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144 lines
4.8 KiB
144 lines
4.8 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/framework/data_type.h"
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#include "paddle/framework/op_registry.h"
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#include "paddle/framework/var_type.h"
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#include "paddle/platform/device_context.h"
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namespace paddle {
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namespace operators {
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class AssignFunctor {
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public:
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AssignFunctor(framework::Variable *out,
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const platform::DeviceContext &dev_ctx)
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: out_(out), dev_ctx_(dev_ctx) {}
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void operator()(const framework::LoDTensor &lod_tensor) const {
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auto &out_tensor = *out_->GetMutable<framework::LoDTensor>();
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copy_tensor(lod_tensor, &out_tensor);
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}
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void operator()(const framework::LoDTensorArray &array) const {
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auto &out_array = *out_->GetMutable<framework::LoDTensorArray>();
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out_array.resize(array.size());
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for (size_t i = 0; i < array.size(); ++i) {
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copy_tensor(array[i], &out_array[i]);
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}
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}
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void operator()(const framework::SelectedRows &rows) const {
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framework::SelectedRows &out_rows =
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*out_->GetMutable<framework::SelectedRows>();
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out_rows.set_rows(rows.rows());
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out_rows.set_height(rows.height());
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auto &t = rows.value();
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auto *m = out_rows.mutable_value();
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framework::Copy(t, t.place(), dev_ctx_, m);
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}
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template <typename T>
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void operator()(const T &v) const {
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PADDLE_THROW("Not support type for assign op %s", typeid(T).name());
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}
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private:
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void copy_tensor(const framework::LoDTensor &lod_tensor,
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framework::LoDTensor *out) const {
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auto &out_tensor = *out;
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Copy(lod_tensor, lod_tensor.place(), dev_ctx_, &out_tensor);
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out_tensor.set_lod(lod_tensor.lod());
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}
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framework::Variable *out_;
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const platform::DeviceContext &dev_ctx_;
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};
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class AssignOp : public framework::OperatorBase {
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public:
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AssignOp(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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void Run(const framework::Scope &scope,
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const platform::Place &place) const override {
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auto *x = scope.FindVar(Input("X"));
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if (x == nullptr) {
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return;
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}
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auto *out = scope.FindVar(Output("Out"));
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PADDLE_ENFORCE(
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out != nullptr,
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"The Output(Out) should not be null if the Input(X) is set.");
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platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
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auto &dev_ctx = *pool.Get(place);
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framework::VisitVarType(*x, AssignFunctor(out, dev_ctx));
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}
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};
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class AssignOpProtoMaker : public framework::OpProtoAndCheckerMaker {
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public:
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AssignOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X",
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"(LoDTensor, SelectedRows or LoDTensorArray) The input variable "
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"could be LoDTensor, SelectedRows or LoDTensorArray.")
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.AsDispensable();
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AddOutput("Out",
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"(LoDTensor, SelectedRows or LoDTensorArray) The type of output "
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"is the same as input X.");
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AddComment(R"DOC(Assign Operator
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Out = X, when type in [LoDTensor/SelectedRows/LoDTensorArray]
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raise error if the type is not listed above.
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)DOC");
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}
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};
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class AssignInferShape : public framework::InferShapeBase {
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public:
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void operator()(framework::InferShapeContext *context) const override {
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if (context->HasInput("X")) {
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auto type = context->GetInputsVarType("X")[0];
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if (type == framework::proto::VarDesc_VarType_SELECTED_ROWS ||
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type == framework::proto::VarDesc_VarType_LOD_TENSOR) {
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context->SetOutputDim("Out", context->GetInputDim("X"));
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}
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}
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}
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};
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class AssignGradMaker : public framework::SingleGradOpDescMaker {
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public:
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using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
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protected:
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std::unique_ptr<framework::OpDesc> Apply() const override {
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auto *op = new framework::OpDesc();
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op->SetType("assign");
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op->SetInput("X", OutputGrad("Out"));
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op->SetOutput("Out", InputGrad("X"));
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return std::unique_ptr<framework::OpDesc>(op);
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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(assign, ops::AssignOp, ops::AssignGradMaker,
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ops::AssignInferShape, ops::AssignOpProtoMaker);
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