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98 lines
3.9 KiB
98 lines
3.9 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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WITHOpArgType::OUT WARRANTIES OR CONDITIONS OF ANY KOpArgType::IND, either
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express or implied. See the License for the specific language governing
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permissions and limitations under the License. */
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#include "paddle/framework/grad_op_builder.h"
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#include "paddle/framework/op_registry.h"
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namespace paddle {
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namespace framework {
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enum class OpArgType { IN, OUT };
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static void TransOpArg(const OperatorBase* src_op, const OpArgType& src_type,
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bool is_grad, VariableNameMap* vars) {
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const auto& src_inout =
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src_type == OpArgType::IN ? src_op->Inputs() : src_op->Outputs();
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auto& dst_inout = *vars;
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auto& proto = OpInfoMap::Instance().Get(src_op->Type()).Proto();
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const auto& src_arg_list =
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src_type == OpArgType::IN ? proto.inputs() : proto.outputs();
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for (const auto& arg : src_arg_list) {
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if (arg.not_in_gradient() && !is_grad) continue;
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const std::string src_name = arg.name();
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std::string dst_name = is_grad ? GradVarName(src_name) : src_name;
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dst_inout[dst_name].reserve(src_inout.at(src_name).size());
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for (auto& var_name : src_inout.at(src_name)) {
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std::string s = is_grad ? GradVarName(var_name) : var_name;
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dst_inout[dst_name].emplace_back(s);
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}
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}
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}
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OperatorBase* BuildGradOp(const OperatorBase* op) {
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auto& info = OpInfoMap::Instance().Get(op->Type());
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PADDLE_ENFORCE(info.HasGradientOp());
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VariableNameMap inputs;
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VariableNameMap outputs;
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TransOpArg(op, OpArgType::IN, false, &inputs); // I
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TransOpArg(op, OpArgType::OUT, false, &inputs); // O
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TransOpArg(op, OpArgType::OUT, true, &inputs); // OG
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TransOpArg(op, OpArgType::IN, true, &outputs); // IG
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auto& grad_info = OpInfoMap::Instance().Get(info.grad_op_type_);
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return grad_info.Creator()(info.grad_op_type_, inputs, outputs, op->Attrs());
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}
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static void TransOpDescArg(const OpDescBind* src_op, const OpArgType& src_type,
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bool is_grad, OpDescBind* dst_op,
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const OpArgType& dst_type) {
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PADDLE_ENFORCE(dst_op != nullptr,
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"Protobuf desc of gradient op must be initialized first.");
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const auto& proto = OpInfoMap::Instance().Get(src_op->Type()).Proto();
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const auto& src_arg_list =
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src_type == OpArgType::IN ? proto.inputs() : proto.outputs();
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for (const auto& arg : src_arg_list) {
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if (arg.not_in_gradient() && !is_grad) continue;
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const std::string src_name = arg.name();
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std::vector<std::string> vars = src_type == OpArgType::IN
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? src_op->Input(src_name)
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: src_op->Output(src_name);
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if (is_grad) {
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for (std::string& var : vars) {
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var = GradVarName(var);
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}
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}
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std::string dst_name = is_grad ? GradVarName(src_name) : src_name;
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dst_type == OpArgType::IN ? dst_op->SetInput(dst_name, vars)
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: dst_op->SetOutput(dst_name, vars);
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}
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}
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void CompleteGradOpDesc(const OpDescBind* forw_op, OpDescBind* grad_op) {
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auto& info = OpInfoMap::Instance().Get(forw_op->Type());
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PADDLE_ENFORCE(info.HasGradientOp());
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grad_op->SetType(info.grad_op_type_);
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TransOpDescArg(forw_op, OpArgType::IN, false, grad_op, OpArgType::IN);
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TransOpDescArg(forw_op, OpArgType::OUT, false, grad_op, OpArgType::IN);
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TransOpDescArg(forw_op, OpArgType::OUT, true, grad_op, OpArgType::IN);
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TransOpDescArg(forw_op, OpArgType::IN, true, grad_op, OpArgType::OUT);
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grad_op->SetAttrMap(forw_op->GetAttrMap());
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}
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} // namespace framework
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} // namespace paddle
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