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
2.9 KiB
84 lines
2.9 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.
|
|
#include <thrust/random.h>
|
|
#include <thrust/transform.h>
|
|
#include "paddle/fluid/framework/generator.h"
|
|
#include "paddle/fluid/framework/op_registry.h"
|
|
#include "paddle/fluid/operators/uniform_random_op.h"
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
template <typename T>
|
|
class GPURandintKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& context) const override {
|
|
std::vector<int64_t> new_shape;
|
|
auto list_new_shape_tensor =
|
|
context.MultiInput<framework::Tensor>("ShapeTensorList");
|
|
if (list_new_shape_tensor.size() > 0 || context.HasInput("ShapeTensor")) {
|
|
if (context.HasInput("ShapeTensor")) {
|
|
auto* shape_tensor = context.Input<framework::Tensor>("ShapeTensor");
|
|
new_shape = GetNewDataFromShapeTensor(shape_tensor);
|
|
} else if (list_new_shape_tensor.size() > 0) {
|
|
new_shape = GetNewDataFromShapeTensorList(list_new_shape_tensor);
|
|
}
|
|
}
|
|
|
|
platform::CPUPlace cpu;
|
|
auto dtype = static_cast<framework::proto::VarType::Type>(
|
|
context.Attr<int>("dtype"));
|
|
auto* out = context.Output<framework::LoDTensor>("Out");
|
|
if (!new_shape.empty()) out->Resize(framework::make_ddim(new_shape));
|
|
T low = static_cast<T>(context.Attr<int>("low"));
|
|
T high = static_cast<T>(context.Attr<int>("high")) - 1;
|
|
framework::LoDTensor tensor;
|
|
tensor.Resize(out->dims());
|
|
tensor.mutable_data(cpu, dtype);
|
|
T* data = tensor.mutable_data<T>(cpu);
|
|
|
|
int64_t size = out->numel();
|
|
unsigned int seed = static_cast<unsigned int>(context.Attr<int>("seed"));
|
|
|
|
/*
|
|
std::minstd_rand engine;
|
|
if (seed == 0) {
|
|
std::random_device rd;
|
|
seed = rd();
|
|
}
|
|
engine.seed(seed);
|
|
*/
|
|
|
|
std::uniform_int_distribution<> dist(context.Attr<int>("low"),
|
|
context.Attr<int>("high") - 1);
|
|
auto engine = framework::GetCPURandomEngine(seed);
|
|
|
|
for (int64_t i = 0; i < size; ++i) {
|
|
data[i] = dist(*engine);
|
|
}
|
|
|
|
if (platform::is_gpu_place(context.GetPlace())) {
|
|
// Copy tensor to out
|
|
framework::TensorCopy(tensor, context.GetPlace(), out);
|
|
}
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|
|
|
|
namespace ops = paddle::operators;
|
|
REGISTER_OP_CUDA_KERNEL(randint, ops::GPURandintKernel<int>,
|
|
ops::GPURandintKernel<int64_t>)
|