You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
136 lines
4.7 KiB
136 lines
4.7 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
|
|
|
|
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. */
|
|
|
|
#include <random>
|
|
#include "paddle/fluid/framework/op_registry.h"
|
|
|
|
#ifdef PADDLE_WITH_MKLDNN
|
|
#include "paddle/fluid/platform/mkldnn_helper.h"
|
|
#endif
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
template <typename T>
|
|
class CPUGaussianRandomKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& context) const override {
|
|
float mean = context.Attr<float>("mean");
|
|
float std = context.Attr<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.Attr<int>("seed"));
|
|
std::minstd_rand engine;
|
|
if (seed == 0) {
|
|
seed = std::random_device()();
|
|
}
|
|
engine.seed(seed);
|
|
std::normal_distribution<T> dist(mean, std);
|
|
int64_t size = tensor->numel();
|
|
for (int64_t i = 0; i < size; ++i) {
|
|
data[i] = dist(engine);
|
|
}
|
|
}
|
|
};
|
|
|
|
class GaussianRandomOp : public framework::OperatorWithKernel {
|
|
public:
|
|
using framework::OperatorWithKernel::OperatorWithKernel;
|
|
|
|
void InferShape(framework::InferShapeContext* ctx) const override {
|
|
PADDLE_ENFORCE(ctx->HasOutput("Out"),
|
|
"Output(Out) of GaussianRandomOp should not be null.");
|
|
auto shape = ctx->Attrs().Get<std::vector<int>>("shape");
|
|
std::vector<int64_t> temp;
|
|
temp.reserve(shape.size());
|
|
for (auto dim : shape) {
|
|
temp.push_back(static_cast<int64_t>(dim));
|
|
}
|
|
PADDLE_ENFORCE(shape.size() > 0UL,
|
|
"shape can be one int or array. shape must be set.");
|
|
ctx->SetOutputDim("Out", framework::make_ddim(temp));
|
|
}
|
|
|
|
protected:
|
|
framework::OpKernelType GetExpectedKernelType(
|
|
const framework::ExecutionContext& ctx) const override {
|
|
framework::LibraryType library{framework::LibraryType::kPlain};
|
|
framework::DataLayout layout{framework::DataLayout::kAnyLayout};
|
|
|
|
#ifdef PADDLE_WITH_MKLDNN
|
|
if (library == framework::LibraryType::kPlain &&
|
|
platform::CanMKLDNNBeUsed(ctx)) {
|
|
library = framework::LibraryType::kMKLDNN;
|
|
layout = framework::DataLayout::kMKLDNN;
|
|
}
|
|
#endif
|
|
|
|
return framework::OpKernelType(
|
|
static_cast<framework::proto::VarType::Type>(ctx.Attr<int>("dtype")),
|
|
ctx.device_context(), layout, library);
|
|
}
|
|
};
|
|
|
|
class GaussianRandomOpMaker : public framework::OpProtoAndCheckerMaker {
|
|
public:
|
|
void Make() override {
|
|
AddOutput("Out", "Output matrix of gaussian random op");
|
|
|
|
AddAttr<std::vector<int>>("shape",
|
|
"(vector<int>) "
|
|
"The dimension of random tensor.");
|
|
AddAttr<float>("mean",
|
|
"(float, default 0.0) "
|
|
"mean of random tensor.")
|
|
.SetDefault(.0f);
|
|
AddAttr<float>("std",
|
|
"(float, default 1.0) "
|
|
"std of random tensor.")
|
|
.SetDefault(1.0f);
|
|
AddAttr<int>("seed",
|
|
"(int, default 0) "
|
|
"Random seed of generator."
|
|
"0 means use system wide seed."
|
|
"Note that if seed is not 0, this operator will always "
|
|
"generate the same random numbers every time.")
|
|
.SetDefault(0);
|
|
AddAttr<int>("dtype",
|
|
"(int, default 5(FP32)) "
|
|
"Output data type.")
|
|
.SetDefault(framework::proto::VarType::FP32);
|
|
AddAttr<bool>("use_mkldnn",
|
|
"(bool, default false) Only used in mkldnn kernel")
|
|
.SetDefault(false);
|
|
AddComment(R"DOC(
|
|
GaussianRandom Operator.
|
|
|
|
Used to initialize tensors with gaussian random generator.
|
|
|
|
)DOC");
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|
|
|
|
namespace ops = paddle::operators;
|
|
REGISTER_OP_WITHOUT_GRADIENT(gaussian_random, ops::GaussianRandomOp,
|
|
ops::GaussianRandomOpMaker);
|
|
REGISTER_OP_CPU_KERNEL(gaussian_random, ops::CPUGaussianRandomKernel<float>,
|
|
ops::CPUGaussianRandomKernel<double>);
|
|
REGISTER_OP_CPU_KERNEL(gaussian_random_batch_size_like,
|
|
ops::CPUGaussianRandomKernel<float>,
|
|
ops::CPUGaussianRandomKernel<double>);
|