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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,178 @@ | ||
| /* 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. */ | ||
|
|
||
| #include "paddle/framework/backward.h" | ||
| #include <list> | ||
| #include "paddle/framework/net.h" | ||
| #include "paddle/framework/op_registry.h" | ||
|
|
||
| namespace paddle { | ||
| namespace framework { | ||
|
|
||
| static bool AllInSet(const std::vector<std::string>& names, | ||
| const std::string& suffix, | ||
| const std::unordered_set<std::string>& set) { | ||
| for (auto& name : names) { | ||
| if (set.find(name + suffix) == set.end()) { | ||
| return false; | ||
| } | ||
| } | ||
| return true; | ||
| } | ||
|
|
||
| static std::shared_ptr<OperatorBase> NOP() { | ||
| auto net_op = std::make_shared<NetOp>(); | ||
| net_op->type_ = "@NOP@"; | ||
| net_op->CompleteAddOp(); | ||
| return net_op; | ||
| } | ||
|
|
||
| // Get backward operator from a forward operator, recursively implementation. | ||
| // | ||
| // no_grad_names the gradient variable names without gradient calculating. | ||
| // | ||
| // uniq_id is a unique index used inside recursively calling BackwardRecursive. | ||
| // use `uid = uniq_id++;` to get the unique index, and pass `uniq_id` through | ||
| // recursive calling. | ||
| // | ||
| // returns The backward operator. For simple situation, it is a simple | ||
| // operator. For complex situation, it is a NetOp. | ||
| // | ||
| // See Backward.h for details | ||
| static std::shared_ptr<OperatorBase> BackwardRecursive( | ||
| const OperatorBase& forwardOp, | ||
| std::unordered_set<std::string>& no_grad_names, size_t& uniq_id); | ||
| std::shared_ptr<OperatorBase> BackwardRecursive( | ||
| const OperatorBase& forwardOp, | ||
| std::unordered_set<std::string>& no_grad_names, size_t& uniq_id) { | ||
| // If all input gradients of forwarding operator do not need to calculate, | ||
| // just return an NOP. Not return null ptr because NOP does not take | ||
| // too much time for calculation, but it is useful for simplifying logic. | ||
| if (AllInSet(forwardOp.inputs_, OperatorBase::GRAD_VAR_SUFFIX(), | ||
| no_grad_names)) { | ||
| return NOP(); | ||
| } | ||
|
|
||
| // All output gradients of forwarding operator do not need to calculate. Then | ||
| // all input gradients cannot be computed at all, and we put them into | ||
| // `no_grad_names` set. Return an NOP. | ||
| if (AllInSet(forwardOp.outputs_, OperatorBase::GRAD_VAR_SUFFIX(), | ||
| no_grad_names)) { | ||
| for (auto& name : forwardOp.inputs_) { | ||
| // Mark all input is not need | ||
| no_grad_names.insert(name + OperatorBase::GRAD_VAR_SUFFIX()); | ||
| } | ||
| return NOP(); | ||
| } | ||
|
|
||
| // Returned gradient network | ||
| auto net = std::make_shared<NetOp>(); | ||
|
|
||
| if (forwardOp.IsNetOp()) { | ||
| // Because forwardOp is a net op, it can static_cast. | ||
| auto& forwardNet = static_cast<const NetOp&>(forwardOp); | ||
|
|
||
| // Map from output gradient variable name to operator's indices in backward | ||
| // net. That operator generates that variable. | ||
| std::unordered_map<std::string, std::vector<size_t>> dup_output_ops; | ||
|
|
||
| size_t local_op_id = 0; | ||
| // reversely travel forwardNet | ||
| for (auto it = forwardNet.ops_.rbegin(); it != forwardNet.ops_.rend(); | ||
| ++it, ++local_op_id) { | ||
| auto fwd = *it; | ||
| auto bwd = BackwardRecursive(*fwd, no_grad_names, uniq_id); | ||
| net->AddOp(bwd); | ||
| for (auto& out : bwd->outputs_) { | ||
