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60 lines
2.1 KiB
60 lines
2.1 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 "paddle/operators/gaussian_random_op.h"
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namespace paddle {
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namespace operators {
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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>(0);
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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 value of random.").SetDefault(.0f);
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AddAttr<float>("std", "minimum value of random value.").SetDefault(1.0f);
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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(
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gaussian_random,
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ops::GaussianRandomKernel<paddle::platform::CPUPlace, float>);
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