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Eagerly drop local scope in iteration #9838
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Original file line number | Diff line number | Diff line change |
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@@ -15,6 +15,7 @@ limitations under the License. */ | |
#include "paddle/fluid/framework/parallel_executor.h" | ||
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#include <string> | ||
#include <tuple> | ||
#include <vector> | ||
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#ifdef PADDLE_WITH_CUDA | ||
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@@ -41,6 +42,8 @@ class ParallelExecutorPrivate { | |
#ifdef PADDLE_WITH_CUDA | ||
std::unique_ptr<platform::NCCLContextMap> nccl_ctxs_; | ||
#endif | ||
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std::vector<std::tuple<std::string, proto::VarType::Type, bool>> var_types_; | ||
}; | ||
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std::vector<Scope *> &ParallelExecutor::GetLocalScopes() { | ||
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@@ -97,14 +100,9 @@ ParallelExecutor::ParallelExecutor( | |
allow_op_delay)); | ||
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// Step 3. Create vars in each scope; | ||
for (auto *scope : member_->local_scopes_) { | ||
for (auto *var : main_program.Block(0).AllVars()) { | ||
if (scope->FindVar(var->Name()) != nullptr) { | ||
continue; | ||
} | ||
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InitializeVariable(scope->Var(var->Name()), var->GetType()); | ||
} | ||
for (auto *var : main_program.Block(0).AllVars()) { | ||
member_->var_types_.emplace_back(var->Name(), var->GetType(), | ||
var->Persistable()); | ||
} | ||
} | ||
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@@ -163,9 +161,42 @@ void ParallelExecutor::Run( | |
const std::unordered_map<std::string, LoDTensor> &feed_tensors) { | ||
platform::RecordBlock b(0); | ||
SplitTensorToPlaces(feed_tensors); | ||
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// Create local scopes. | ||
for (auto &scope : member_->local_scopes_) { | ||
Scope &local_scope = scope->NewScope(); | ||
*scope->Var(details::kLocalExecScopeName)->GetMutable<Scope *>() = | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. What is usefule of There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Currently, all non-persistable variables will be in the 'sub-scope of local scope'. The sub-scope is created before batch training and deleted after batch training. |
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&local_scope; | ||
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for (auto &name_type_pair : member_->var_types_) { | ||
if (scope->FindVar(std::get<0>(name_type_pair)) != nullptr) { | ||
continue; | ||
} | ||
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if (std::get<2>(name_type_pair)) { // Persistable | ||
InitializeVariable(scope->Var(std::get<0>(name_type_pair)), | ||
std::get<1>(name_type_pair)); | ||
} else { | ||
InitializeVariable(scope->Var(std::get<0>(name_type_pair)), | ||
std::get<1>(name_type_pair)); | ||
} | ||
} | ||
} | ||
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auto fetch_data = member_->executor_->Run(fetch_tensors); | ||
*member_->global_scope_->Var(fetched_var_name)->GetMutable<FeedFetchList>() = | ||
fetch_data; | ||
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// Wait All computational streams | ||
for (auto p : member_->places_) { | ||
platform::DeviceContextPool::Instance().Get(p)->Wait(); | ||
} | ||
for (auto &scope : member_->local_scopes_) { | ||
auto &local_scope = | ||
*scope->Var(details::kLocalExecScopeName)->GetMutable<Scope *>(); | ||
scope->DeleteScope(local_scope); | ||
local_scope = nullptr; | ||
} | ||
} | ||
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void ParallelExecutor::SplitTensorToPlaces( | ||
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Is this used to fetch the variable in the local scope?