gaussian_random_op.cc 3.0 KB
Newer Older
D
dongzhihong 已提交
1 2 3 4 5 6 7 8 9 10 11
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at
   http://www.apache.org/licenses/LICENSE-2.0
   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and
   limitations under the License. */

Q
qijun 已提交
12 13
#include <random>
#include "paddle/framework/op_registry.h"
D
dongzhihong 已提交
14 15 16

namespace paddle {
namespace operators {
D
dongzhihong 已提交
17

Q
qijun 已提交
18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41
template <typename T>
class CPUGaussianRandomKernel : public framework::OpKernel {
 public:
  void Compute(const framework::ExecutionContext& context) const override {
    float mean = context.op_.GetAttr<float>("mean");
    float std = context.op_.GetAttr<float>("std");
    auto* tensor = context.Output<framework::Tensor>("Out");
    T* data = tensor->mutable_data<T>(context.GetPlace());

    unsigned int seed =
        static_cast<unsigned int>(context.op_.GetAttr<int>("seed"));
    std::minstd_rand engine;
    if (seed == 0) {
      seed = std::random_device()();
    }
    engine.seed(seed);
    std::normal_distribution<T> dist(mean, std);
    ssize_t size = framework::product(tensor->dims());
    for (ssize_t i = 0; i < size; ++i) {
      data[i] = dist(engine);
    }
  }
};

D
dongzhihong 已提交
42
class GaussianRandomOp : public framework::OperatorWithKernel {
Y
Yu Yang 已提交
43 44
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;
45

D
dongzhihong 已提交
46
 protected:
47
  void InferShape(const framework::InferShapeContext& context) const override {
Q
qijun 已提交
48
    auto* tensor = context.Output<framework::Tensor>("Out");
49 50 51
    auto dims = GetAttr<std::vector<int>>("dims");
    PADDLE_ENFORCE(dims.size() > 0UL,
                   "dims can be one int or array. dims must be set.");
D
dongzhihong 已提交
52
    tensor->Resize(framework::make_ddim(dims));
D
dongzhihong 已提交
53 54 55
  }
};

D
dongzhihong 已提交
56
class GaussianRandomOpMaker : public framework::OpProtoAndCheckerMaker {
D
dongzhihong 已提交
57
 public:
D
dongzhihong 已提交
58 59
  GaussianRandomOpMaker(framework::OpProto* proto,
                        framework::OpAttrChecker* op_checker)
D
dongzhihong 已提交
60 61 62
      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
    AddOutput("Out", "output matrix of random op");
    AddComment(R"DOC(
63 64
GaussianRandom operator.
Use to initialize tensor with gaussian random generator.
D
dongzhihong 已提交
65
)DOC");
66 67

    AddAttr<std::vector<int>>("dims", "The dimension of random tensor.");
Q
qijun 已提交
68 69 70 71 72 73
    AddAttr<float>("mean", "mean of random tensor.").SetDefault(.0f);
    AddAttr<float>("std", "std of random tensor.").SetDefault(1.0f);
    AddAttr<int>("seed",
                 "Random seed of generator."
                 "0 means use system wide seed")
        .SetDefault(0);
D
dongzhihong 已提交
74 75 76 77 78 79
  }
};

}  // namespace operators
}  // namespace paddle

80
namespace ops = paddle::operators;
F
fengjiayi 已提交
81 82
REGISTER_OP_WITHOUT_GRADIENT(gaussian_random, ops::GaussianRandomOp,
                             ops::GaussianRandomOpMaker);
Q
qijun 已提交
83
REGISTER_OP_CPU_KERNEL(gaussian_random, ops::CPUGaussianRandomKernel<float>);