p60975123
/
mindspore
forked from mindspore-Ecosystem/mindspore
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

actor runtime code review modify

This commit is contained in:
limingqi107 2021-04-27 10:56:25 +08:00
parent fba1dd8f2f
commit 57a14f55e8
11 changed files with 66 additions and 50 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

17
mindspore/ccsrc/runtime/device/device_address.h
View File

@ -69,11 +69,16 @@ class DeviceAddress : public mindspore::DeviceSync {
virtual DeviceAddressStatus status() const { return DeviceAddressStatus::kInDevice; }
virtual DeviceAddressType DeviceType() const { return DeviceAddressType::kUnknown; }
void *GetMutablePtr() const override { return ptr_; }
// The related interface of reference count operation.
void set_original_ref_count(size_t original_ref_count) { original_ref_count_ = original_ref_count; }
size_t original_ref_count() const { return original_ref_count_; }
void set_ref_count(size_t ref_count) { ref_count_ = ref_count; }
void IncreaseRefCount() { ref_count_++; }
void DecreaseRefCountUsed() { ref_count_dynamic_used_--; }
void ResetRefCountUsed() { ref_count_dynamic_used_ = ref_count_; }
size_t ref_count_dynamic_used() const { return ref_count_dynamic_used_; }
size_t ref_count() const { return ref_count_; }
void IncreaseOriginalRefCount() { original_ref_count_++; }
void DecreaseRefCount() { ref_count_--; }
void ResetRefCount() { ref_count_ = original_ref_count_; }
virtual bool DumpMemToFile(const std::string &filepath, const std::string &host_fmt, const ShapeVector &host_shape,
TypeId host_type, bool trans_flag) const {
return true;
@ -91,9 +96,9 @@ class DeviceAddress : public mindspore::DeviceSync {
void set_ptr(void *ptr) { ptr_ = ptr; }
void *ptr_{nullptr};
size_t size_{0};
size_t original_ref_count_{1};
// It will be decreased in the running, and reset by original_ref_count_ when it is zero.
size_t ref_count_{1};
// It will be decreased in the running, and reset by ref_count_ when it is zero.
size_t ref_count_dynamic_used_{1};
string format_{"DefaultFormat"};
TypeId type_id_{kNumberTypeFloat16};
bool from_mem_pool_{false};

2
mindspore/ccsrc/runtime/framework/actor/data_source_actor.h
View File

@ -36,7 +36,7 @@ using mindspore::device::DeviceContext;
// The data source actor is used to fetch data from data source and process them into device tensors,
// and then send them to kernel actor. The processing flow is FetchData -> FillDataBuffer -> AllocateMemory
// -> OnMemoryAllocFinish -> SendOutput -> FreeMemory.
// -> OnMemoryAllocFinish -> FreeMemory -> SendOutput.
class DataSourceActor : public MemoryInterfaceActor {
public:
DataSourceActor(std::string name, size_t buffer_capacity, const DeviceContext *device_context,

2
mindspore/ccsrc/runtime/framework/actor/kernel_actor.h
View File

@ -37,7 +37,7 @@ using mindspore::kernel::AddressPtr;
// The kernel actor is used to receive the device tensors and control info to luanch kernel.
// The processing flow is RunOpData/RunOpControl -> CheckLaunchCondition -> AllocateMemory
// -> OnMemoryAllocFinish -> LaunchKernel -> SendOutput -> FreeMemory.
// -> OnMemoryAllocFinish -> LaunchKernel -> FreeMemory -> SendOutput.
class KernelActor : public MemoryInterfaceActor {
public:
KernelActor(std::string name, CNodePtr kernel, const DeviceContext *device_context, const AID memory_manager_aid)

6
mindspore/ccsrc/runtime/framework/actor/memory_manager_actor.cc
View File

@ -50,13 +50,13 @@ void MemoryManagerActor::FreeMemory(std::vector<DeviceTensor *> free_list, const
for (auto &device_tensor : free_list) {
MS_EXCEPTION_IF_NULL(device_tensor);
// The reference count is decremented to zero to free memory, and reset to the original count.
device_tensor->DecreaseRefCountUsed();
if (device_tensor->ref_count_dynamic_used() == 0) {
device_tensor->DecreaseRefCount();
if (device_tensor->ref_count() == 0) {
// Free memory through the device context.
if (device_tensor->GetPtr() != nullptr) {
device_context->FreeMemory(device_tensor);
}
device_tensor->ResetRefCountUsed();
device_tensor->ResetRefCount();
}
}
}