| dup_output_ops[out].emplace_back(local_op_id); | ||
| } | ||
| } | ||
| // Get unique ID for this method. | ||
| auto uid = uniq_id++; | ||
| // TODO(dzh): more comment | ||
| using Pos = std::pair<size_t, std::shared_ptr<OperatorBase>>; | ||
| std::list<Pos> insert_position; | ||
| for (auto& dup_output_op : dup_output_ops) { | ||
| const std::string& name = dup_output_op.first; | ||
| auto& dup_op = dup_output_op.second; | ||
| if (dup_op.size() == 1) continue; | ||
| std::vector<std::string> dup_outputs; | ||
|
|
||
| for (size_t i = 0; i < dup_op.size(); ++i) { | ||
| auto op_offset = dup_op[i]; | ||
| dup_outputs.push_back(name + "@RENAME@" + std::to_string(uid) + "@" + | ||
| std::to_string(i)); | ||
| net->ops_[op_offset]->Rename(name, dup_outputs.back()); | ||
| } | ||
| insert_position.push_back( | ||
| {dup_op.back(), | ||
| OpRegistry::CreateOp( | ||
| "add", {dup_outputs}, {name}, | ||
| {{"input_format", | ||
| std::vector<int>{0, static_cast<int>(dup_outputs.size())}}})}); | ||
| } | ||
|
|
||
| insert_position.sort( | ||
| [](const Pos& l, const Pos& r) { return l.first > r.first; }); | ||
|
|
||
| for (auto& pos : insert_position) { | ||
| net->InsertOp(pos.first + 1, pos.second); | ||
| } | ||
|
|
||
| } else { | ||
| std::shared_ptr<OperatorBase> grad_op = OpRegistry::CreateGradOp(forwardOp); | ||
| for (std::string& grad_input : grad_op->inputs_) { | ||
| if (no_grad_names.count(grad_input)) { | ||
| std::string prefix = grad_input.substr( | ||
| 0, grad_input.size() - OperatorBase::GRAD_VAR_SUFFIX().size()); | ||
| grad_input = prefix + OperatorBase::ZERO_VAR_SUFFIX(); | ||
|
|
||
| // If part of input gradient of that operator is not calculated, fill | ||
| // zero variables to that input gradient. | ||
| net->AddOp(OpRegistry::CreateOp("fill_zeros_like", {prefix}, | ||
| {grad_input}, {})); | ||
| } | ||
| } | ||
|
|
||
| for (std::string& grad_output : grad_op->outputs_) { | ||
| if (no_grad_names.count(grad_output)) { | ||
| grad_output = OperatorBase::EMPTY_VAR_NAME(); | ||
| } | ||
| } | ||
|
|
||
| if (net->ops_.empty()) { // Current no aux op is added to network | ||
| return grad_op; | ||
| } | ||
| net->AddOp(grad_op); | ||
| } | ||
| net->type_ = "@GENERATED_BACKWARD@"; | ||
| net->CompleteAddOp(); | ||
| return net; | ||
| } | ||
|
|
||
| // See header for comments | ||
| std::shared_ptr<OperatorBase> Backward( | ||
| const OperatorBase& forwardOp, | ||
| const std::unordered_set<std::string>& no_grad_vars) { | ||
| std::unordered_set<std::string> no_grad_names; | ||
| no_grad_names.reserve(no_grad_vars.size()); | ||
|
|
||
| for (auto& name : no_grad_vars) { | ||
| no_grad_names.insert(name + OperatorBase::GRAD_VAR_SUFFIX()); | ||
| } | ||
| size_t uid = 0; | ||
| return BackwardRecursive(forwardOp, no_grad_names, uid); | ||
| } | ||
| } // namespace framework | ||
| } // namespace paddle |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,27 @@ | ||
| /* 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. */ | ||
|
|
||
| #pragma once | ||
| #include <unordered_set> | ||
| #include "operator.h" | ||
| namespace paddle { | ||
| namespace framework { | ||
|
|
||
| // Create the backward operator from a forward operator. | ||
| // TODO(yuyang18): Add more API reference comment. | ||
| extern std::shared_ptr<OperatorBase> Backward( | ||
| const OperatorBase& forwardOp, | ||
| const std::unordered_set<std::string>& no_grad_vars); | ||
| } // namespace framework | ||
| } // namespace paddle |
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