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9 changes: 7 additions & 2 deletions paddle/fluid/framework/details/CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,10 @@ cc_library(fetch_barrier_op_handle SRCS fetch_barrier_op_handle.cc DEPS framewor
cc_library(multi_devices_helper SRCS multi_devices_helper.cc DEPS graph graph_helper)
cc_library(multi_devices_graph_print_pass SRCS multi_devices_graph_print_pass.cc DEPS multi_devices_helper)
cc_library(multi_devices_graph_check_pass SRCS multi_devices_graph_check_pass.cc DEPS multi_devices_helper)

cc_library(alloc_continuous_space_for_grad_pass SRCS alloc_continuous_space_for_grad_pass.cc DEPS graph graph_helper)
cc_library(fuse_adam_op_pass SRCS fuse_adam_op_pass.cc fuse_optimizer_op_pass.cc DEPS graph graph_helper)
cc_library(fuse_sgd_op_pass SRCS fuse_sgd_op_pass.cc fuse_optimizer_op_pass.cc DEPS graph graph_helper)

cc_library(variable_visitor SRCS variable_visitor.cc DEPS lod_tensor selected_rows)

Expand Down Expand Up @@ -104,5 +107,7 @@ cc_library(build_strategy SRCS build_strategy.cc DEPS
graph_viz_pass multi_devices_graph_pass
multi_devices_graph_print_pass multi_devices_graph_check_pass
fuse_elewise_add_act_pass multi_batch_merge_pass
fuse_relu_depthwise_conv_pass
memory_optimize_pass lock_free_optimize_pass alloc_continuous_space_for_grad_pass fuse_all_reduce_op_pass)
fuse_relu_depthwise_conv_pass
memory_optimize_pass lock_free_optimize_pass
alloc_continuous_space_for_grad_pass fuse_all_reduce_op_pass
fuse_adam_op_pass fuse_sgd_op_pass)
Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@
#include "paddle/fluid/framework/details/multi_devices_helper.h"
#include "paddle/fluid/framework/ir/graph_helper.h"
#include "paddle/fluid/framework/op_registry.h"

DEFINE_uint32(fuse_parameter_memory_size, 0, // 0 KB
"fuse_parameter_memory_size is up limited memory size "
"of one group parameters' gradient which is the input "
Expand Down Expand Up @@ -105,20 +106,29 @@ class AllocContinuousSpaceForGradPass : public ir::Pass {
auto ele_dtype = iter->second->Var()->GetDataType();
if (dtype == kDefaultDtype) {
dtype = ele_dtype;
PADDLE_ENFORCE_NE(ele_dtype, kDefaultDtype);
PADDLE_ENFORCE_NE(ele_dtype, kDefaultDtype,
"The data type should not be bool.");
}
PADDLE_ENFORCE_EQ(ele_dtype, dtype);
PADDLE_ENFORCE_EQ(ele_dtype, dtype,
"The data type of input is not consistent.");
}

// Create the fused variable name.
// Create a FusedVarsSet to avoid duplicating names for fused_var in other
// pass.
if (!result.Has(kFusedVars)) {
result.Set(kFusedVars, new FusedVars);
}
const std::string prefix(kFusedVarNamePrefix);
// The fused_var_name should be unique.
auto fused_var_name = prefix + "GRAD@" + params_grads[0].second;
// the kFusedGrads is used be fuse_optimizer_op_pass.
result.Set(kFusedGrads, new FusedGrads);

// the fused_var_name should be unique, so it appends
// params_grads.begin()->second.
auto fused_var_name = std::string(kFusedVarNamePrefix) + "@GRAD@" +
params_grads.begin()->second;
result.Get<FusedGrads>(kFusedGrads) = fused_var_name;
auto &fused_var_set = result.Get<FusedVars>(kFusedVars);
PADDLE_ENFORCE_EQ(fused_var_set.count(fused_var_name), 0);
PADDLE_ENFORCE_EQ(fused_var_set.count(fused_var_name), 0,
"%s is duplicate in FusedVars.", fused_var_name);
fused_var_set.insert(fused_var_name);

InitFusedVarsAndAllocSpaceForVars(places, local_scopes, vars,
Expand Down Expand Up @@ -295,17 +305,6 @@ class AllocContinuousSpaceForGradPass : public ir::Pass {
return type == proto::VarType::LOD_TENSOR;
}

void AppendAllocSpaceForVarsOp(const std::vector<std::string> &params_name,
const std::vector<std::string> &grads_name,
const std::string &fused_var_name,
BlockDesc *global_block) const {
auto op_desc = global_block->AppendOp();
op_desc->SetType("alloc_continuous_space");
op_desc->SetInput("Input", params_name);
op_desc->SetOutput("Output", grads_name);
op_desc->SetOutput("FusedOutput", {fused_var_name});
}

void RecordParamsAndGrads(ir::Node *node,
ParamsAndGrads *params_grads) const {
try {
Expand Down Expand Up @@ -358,6 +357,7 @@ class AllocContinuousSpaceForGradPass : public ir::Pass {
}
}