15
mindspore/ccsrc/runtime/framework/graph_compiler.cc
View File

@ -78,10 +78,8 @@ void CreateParameterDeviceAddress(const DeviceContext *device_context, const Ker
auto output_size = AnfAlgo::GetOutputTensorNum(item);
for (size_t index = 0; index < output_size; index++) {
TypeId output_type_id = AnfAlgo::GetOutputDeviceDataType(item, index);
// if graph output is a weight and doesn't link to any cnode, it's data type will be unknown
if (output_type_id == kTypeUnknown) {
MS_LOG(WARNING) << "It is not suggested to use a lonely weight parameter as the output of graph";
continue;
output_type_id = AnfAlgo::GetOutputInferDataType(item, index);
}
size_t tensor_size = AnfAlgo::GetOutputTensorMemSize(item, index);
@ -212,13 +210,9 @@ GraphId GraphCompiler::CompileGraph(const AnfNodePtrList &nodes, const AnfNodePt
GraphId GraphCompiler::CompileGraphImpl(const KernelGraphPtr &graph) const {
MS_EXCEPTION_IF_NULL(graph);
MS_EXCEPTION_IF_NULL(device_context_);
// Optimization pass which is irrelevant to device type or format.
device_context_->OptimizeGraphWithoutDeviceInfo(graph);
device_context_->SetOperatorInfo(graph->execution_order());
// Optimization pass which is relevant to device type or format.
device_context_->OptimizeGraphWithDeviceInfo(graph);
// Execute optimization pass.
device_context_->OptimizeGraph(graph);
// Generate 'KernelMod' for all kernels and set 'KernelMod' into kernel,
// 'KernelMod' is real executive object of kernel.
@ -248,9 +242,8 @@ GraphId GraphCompiler::CompileGraph(session::OpRunInfo *op_run_info, const Graph
MS_EXCEPTION_IF_NULL(graph);
MS_EXCEPTION_IF_NULL(device_context_);
device_context_->SetOperatorInfo(graph->execution_order());
device_context_->OptimizeSingleOpGraph(graph);
MS_EXCEPTION_IF_NULL(session_);
session_->RunOpHideNopNode(graph);
session_->RunOpRemoveNopNode(graph);

