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84 lines
3.0 KiB
84 lines
3.0 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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 <random>
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#include "paddle/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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template <typename T>
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class CPUGaussianRandomKernel : public framework::OpKernel {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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float mean = context.op().GetAttr<float>("mean");
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float std = context.op().GetAttr<float>("std");
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auto* tensor = context.Output<framework::Tensor>("Out");
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T* data = tensor->mutable_data<T>(context.GetPlace());
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unsigned int seed =
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static_cast<unsigned int>(context.op().GetAttr<int>("seed"));
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std::minstd_rand engine;
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if (seed == 0) {
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seed = std::random_device()();
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}
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engine.seed(seed);
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std::normal_distribution<T> dist(mean, std);
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ssize_t size = framework::product(tensor->dims());
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for (ssize_t i = 0; i < size; ++i) {
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data[i] = dist(engine);
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}
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}
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};
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class GaussianRandomOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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void InferShape(const framework::InferShapeContext& context) const override {
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auto* tensor = context.Output<framework::Tensor>("Out");
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auto dims = GetAttr<std::vector<int>>("dims");
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PADDLE_ENFORCE(dims.size() > 0UL,
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"dims can be one int or array. dims must be set.");
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tensor->Resize(framework::make_ddim(dims));
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}
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};
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class GaussianRandomOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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GaussianRandomOpMaker(framework::OpProto* proto,
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framework::OpAttrChecker* op_checker)
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: framework::OpProtoAndCheckerMaker(proto, op_checker) {
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AddOutput("Out", "output matrix of random op");
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AddComment(R"DOC(
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GaussianRandom operator.
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Use to initialize tensor with gaussian random generator.
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)DOC");
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AddAttr<std::vector<int>>("dims", "The dimension of random tensor.");
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AddAttr<float>("mean", "mean of random tensor.").SetDefault(.0f);
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AddAttr<float>("std", "std of random tensor.").SetDefault(1.0f);
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AddAttr<int>("seed",
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"Random seed of generator."
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"0 means use system wide seed")
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.SetDefault(0);
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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_WITHOUT_GRADIENT(gaussian_random, ops::GaussianRandomOp,
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ops::GaussianRandomOpMaker);
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REGISTER_OP_CPU_KERNEL(gaussian_random, ops::CPUGaussianRandomKernel<float>);
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