// Alloc continuous space for vars.
std::vector<std::string> grads_name;
std::vector<std::string> params_name;
grads_name.reserve(params_grads.size());
Expand All @@ -370,14 +370,24 @@ class AllocContinuousSpaceForGradPass : public ir::Pass {
AppendAllocSpaceForVarsOp(params_name, grads_name, fused_var_name,
program_desc.MutableBlock(0));

// Run Only Once Programs
for (size_t i = 0; i < local_scopes.size(); ++i) {
for (auto &op_desc : program_desc.Block(0).AllOps()) {
auto op = OpRegistry::CreateOp(*op_desc);
op->Run(*local_scopes[i], places[i]);
}
}
}

void AppendAllocSpaceForVarsOp(const std::vector<std::string> &params_name,
const std::vector<std::string> &grads_name,
const std::string &fused_var_name,
BlockDesc *global_block) const {
auto op_desc = global_block->AppendOp();
op_desc->SetType("alloc_continuous_space");
op_desc->SetInput("Input", params_name);
op_desc->SetOutput("Output", grads_name);
op_desc->SetOutput("FusedOutput", {fused_var_name});
}
};

} // namespace details
Expand Down
13 changes: 5 additions & 8 deletions paddle/fluid/framework/details/broadcast_op_handle.cc
Original file line number Diff line number Diff line change
Expand Up @@ -27,20 +27,17 @@ void BroadcastOpHandle::RunImpl() {
if (places_.size() == 1) return;

// The input and output may have dummy vars.
VarHandle *in_var_handle;
{
auto in_var_handles = DynamicCast<VarHandle>(inputs_);
PADDLE_ENFORCE_EQ(in_var_handles.size(), 1UL,
"The number of input should be one.");
in_var_handle = in_var_handles[0];
}

auto in_var_handles = DynamicCast<VarHandle>(inputs_);
auto out_var_handles = DynamicCast<VarHandle>(outputs_);

PADDLE_ENFORCE_EQ(in_var_handles.size(), 1UL,
"The number of input should be one.");
PADDLE_ENFORCE_EQ(
out_var_handles.size(), places_.size(),
"The number of output should equal to the number of places.");

VarHandle *in_var_handle = in_var_handles[0];

WaitInputVarGenerated();

std::vector<const Scope *> var_scopes;
Expand Down
52 changes: 39 additions & 13 deletions paddle/fluid/framework/details/build_strategy.cc
Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,6 @@ limitations under the License. */
#include <glog/logging.h>
#include <memory>
#include <utility>

#include "paddle/fluid/framework/details/memory_optimize_helper.h"
#include "paddle/fluid/framework/details/multi_devices_graph_pass.h"
#include "paddle/fluid/framework/details/multi_devices_graph_print_pass.h"
Expand Down Expand Up @@ -82,23 +81,43 @@ class ParallelExecutorPassBuilder : public ir::PassBuilder {
AppendPass("inplace_pass");
}

if (strategy.fuse_elewise_add_act_ops_) {
if (strategy_.fuse_elewise_add_act_ops_) {
VLOG(10) << "Add fuse_elewise_add_act_pass";
AppendPass("fuse_elewise_add_act_pass");
}

// for single card training, fuse_all_reduce_ops is unnecessary.
// alloc_continuous_space_for_grad_pass should be before of MultiDevPass.
if (strategy.fuse_all_reduce_ops_) {
if (strategy_.fuse_all_reduce_ops_) {
VLOG(10) << "Add alloc_continuous_space_for_grad_pass";
AppendPass("alloc_continuous_space_for_grad_pass");
}

if (strategy_.fuse_all_optimizer_ops_) {
if (strategy_.reduce_ == BuildStrategy::ReduceStrategy::kReduce ||
strategy_.is_distribution_) {
VLOG(3)
<< "Currently, fuse_all_optimizer_ops only works under AllReduce "
"mode.";
strategy_.fuse_all_optimizer_ops_ = false;
} else {
VLOG(10) << "Add alloc_continuous_space_for_grad_pass";
AppendPass("alloc_continuous_space_for_grad_pass");
// NOTE: fuse_all_xx_ops will count the number of xx operator first,
// if the number is zero, fuse_all_reduce_ops will do nothing.
// Currently, only one type of optimization algorithm can be fused.
VLOG(10) << "Add fuse_adam_op_pass";
AppendPass("fuse_adam_op_pass");
VLOG(10) << "Add fuse_sgd_op_pass";
AppendPass("fuse_sgd_op_pass");
}
}

// Add a graph viz pass to record a graph.
if (!strategy.debug_graphviz_path_.empty()) {
auto viz_pass = AppendPass("graph_viz_pass");
const std::string graph_path = string::Sprintf(
"%s%s", strategy.debug_graphviz_path_.c_str(), "_fused_graph");
"%s%s", strategy_.debug_graphviz_path_.c_str(), "_fused_graph");
viz_pass->Set<std::string>("graph_viz_path", new std::string(graph_path));
}