30
mindspore/ccsrc/runtime/framework/graph_scheduler.cc
View File

@ -99,8 +99,8 @@ void UpdateRefCount(const AnfNodePtr &node, size_t output_idx) {
MS_EXCEPTION_IF_NULL(node);
auto device_tensor = AnfAlgo::GetMutableOutputAddr(node, output_idx);
MS_EXCEPTION_IF_NULL(device_tensor);
device_tensor->IncreaseRefCount();
device_tensor->ResetRefCountUsed();
device_tensor->IncreaseOriginalRefCount();
device_tensor->ResetRefCount();
}
// The branch processing of PrepareDataForValueNode that value type is tensor.
@ -252,8 +252,8 @@ BaseRef CreateOutputTensor(const session::KernelWithIndex &node_output_pair, con
const auto &device_tensor = AnfAlgo::GetMutableOutputAddr(node, output_index);
MS_EXCEPTION_IF_NULL(device_tensor);
tensor->set_device_address(device_tensor);
device_tensor->set_ref_count(SIZE_MAX);
device_tensor->ResetRefCountUsed();
device_tensor->set_original_ref_count(SIZE_MAX);
device_tensor->ResetRefCount();
return tensor;
}
}
@ -307,8 +307,8 @@ void AllocateContinuousMemoryForInput(const AnfNodePtr &kernel, const DeviceCont
MS_EXCEPTION_IF_NULL(device_tensor);
// In the scene of communication op and computing op parallel multi stream, the input address of communication op
// can't be reused, so set the max reference count.
device_tensor->set_ref_count(SIZE_MAX);
device_tensor->ResetRefCountUsed();
device_tensor->set_original_ref_count(SIZE_MAX);
device_tensor->ResetRefCount();
if (device_tensor->GetPtr() == nullptr) {
is_need_alloc_memory = true;
@ -341,8 +341,8 @@ void AllocateContinuousMemoryForOutput(const AnfNodePtr &kernel, const DeviceCon
const auto &device_tensor = AnfAlgo::GetMutableOutputAddr(kernel, i, false);
MS_EXCEPTION_IF_NULL(device_tensor);
// One time application for continuous memory, so set the max reference count.
device_tensor->set_ref_count(SIZE_MAX);
device_tensor->ResetRefCountUsed();
device_tensor->set_original_ref_count(SIZE_MAX);
device_tensor->ResetRefCount();
if (device_tensor->GetPtr() == nullptr) {
is_need_alloc_memory = true;
@ -925,8 +925,8 @@ void GraphScheduler::PersistDeviceTensor(const KernelGraphPtr &graph) {
}
auto device_tensor = AnfAlgo::GetMutableOutputAddr(value_node, 0);
DeviceTensorStore::GetInstance().Insert(value_node.get(), device_tensor);
device_tensor->set_ref_count(SIZE_MAX);
device_tensor->ResetRefCountUsed();
device_tensor->set_original_ref_count(SIZE_MAX);
device_tensor->ResetRefCount();
}
for (auto &input_node : graph->input_nodes()) {
@ -935,8 +935,8 @@ void GraphScheduler::PersistDeviceTensor(const KernelGraphPtr &graph) {
auto device_tensor = AnfAlgo::GetMutableOutputAddr(input_node, 0);
MS_EXCEPTION_IF_NULL(device_tensor);
DeviceTensorStore::GetInstance().Insert(input_node.get(), device_tensor);
device_tensor->set_ref_count(SIZE_MAX);
device_tensor->ResetRefCountUsed();
device_tensor->set_original_ref_count(SIZE_MAX);
device_tensor->ResetRefCount();
}
}
}
@ -1008,7 +1008,7 @@ void GraphScheduler::DumpDSActor(const DataSourceActor *actor, std::ofstream &of
const auto &device_tensor = AnfAlgo::GetMutableOutputAddr(data_kernel, i, false);
MS_EXCEPTION_IF_NULL(device_tensor);
ofs << "\t\t\toutput_index:" << i << "\tptr:" << device_tensor->GetPtr() << "\tsize:" << device_tensor->GetSize()
<< "\tref_count:" << device_tensor->ref_count_dynamic_used() << "\n ";
<< "\toriginal_ref_count:" << device_tensor->original_ref_count() << "\n ";
}
} else if (actor_name.find("_HostQueueDataSourceActor") != string::npos) {
// Dump the member info of host queue data source actor.
@ -1021,7 +1021,7 @@ void GraphScheduler::DumpDSActor(const DataSourceActor *actor, std::ofstream &of
MS_EXCEPTION_IF_NULL(device_tensor);
ofs << "\t\t\tnode_order_number:" << i << "\tnode_name:" << data_node->fullname_with_scope()
<< "\tptr:" << device_tensor->GetPtr() << "\tsize:" << device_tensor->GetSize()
<< "\tref_count:" << device_tensor->ref_count_dynamic_used() << "\n ";
<< "\toriginal_ref_count:" << device_tensor->original_ref_count() << "\n ";
}
}
@ -1065,7 +1065,7 @@ void GraphScheduler::DumpKernelActor(const KernelActor *actor, std::ofstream &of
const auto &device_tensor = AnfAlgo::GetMutableOutputAddr(kernel, i, false);
MS_EXCEPTION_IF_NULL(device_tensor);
ofs << "\t\t\toutput_index:" << i << "\tptr:" << device_tensor->GetPtr() << "\tsize:" << device_tensor->GetSize()
<< "\tref_count:" << device_tensor->ref_count_dynamic_used() << "\n ";
<< "\toriginal_ref_count:" << device_tensor->original_ref_count() << "\n ";
}
ofs << "\t\tdevice_tensor_stores:" << actor->device_tensor_store_keys_.size() << "\n ";

9
mindspore/ccsrc/runtime/hardware/cpu/cpu_device_context.cc
View File

@ -55,10 +55,11 @@ DeviceAddressPtr CPUDeviceContext::CreateDeviceAddress(void *device_ptr, size_t
return std::make_shared<CPUDeviceAddress>(device_ptr, device_size, format, type_id);
}
void CPUDeviceContext::OptimizeGraphWithoutDeviceInfo(const KernelGraphPtr &graph) const {
void CPUDeviceContext::OptimizeGraph(const KernelGraphPtr &graph) const {
// Update Graph Dynamic Shape Attr.
UpdateGraphDynamicShapeAttr(NOT_NULL(graph));
SetOperatorInfo(graph->execution_order());
OptimizeGraphImpl(graph);
// Remove reorder after PS feature finish adapting push/pull in auto_monad.
@ -67,7 +68,11 @@ void CPUDeviceContext::OptimizeGraphWithoutDeviceInfo(const KernelGraphPtr &grap
graph->set_execution_order(execution_order);
}
void CPUDeviceContext::OptimizeSingleOpGraph(const KernelGraphPtr &graph) const { OptimizeGraphImpl(graph); }
void CPUDeviceContext::OptimizeSingleOpGraph(const KernelGraphPtr &graph) const {
MS_EXCEPTION_IF_NULL(graph);
SetOperatorInfo(graph->execution_order());
OptimizeGraphImpl(graph);
}
void CPUDeviceContext::OptimizeGraphImpl(const KernelGraphPtr &graph) const {
auto optimizer = std::make_shared<opt::GraphOptimizer>();

