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.
72 lines
2.3 KiB
72 lines
2.3 KiB
// Copyright (c) 2018 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 <vector>
|
|
#include "paddle/fluid/operators/reduce_ops/cub_reduce.h"
|
|
#include "paddle/fluid/operators/reduce_ops/reduce_mean_op.h"
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
template <typename T>
|
|
struct DivideFunctor {
|
|
HOSTDEVICE explicit inline DivideFunctor(int n) : n_inv((T)(1.0 / n)) {}
|
|
|
|
HOSTDEVICE inline T operator()(const T& x) const { return x * n_inv; }
|
|
|
|
private:
|
|
T n_inv;
|
|
};
|
|
|
|
template <typename T>
|
|
class ReduceMeanKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& context) const override {
|
|
bool reduce_all = context.Attr<bool>("reduce_all");
|
|
auto* input = context.Input<Tensor>("X");
|
|
auto* output = context.Output<Tensor>("Out");
|
|
|
|
auto dims = context.Attr<std::vector<int>>("dim");
|
|
bool keep_dim = context.Attr<bool>("keep_dim");
|
|
|
|
std::vector<int> reduce_dims;
|
|
if (reduce_all) {
|
|
reduce_dims.resize(input->dims().size());
|
|
for (int i = 0; i < reduce_dims.size(); ++i) reduce_dims[i] = i;
|
|
} else {
|
|
for (auto e : dims) {
|
|
reduce_dims.push_back(e >= 0 ? e : e + input->dims().size());
|
|
}
|
|
}
|
|
|
|
int reduce_num = 1;
|
|
for (int i = 0; i < reduce_dims.size(); ++i) {
|
|
reduce_num *= input->dims()[reduce_dims[i]];
|
|
}
|
|
|
|
auto stream = context.cuda_device_context().stream();
|
|
TensorReduce<T, T, cub::Sum, DivideFunctor<T>>(
|
|
*input, output, reduce_dims, static_cast<T>(0), cub::Sum(),
|
|
DivideFunctor<T>(reduce_num), stream);
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|
|
|
|
REGISTER_OP_CUDA_KERNEL(reduce_mean, ops::ReduceMeanKernel<float>,
|
|
ops::ReduceMeanKernel<double>,
|
|
ops::ReduceMeanKernel<int>,
|
|
ops::ReduceMeanKernel<int64_t>);
|