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86 lines
3.2 KiB
86 lines
3.2 KiB
/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/execution_policy.h>
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#include <thrust/random.h>
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#include <thrust/transform.h>
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#include "paddle/fluid/framework/generator.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/operator.h"
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#include "paddle/fluid/operators/bernoulli_op.h"
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#include "paddle/fluid/platform/transform.h"
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namespace paddle {
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namespace operators {
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// it can be consistent with cpu when CUDAGenerator is provided.
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template <typename T>
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struct BernoulliCudaFunctor {
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unsigned int seed_;
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unsigned int offset_;
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__host__ __device__ BernoulliCudaFunctor(unsigned int seed,
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unsigned int offset)
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: seed_(seed), offset_(offset) {}
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__host__ __device__ T operator()(const unsigned int n, const T p) const {
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// NOTE(zhiqiu): currently, PADDLE_ENFORCE in cuda kernel may print several
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// lines of error messages if, and it should be refined.
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PADDLE_ENFORCE(p >= 0.0 && p <= 1.0,
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"The probability should be >=0 and <= 1, but got %f", p);
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thrust::minstd_rand rng;
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rng.seed(seed_);
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thrust::uniform_real_distribution<T> dist(0.0, 1.0);
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rng.discard(n + offset_);
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return static_cast<T>(dist(rng) < p);
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}
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};
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template <typename T>
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class BernoulliOpKernel<platform::CUDADeviceContext, T>
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: public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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const auto x = ctx.Input<framework::Tensor>("X");
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auto out = ctx.Output<framework::Tensor>("Out");
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auto* in_data = x->data<T>();
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auto* out_data = out->mutable_data<T>(ctx.GetPlace());
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int64_t size = x->numel();
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int device_id =
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BOOST_GET_CONST(platform::CUDAPlace, ctx.GetPlace()).GetDeviceId();
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auto gen_cuda = framework::GetDefaultCUDAGenerator(device_id);
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auto seed_offset = gen_cuda->IncrementOffset(1);
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int gen_offset = size * seed_offset.second;
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platform::Transform<platform::CUDADeviceContext> trans;
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thrust::counting_iterator<unsigned int> index_sequence_begin(0);
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auto* context =
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static_cast<const platform::CUDADeviceContext*>(&ctx.device_context());
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trans(*context, index_sequence_begin, index_sequence_begin + size, in_data,
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out_data,
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BernoulliCudaFunctor<T>(static_cast<unsigned int>(seed_offset.first),
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static_cast<unsigned int>(gen_offset)));
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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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namespace plat = paddle::platform;
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REGISTER_OP_CUDA_KERNEL(
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bernoulli, ops::BernoulliOpKernel<plat::CUDADeviceContext, float>,
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ops::BernoulliOpKernel<plat::CUDADeviceContext, double>);
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