Expand All @@ -118,14 +137,14 @@ class ParallelExecutorPassBuilder : public ir::PassBuilder {
// the de-fact IR, any reuse on Graph is meaningless.
// A side-effect of that, memory optimize cannot forsee the fetched vars
// , so fetchlist should be set persistable before call the Run interface.
if (strategy.memory_optimize_) {
if (strategy_.memory_optimize_) {
VLOG(10) << "Add memory_optimize_pass";
AppendPass("memory_optimize_pass");
}

AppendMultiDevPass(strategy);
AppendMultiDevPass(strategy_);

if (strategy.fuse_all_reduce_ops_) {
if (strategy_.fuse_all_reduce_ops_) {
// NOTE: fuse_all_reduce_ops will count the number of all_reduce operator
// first, if the number is zero, fuse_all_reduce_ops will do nothing.
VLOG(10) << "Add fuse_all_reduce_op_pass";
Expand All @@ -151,7 +170,7 @@ class ParallelExecutorPassBuilder : public ir::PassBuilder {
AppendPass("all_reduce_deps_pass");
}

if (SeqOnlyAllReduceOps(strategy)) {
if (SeqOnlyAllReduceOps(strategy_)) {
VLOG(10) << "Add all_reduce_deps_pass";
AppendPass("all_reduce_deps_pass");
}
Expand All @@ -165,7 +184,7 @@ class ParallelExecutorPassBuilder : public ir::PassBuilder {
// Convert graph to run on multi-devices.
void AppendMultiDevPass(const BuildStrategy &strategy) {
ir::Pass *multi_devices_pass = nullptr;
if (strategy_.is_distribution_) {
if (strategy.is_distribution_) {
VLOG(10) << "Add dist_multi_devices_pass";
multi_devices_pass = AppendPass("dist_multi_devices_pass").get();
} else {
Expand Down Expand Up @@ -235,17 +254,22 @@ ir::Graph *BuildStrategy::Apply(ir::Graph *graph,
pass->Erase(kNCCLCtxs);
pass->SetNotOwned<platform::NCCLContextMap>(kNCCLCtxs, nctx);
#endif
} else if (pass->Type() == "fuse_all_reduce_op_pass") {
} else if (pass->Type() == "alloc_continuous_space_for_grad_pass" ||
pass->Type() == "fuse_adam_op_pass" ||
pass->Type() == "fuse_sgd_op_pass" ||
pass->Type() == "fuse_all_reduce_op_pass") {
pass->Erase(kPlaces);
pass->SetNotOwned<const std::vector<platform::Place>>(kPlaces, &places);
pass->Erase(kLocalScopes);
pass->SetNotOwned<const std::vector<Scope *>>(kLocalScopes,
&local_scopes);
if (pass->Type() == "fuse_all_reduce_op_pass") {
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
platform::NCCLContextMap *nctx = use_cuda ? nccl_ctxs : nullptr;
pass->Erase(kNCCLCtxs);
pass->SetNotOwned<platform::NCCLContextMap>(kNCCLCtxs, nctx);
platform::NCCLContextMap *nctx = use_cuda ? nccl_ctxs : nullptr;
pass->Erase(kNCCLCtxs);
pass->SetNotOwned<platform::NCCLContextMap>(kNCCLCtxs, nctx);
#endif
}
} else if (pass->Type() == "alloc_continuous_space_for_grad_pass") {
pass->Erase(kPlaces);
pass->SetNotOwned<const std::vector<platform::Place>>(kPlaces, &places);
Expand Down Expand Up @@ -294,4 +318,6 @@ USE_PASS(inplace_pass);
USE_PASS(lock_free_optimize_pass);
USE_PASS(alloc_continuous_space_for_grad_pass);
USE_PASS(graph_to_program_pass);
USE_PASS(fuse_adam_op_pass);
USE_PASS(fuse_sgd_op_pass);
USE_PASS(fuse_all_reduce_op_pass);
3 changes: 2 additions & 1 deletion paddle/fluid/framework/details/build_strategy.h
Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,6 @@
#include <string>
#include <utility>
#include <vector>

#include "paddle/fluid/framework/ir/pass_builder.h"
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/framework/scope.h"
Expand Down Expand Up @@ -76,6 +75,8 @@ struct BuildStrategy {

bool fuse_elewise_add_act_ops_{false};

bool fuse_all_optimizer_ops_{false};
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enable by default?

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?

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I'm not sure if this pass can improve performance on all models, today I'll turn it on and run on CE.

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what's the result?

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For some models, the speed can be increased by 19%, for example, the model_object_detection model (in the case of 4 cards), in some models, the speed decreases slightly by 1%.


bool fuse_all_reduce_ops_{false};

bool fuse_relu_depthwise_conv_{false};
Expand Down
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