提交 3abb2aa0 编写于 作者: M minqiyang

Refine MultiDevSSAGraph

test=release/1.2
上级 553df9d3
...@@ -45,7 +45,7 @@ class MultiDevSSAGraphBuilder : public ir::Pass { ...@@ -45,7 +45,7 @@ class MultiDevSSAGraphBuilder : public ir::Pass {
#endif #endif
int GetVarDeviceID( int GetVarDeviceID(
const ir::Graph &graph, const std::string &varname, const std::string &varname,
const std::unordered_map<std::string, int> &sharded_var_device) const; const std::unordered_map<std::string, int> &sharded_var_device) const;
bool IsScaleLossOp(ir::Node *node) const; bool IsScaleLossOp(ir::Node *node) const;
...@@ -57,12 +57,6 @@ class MultiDevSSAGraphBuilder : public ir::Pass { ...@@ -57,12 +57,6 @@ class MultiDevSSAGraphBuilder : public ir::Pass {
ir::Graph *result, ir::Node *node, ir::Graph *result, ir::Node *node,
std::unordered_map<std::string, int> *sharded_var_device) const; std::unordered_map<std::string, int> *sharded_var_device) const;
std::vector<std::string> FindDistTrainSendVars(
const std::vector<ir::Node *> &nodes) const;
std::vector<std::string> FindDistTrainRecvVars(
const std::vector<ir::Node *> &nodes) const;
void CreateComputationalOps(ir::Graph *result, ir::Node *node, void CreateComputationalOps(ir::Graph *result, ir::Node *node,
size_t num_places) const; size_t num_places) const;
...@@ -76,7 +70,7 @@ class MultiDevSSAGraphBuilder : public ir::Pass { ...@@ -76,7 +70,7 @@ class MultiDevSSAGraphBuilder : public ir::Pass {
int dev_id) const; int dev_id) const;
int GetOpDeviceID( int GetOpDeviceID(
const ir::Graph &graph, ir::Node *node, ir::Node *node,
const std::unordered_map<std::string, int> &sharded_var_device) const; const std::unordered_map<std::string, int> &sharded_var_device) const;
void InsertAllReduceOp(ir::Graph *result, const std::string &og) const; void InsertAllReduceOp(ir::Graph *result, const std::string &og) const;
...@@ -99,6 +93,15 @@ class MultiDevSSAGraphBuilder : public ir::Pass { ...@@ -99,6 +93,15 @@ class MultiDevSSAGraphBuilder : public ir::Pass {
void SetCommunicationContext(OpHandleBase *op_handle, void SetCommunicationContext(OpHandleBase *op_handle,
const platform::Place &p) const; const platform::Place &p) const;
std::vector<ir::Node *> SortForReduceMode(
const std::vector<ir::Node *> &) const;
int GetOpDeviceID(
ir::Node *node,
const std::unordered_map<std::string, int> &shared_var_device,
std::unordered_map<std::string, std::vector<ir::Node *>> *delay_ops)
const;
mutable std::string loss_var_name_; mutable std::string loss_var_name_;
mutable std::vector<platform::Place> places_; mutable std::vector<platform::Place> places_;
mutable std::vector<Scope *> local_scopes_; mutable std::vector<Scope *> local_scopes_;
......
...@@ -23,67 +23,8 @@ limitations under the License. */ ...@@ -23,67 +23,8 @@ limitations under the License. */
namespace paddle { namespace paddle {
namespace framework { namespace framework {
namespace ir { namespace ir {
namespace {
void CheckProgram(const ProgramDesc &program) {
#define _INT(role) static_cast<int>(role)
std::map<int, bool> visit;
for (OpDesc *op : program.Block(0).AllOps()) {
// For backward compatibility, some program doesn't have role added.
if (!op->HasAttr(OpProtoAndCheckerMaker::OpRoleAttrName())) continue;
int role_id =
boost::get<int>(op->GetAttr(OpProtoAndCheckerMaker::OpRoleAttrName()));
visit[role_id] = true;
switch (role_id) {
case _INT(OpRole::kForward):
if (visit.find(_INT(OpRole::kBackward)) != visit.end()) {
LOG(ERROR)
<< "Cannot add backward operator before forward operator %s."
<< op->Type();
}
break;
case _INT(OpRole::kBackward):
case _INT(OpRole::kBackward) | _INT(OpRole::kLoss):
PADDLE_ENFORCE(
visit.find(_INT(OpRole::kOptimize)) == visit.end(),
"Cannot add backward operator %s after optimize operator.",
op->Type());
break;
case _INT(OpRole::kForward) | _INT(OpRole::kLoss):
PADDLE_ENFORCE(visit.find(_INT(OpRole::kBackward) |
_INT(OpRole::kLoss)) == visit.end(),
"Cannot add backward|loss operator before "
"forward|loss operator %s.",
op->Type());
PADDLE_ENFORCE(
visit.find(_INT(OpRole::kOptimize)) == visit.end(),
"Cannot add forward|loss operator %s after optimize operator.",
op->Type());
break;
case _INT(OpRole::kOptimize):
case _INT(OpRole::kOptimize) | _INT(OpRole::kLRSched):
PADDLE_ENFORCE(visit.find(_INT(OpRole::kBackward)) != visit.end(),
"Optimize operators %s must follow backward operator.",
op->Type());
break;
case _INT(OpRole::kLRSched):
case _INT(OpRole::kDist):
case _INT(OpRole::kRPC):
case _INT(OpRole::kNotSpecified):
break;
default:
LOG(FATAL) << "Unknown operator role. Don't add new role because "
"you don't know what you are doing.";
}
}
#undef _INT
}
} // namespace
Graph::Graph(const ProgramDesc &program) : program_(program) { Graph::Graph(const ProgramDesc &program) : program_(program) {
CheckProgram(program_);
auto var_nodes = InitFromProgram(program_); auto var_nodes = InitFromProgram(program_);
ResolveHazard(var_nodes); ResolveHazard(var_nodes);
} }
......
...@@ -215,6 +215,7 @@ void ParallelExecutor::BCastParamsToDevices( ...@@ -215,6 +215,7 @@ void ParallelExecutor::BCastParamsToDevices(
if (paddle::platform::is_gpu_place(main_tensor.place())) { if (paddle::platform::is_gpu_place(main_tensor.place())) {
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32) #if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
std::vector<void *> buffers; std::vector<void *> buffers;
buffers.reserve(member_->places_.size());
size_t numel = main_tensor.numel(); size_t numel = main_tensor.numel();
ncclDataType_t data_type = platform::ToNCCLDataType(main_tensor.type()); ncclDataType_t data_type = platform::ToNCCLDataType(main_tensor.type());
for (size_t i = 0; i < member_->places_.size(); ++i) { for (size_t i = 0; i < member_->places_.size(); ++i) {
...@@ -248,9 +249,7 @@ void ParallelExecutor::BCastParamsToDevices( ...@@ -248,9 +249,7 @@ void ParallelExecutor::BCastParamsToDevices(
#endif #endif
} else { } else {
platform::CPUPlace cpu; platform::CPUPlace cpu;
for (size_t i = 0; i < member_->places_.size(); ++i) { for (size_t i = 1; i < member_->places_.size(); ++i) {
if (i == 0) continue;
auto local_scope = member_->local_scopes_[i]; auto local_scope = member_->local_scopes_[i];
auto *t = local_scope->Var(var)->GetMutable<LoDTensor>(); auto *t = local_scope->Var(var)->GetMutable<LoDTensor>();
......
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