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77 lines
2.8 KiB
77 lines
2.8 KiB
// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include <thrust/random.h>
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#include <thrust/transform.h>
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/uniform_random_op.h"
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namespace paddle {
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namespace operators {
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template <typename T>
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struct UniformIntGenerator {
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T low_, high_;
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__host__ __device__ UniformIntGenerator(T low, T high)
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: low_(low), high_(high) {}
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__host__ __device__ T operator()(const unsigned int n) const {
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thrust::minstd_rand rng;
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rng.seed(0);
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thrust::uniform_int_distribution<T> dist(low_, high_);
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rng.discard(n);
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T out = dist(rng);
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return out;
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}
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};
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// Use std::uniform_int_distribution and thrust::uniform_int_distribution(thrust
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// is a std library in CUDA) to
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// implement randint.
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template <typename T>
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class GPURandintKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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std::vector<int64_t> new_shape;
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auto list_new_shape_tensor =
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context.MultiInput<framework::Tensor>("ShapeTensorList");
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if (list_new_shape_tensor.size() > 0 || context.HasInput("ShapeTensor")) {
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if (context.HasInput("ShapeTensor")) {
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auto* shape_tensor = context.Input<framework::Tensor>("ShapeTensor");
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new_shape = GetNewDataFromShapeTensor(shape_tensor);
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} else if (list_new_shape_tensor.size() > 0) {
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new_shape = GetNewDataFromShapeTensorList(list_new_shape_tensor);
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}
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}
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auto* out = context.Output<framework::LoDTensor>("Out");
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if (!new_shape.empty()) out->Resize(framework::make_ddim(new_shape));
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T* data = out->mutable_data<T>(context.GetPlace());
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T low = static_cast<T>(context.Attr<int>("low"));
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T high = static_cast<T>(context.Attr<int>("high")) - 1;
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thrust::counting_iterator<unsigned int> index_sequence_begin(0);
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int64_t size = out->numel();
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thrust::transform(index_sequence_begin, index_sequence_begin + size,
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thrust::device_ptr<T>(data),
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UniformIntGenerator<T>(low, high));
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_CUDA_KERNEL(randint, ops::GPURandintKernel<int>,
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ops::GPURandintKernel<int64_t>)
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