2
mindspore/ccsrc/runtime/hardware/cpu/cpu_device_context.h
View File

@ -41,7 +41,7 @@ class CPUDeviceContext : public DeviceContext {
TypeId type_id) const override;
DeviceAddressType GetDeviceAddressType() const override { return DeviceAddressType::kCPU; }
void OptimizeGraphWithoutDeviceInfo(const KernelGraphPtr &graph) const override;
void OptimizeGraph(const KernelGraphPtr &graph) const override;
void OptimizeSingleOpGraph(const KernelGraphPtr &graph) const override;
void SetOperatorInfo(const std::vector<CNodePtr> &nodes) const override;

7
mindspore/ccsrc/runtime/hardware/device_context.h
View File

@ -70,11 +70,8 @@ class DeviceContext {
// Get device address type according different device type, such GPU, Ascend.
virtual DeviceAddressType GetDeviceAddressType() const = 0;
// The two functions below will be merged to one in the future.
// General graph optimezer ignore device data type and format.
virtual void OptimizeGraphWithoutDeviceInfo(const KernelGraphPtr &graph) const {}
// Optimize the kernel graph according to device data type and format.
virtual void OptimizeGraphWithDeviceInfo(const KernelGraphPtr &graph) const {}
// Optimize the kernel graph for graph mode.
virtual void OptimizeGraph(const KernelGraphPtr &graph) const {}
// Optimize the single operator graph for PyNative mode.
virtual void OptimizeSingleOpGraph(const KernelGraphPtr &graph) const {}

14
mindspore/ccsrc/runtime/hardware/gpu/gpu_device_context.cc
View File

@ -165,6 +165,17 @@ DeviceAddressPtr GPUDeviceContext::CreateDeviceAddress(void *device_ptr, size_t
return std::make_shared<GPUDeviceAddress>(device_ptr, device_size, format, type_id);
}
void GPUDeviceContext::OptimizeGraph(const KernelGraphPtr &graph) const {
MS_EXCEPTION_IF_NULL(graph);
// Optimization pass which is irrelevant to device type or format.
OptimizeGraphWithoutDeviceInfo(graph);
SetOperatorInfo(graph->execution_order());
// Optimization pass which is relevant to device type or format.
OptimizeGraphWithDeviceInfo(graph);
}
void GPUDeviceContext::OptimizeGraphWithoutDeviceInfo(const KernelGraphPtr &graph) const {
MS_EXCEPTION_IF_NULL(graph);
// Operator fusion optimization.
@ -240,6 +251,9 @@ void GPUDeviceContext::UpdateGraphDynamicShapeAttr(const NotNull<KernelGraphPtr>
}
void GPUDeviceContext::OptimizeSingleOpGraph(const KernelGraphPtr &graph) const {
MS_EXCEPTION_IF_NULL(graph);
SetOperatorInfo(graph->execution_order());
auto optimizer = std::make_shared<opt::GraphOptimizer>();
auto pm = std::make_shared<opt::PassManager>();
pm->AddPass(std::make_shared<opt::ReducePrecisionFusion>("reduce_precision"));

12
mindspore/ccsrc/runtime/hardware/gpu/gpu_device_context.h
View File

@ -48,11 +48,8 @@ class GPUDeviceContext : public DeviceContext {
TypeId type_id) const override;
DeviceAddressType GetDeviceAddressType() const override { return DeviceAddressType::kGPU; }
// General graph optimezer ignore device data type and format.
void OptimizeGraphWithoutDeviceInfo(const KernelGraphPtr &graph) const override;
// Optimize the kernel graph according to device type, such format transform.
void OptimizeGraphWithDeviceInfo(const KernelGraphPtr &graph) const override;
// Optimize the kernel graph for graph mode.
void OptimizeGraph(const KernelGraphPtr &graph) const override;
// Optimize the single operator graph for PyNative mode.
void OptimizeSingleOpGraph(const KernelGraphPtr &graph) const override;
@ -67,6 +64,11 @@ class GPUDeviceContext : public DeviceContext {
DISABLE_COPY_AND_ASSIGN(GPUDeviceContext);
bool InitDevice();
// General graph optimezer ignore device data type and format.
void OptimizeGraphWithoutDeviceInfo(const KernelGraphPtr &graph) const;
// Optimize the kernel graph according to device type, such format transform.
void OptimizeGraphWithDeviceInfo(const KernelGraphPtr &graph) const;
// Operator fusion optimization.
void FuseOperators(const KernelGraphPtr &graph) const;