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89 lines
3.0 KiB
89 lines
3.0 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 "paddle/fluid/operators/bernoulli_op.h"
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#include <algorithm>
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#include <string>
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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/common_infer_shape_functions.h"
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namespace paddle {
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namespace operators {
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class BernoulliOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X",
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"A tensor with probabilities for generating the random binary "
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"number");
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AddOutput("Out", "A Tensor filled with random binary number");
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AddComment(R"DOC(
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This OP returns a Tensor filled with random binary(0 or 1) number from a Bernoulli distribution.
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Out ~ Bernoulli(X)
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)DOC");
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}
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};
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class BernoulliOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext *ctx) const override {
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return UnaryOpUnchangedInferShape(ctx);
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}
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};
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// It seems that Eigen::Tensor::random in GPU will SEGFAULT.
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// Use std::random and thrust::random(thrust is a std library in CUDA) to
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// implement uniform random.
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template <typename T>
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class BernoulliOpKernel<platform::CPUDeviceContext, 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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std::uniform_real_distribution<T> dist(0.0, 1.0);
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auto gen_ptr = framework::DefaultCPUGenerator();
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auto engine = gen_ptr->GetCPUEngine();
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for (int64_t i = 0; i < size; ++i) {
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out_data[i] = BernoulliFunctor(in_data[i], dist(*engine));
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}
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}
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}; // namespace operators
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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_OPERATOR(
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bernoulli, ops::BernoulliOp, ops::BernoulliOpMaker,
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paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
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paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>);
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REGISTER_OP_CPU_KERNEL(bernoulli,
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ops::BernoulliOpKernel<plat::CPUDeviceContext, float>,
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ops::BernoulliOpKernel<plat::CPUDeviceContext, double>);
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