
|
|
|
|
auto x_dims = x->dims();
|
|
const int total_dims = x_dims.size();
|
|
std::bitset<dim_bitset_size> dim_bitset;
|
|
for (size_t i = 0; i < flip_dims.size(); ++i) {
|
|
int dim = flip_dims[i];
|
|
if (flip_dims[i] < 0) {
|
|
dim += total_dims;
|
|
}
|
|
dim_bitset[dim] = true;
|
|
}
|
|
auto x_strides = framework::stride(x_dims);
|
|
auto numel = x->numel();
|
|
const T* x_data = x->data<T>();
|
|
T* out_data = out->mutable_data<T>(ctx.GetPlace());
|
|
#ifdef PADDLE_WITH_MKLML
|
|
#pragma omp parallel for
|
|
#endif
|
|
for (int64_t i = 0; i < numel; ++i) {
|
|
int64_t cur_indices = i;
|
|
int64_t rem = 0;
|
|
int64_t dst_offset = 0;
|
|
|
|
for (int d = 0; d < total_dims; ++d) {
|
|
int64_t temp = cur_indices;
|
|
cur_indices = cur_indices / x_strides[d];
|
|
rem = temp - cur_indices * x_strides[d];
|
|
dst_offset += dim_bitset[d]
|
|
? (x_dims[d] - 1 - cur_indices) * x_strides[d]
|
|
: cur_indices * x_strides[d];
|
|
cur_indices = rem;
|
|
}
|
|
out_data[i] = x_data[dst_offset];
|
|
}
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|