提交 f4851f14 编写于 作者: C chengduoZH

clean code

上级 22ab14c5
......@@ -14,8 +14,6 @@
#include "paddle/fluid/framework/details/threaded_ssa_graph_executor.h"
#include "paddle/fluid/framework/details/fetch_op_handle.h"
namespace paddle {
namespace framework {
namespace details {
......@@ -45,73 +43,33 @@ FeedFetchList ThreadedSSAGraphExecutor::Run(
// Should revisit it if overlapping is available.
std::unordered_set<OpHandleBase *> delayed_ops;
auto InsertPendingVar = [&pending_vars, &ready_vars](VarHandleBase &var) {
pending_vars.insert(&var);
if (var.generated_op_ == nullptr) {
ready_vars.Push(&var);
}
};
auto InsertPendingOp = [&pending_ops](OpHandleBase &op_instance) {
pending_ops.insert({&op_instance, op_instance.Inputs().size()});
};
// Transform SSAGraph to pending_ops & pending_vars
for (auto &var_map : graph_->vars_) {
for (auto &name_pair : var_map) {
for (auto &version_pair : name_pair.second) {
InsertPendingVar(*version_pair);
InsertPendingVar(&pending_vars, &ready_vars, version_pair.get());
}
}
}
for (auto &var : graph_->dep_vars_) {
InsertPendingVar(*var);
InsertPendingVar(&pending_vars, &ready_vars, var.get());
}
for (auto &op : graph_->ops_) {
if (op->Inputs().empty()) { // Special case, Op has no input.
ready_ops.insert(op.get());
} else {
InsertPendingOp(*op);
InsertPendingOp(&pending_ops, op.get());
}
}
// Step 2. Insert FetchOps
std::vector<std::unique_ptr<FetchOpHandle>> fetch_ops;
FeedFetchList fetch_data(fetch_tensors.size());
std::unordered_map<std::string, std::vector<VarHandleBase *>> fetched_vars;
for (auto &fetch_var_name : fetch_tensors) {
for (auto &var_map : graph_->vars_) {
auto it = var_map.find(fetch_var_name);
if (it != var_map.end()) {
fetched_vars[fetch_var_name].push_back(it->second.rbegin()->get());
}
}
}
std::unordered_set<std::unique_ptr<VarHandleBase>> fetch_dependencies;
for (size_t i = 0; i < fetch_tensors.size(); ++i) {
auto &var_name = fetch_tensors[i];
auto &vars = fetched_vars.at(var_name);
auto *op = new FetchOpHandle(&fetch_data, i, &local_scopes_);
fetch_ops.emplace_back(op);
for (auto &p : places_) {
op->SetDeviceContext(p, fetch_ctxs_.Get(p));
}
for (auto *var : vars) {
op->AddInput(var);
}
FeedFetchList fetch_data(fetch_tensors.size());
auto *fetch_dummy = new DummyVarHandle();
op->AddOutput(fetch_dummy);
fetch_dependencies.emplace(fetch_dummy);
InsertPendingVar(*fetch_dummy);
InsertPendingOp(*op);
}
InsertFetchOps(fetch_tensors, &fetch_ops, &fetch_dependencies, &pending_ops,
&pending_vars, &ready_vars, &fetch_data);
auto run_all_ops = [&](std::unordered_set<OpHandleBase *> &set) {
for (auto *op : set) {
......@@ -174,6 +132,60 @@ FeedFetchList ThreadedSSAGraphExecutor::Run(
return fetch_data;
}
void ThreadedSSAGraphExecutor::InsertFetchOps(
const std::vector<std::string> &fetch_tensors,
std::vector<std::unique_ptr<FetchOpHandle>> *fetch_ops,
std::unordered_set<std::unique_ptr<VarHandleBase>> *fetch_dependencies,
std::unordered_map<OpHandleBase *, size_t> *pending_ops,
std::unordered_set<VarHandleBase *> *pending_vars,
BlockingQueue<VarHandleBase *> *ready_vars, FeedFetchList *fetch_data) {
std::unordered_map<std::string, std::vector<VarHandleBase *>> fetched_vars;
for (auto &fetch_var_name : fetch_tensors) {
for (auto &var_map : graph_->vars_) {
auto it = var_map.find(fetch_var_name);
if (it != var_map.end()) {
fetched_vars[fetch_var_name].push_back(it->second.rbegin()->get());
}
}
}
for (size_t i = 0; i < fetch_tensors.size(); ++i) {
auto &var_name = fetch_tensors[i];
auto &vars = fetched_vars.at(var_name);
auto *op = new FetchOpHandle(fetch_data, i, &local_scopes_);
fetch_ops->emplace_back(op);
for (auto &p : places_) {
op->SetDeviceContext(p, fetch_ctxs_.Get(p));
}
for (auto *var : vars) {
op->AddInput(var);
}
auto *fetch_dummy = new DummyVarHandle();
op->AddOutput(fetch_dummy);
fetch_dependencies->emplace(fetch_dummy);
this->InsertPendingVar(pending_vars, ready_vars, fetch_dummy);
this->InsertPendingOp(pending_ops, op);
}
}
void ThreadedSSAGraphExecutor::InsertPendingOp(
std::unordered_map<OpHandleBase *, size_t> *pending_ops,
OpHandleBase *op_instance) const {
pending_ops->insert({op_instance, op_instance->Inputs().size()});
}
void ThreadedSSAGraphExecutor::InsertPendingVar(
std::unordered_set<VarHandleBase *> *pending_vars,
BlockingQueue<VarHandleBase *> *ready_vars, VarHandleBase *var) const {
pending_vars->insert(var);
if (var->generated_op_ == nullptr) {
ready_vars->Push(var);
}
}
void ThreadedSSAGraphExecutor::RunOp(
BlockingQueue<VarHandleBase *> *ready_var_q, details::OpHandleBase *op) {
auto op_run = [ready_var_q, op, this] {
......
......@@ -23,6 +23,7 @@
#include <functional>
#include "ThreadPool.h" // ThreadPool in thrird party
#include "paddle/fluid/framework/blocking_queue.h"
#include "paddle/fluid/framework/details/fetch_op_handle.h"
#include "paddle/fluid/framework/details/ssa_graph_executor.h"
namespace paddle {
......@@ -58,6 +59,21 @@ class ThreadedSSAGraphExecutor : public SSAGraphExecutor {
std::unique_ptr<platform::EnforceNotMet> exception_;
std::atomic<int> running_ops_;
bool allow_op_delay_;
void InsertPendingOp(std::unordered_map<OpHandleBase *, size_t> *pending_ops,
OpHandleBase *op_instance) const;
void InsertPendingVar(std::unordered_set<VarHandleBase *> *pending_vars,
BlockingQueue<VarHandleBase *> *ready_vars,
VarHandleBase *var) const;
void InsertFetchOps(
const std::vector<std::string> &fetch_tensors,
std::vector<std::unique_ptr<FetchOpHandle>> *fetch_ops,
std::unordered_set<std::unique_ptr<VarHandleBase>> *fetch_dependencies,
std::unordered_map<OpHandleBase *, size_t> *pending_ops,
std::unordered_set<VarHandleBase *> *pending_vars,
BlockingQueue<VarHandleBase *> *ready_vars, FeedFetchList *fetch_data);
};
} // namespace details
......
......@@ -721,3 +721,7 @@ class TestCRFModel(unittest.TestCase):
def test_update_dense_parameter(self):
self.check_network_convergence(is_sparse=False)
if __name__ == '__main__':
unittest.main()
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