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117 lines
4.1 KiB
117 lines
4.1 KiB
/* Copyright (c) 2016 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/framework/data_type.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/detail/safe_ref.h"
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#include "paddle/fluid/platform/device_context.h"
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namespace paddle {
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namespace operators {
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struct FillOpVisitor {
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FillOpVisitor(framework::LoDTensor *tensor, const std::vector<float> &value)
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: tensor_(tensor), value_(value) {}
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template <typename T>
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void operator()() const {
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platform::CPUPlace cpu;
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auto *data = tensor_->mutable_data<T>(cpu);
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std::transform(value_.data(), value_.data() + tensor_->numel(), data,
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[](float dat) { return static_cast<T>(dat); });
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}
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framework::LoDTensor *tensor_;
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const std::vector<float> &value_;
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};
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class FillOp : public framework::OperatorBase {
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public:
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FillOp(const std::string &type, const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: OperatorBase(type, inputs, outputs, attrs) {}
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private:
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void RunImpl(const framework::Scope &scope,
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const platform::Place &place) const override {
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auto &out =
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detail::Ref(detail::Ref(scope.FindVar(Output("Out")),
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"Cannot find variable %s", Output("Out"))
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.GetMutable<framework::LoDTensor>());
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out.Resize(framework::make_ddim(Attr<std::vector<int>>("shape")));
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auto dtype = static_cast<framework::proto::DataType>(Attr<int>("dtype"));
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platform::CPUPlace cpu;
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auto force_cpu = Attr<bool>("force_cpu");
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out.mutable_data(force_cpu ? cpu : place, framework::ToTypeIndex(dtype));
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framework::LoDTensor tensor;
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if (force_cpu || platform::is_cpu_place(place)) {
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tensor.ShareDataWith(out);
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} else {
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// Always make tensor in CPU memory.
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tensor.Resize(out.dims());
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tensor.mutable_data(cpu, framework::ToTypeIndex(dtype));
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}
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framework::VisitDataType(
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dtype, FillOpVisitor(&tensor, Attr<std::vector<float>>("value")));
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if (!force_cpu && platform::is_gpu_place(place)) {
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// Copy tensor to out
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platform::DeviceContextPool &pool =
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platform::DeviceContextPool::Instance();
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auto &dev_ctx = *pool.Get(place);
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framework::TensorCopy(tensor, place, dev_ctx, &out);
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}
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}
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};
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class FillOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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FillOpMaker(OpProto *proto, OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddComment(R"DOC(Fill operator
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Fill an tensor with `value` and `shape`. The type of the tensor is specify by
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`dtype`.
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)DOC");
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AddOutput("Out", "(LoDTensor) The output tensor.");
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AddAttr<std::vector<float>>(
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"value", "The float values of tensor, which are flatten in row major");
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AddAttr<std::vector<int>>("shape", "The shape of output tensor");
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AddAttr<int>("dtype", "The data type of output tensor, Default is float")
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.SetDefault(framework::proto::DataType::FP32);
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AddAttr<bool>("force_cpu",
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"Whether the output tensor must be at CPU memory or not. "
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"Default is false.")
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.SetDefault(false);
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}
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};
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class FillOpInferShape : public framework::InferShapeBase {
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public:
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void operator()(framework::InferShapeContext *context) const override {
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context->SetOutputDim(
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"Out",
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framework::make_ddim(context->Attrs().Get<std::vector<int>>("shape")));
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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_OPERATOR(fill, ops::FillOp, ops::FillOpInferShape, ops::FillOpMaker);
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