!1047 multi_task for single_op.

From: @zhao_zhixuan
Reviewed-by: @xchu42,@ji_chen
Signed-off-by: @ji_chen
pull/1047/MERGE
mindspore-ci-bot 4 years ago committed by Gitee
commit a8489106ba

@ -639,15 +639,6 @@ set(INFER_SRC_LIST
"graph/load/model_manager/task_info/model_exit_task_info.cc"
"graph/load/model_manager/task_info/super_kernel/super_kernel_factory.cc"
"graph/load/model_manager/task_info/super_kernel/super_kernel.cc"
"single_op/task/op_task.cc"
"single_op/task/build_task_utils.cc"
"single_op/task/tbe_task_builder.cc"
"single_op/task/aicpu_task_builder.cc"
"single_op/task/aicpu_kernel_task_builder.cc"
"single_op/single_op.cc"
"single_op/single_op_model.cc"
"single_op/stream_resource.cc"
"single_op/single_op_manager.cc"
"hybrid/hybrid_davinci_model_stub.cc"
"ir_build/ge_ir_build.cc"
"ir_build/atc_ir_common.cc"

@ -71,7 +71,7 @@ TensorValue::TensorValue(void *buffer, size_t size) : ref_buffer_(buffer), ref_s
TensorValue::~TensorValue() { Destroy(); }
void TensorValue::Destroy() {
if (buffer_ != nullptr || ref_buffer_ != nullptr) {
if (buffer_ != nullptr) {
GELOGD("Unref tensor: %s", DebugString().c_str());
buffer_.reset();
}

@ -71,12 +71,14 @@ Status HybridModelExecutor::ExecuteGraphInternal(SubgraphExecutor &executor,
GE_CHK_STATUS_RET_NOLOG(ResetExecutionContext(context_));
RECORD_MODEL_EXECUTION_EVENT(&context_, "[InitContext] End");
HYBRID_CHK_STATUS_RET(executor.ExecuteAsync(args.inputs, args.input_desc), "Failed to execute partitioned call.");
HYBRID_CHK_STATUS_RET(executor.ExecuteAsync(args.inputs, args.input_desc, args.outputs),
"Failed to execute partitioned call.");
RECORD_MODEL_EXECUTION_EVENT(&context_, "[ExecuteAsync] End");
HYBRID_CHK_STATUS_RET(executor.Synchronize(), "Failed to sync root graph.");
RECORD_MODEL_EXECUTION_EVENT(&context_, "[Synchronize] End");
args.outputs.clear();
HYBRID_CHK_STATUS_RET(executor.GetOutputs(args.outputs, args.output_desc), "Failed to get outputs");
RECORD_MODEL_EXECUTION_EVENT(&context_, "[GetOutput] End");
return SUCCESS;

@ -131,10 +131,14 @@ Status SubgraphExecutor::InitInputsForKnownShape(const std::vector<TensorValue>
}
Status SubgraphExecutor::ExecuteAsync(const std::vector<TensorValue> &inputs,
const std::vector<ConstGeTensorDescPtr> &input_desc) {
const std::vector<ConstGeTensorDescPtr> &input_desc,
const std::vector<TensorValue> &outputs) {
GELOGD("[%s] is dynamic = %s", graph_item_->GetName().c_str(), graph_item_->IsDynamic() ? "true" : "false");
GE_CHK_STATUS_RET(Init(inputs, input_desc), "[%s] Failed to init executor.", graph_item_->GetName().c_str());
if (!outputs.empty()) {
GE_CHK_STATUS_RET(EnableOutputZeroCopy(outputs),
"Failed to enable output zero copy by user provided outputs.");
}
if (!graph_item_->IsDynamic()) {
return ExecuteAsyncForKnownShape(inputs);
}
@ -144,6 +148,11 @@ Status SubgraphExecutor::ExecuteAsync(const std::vector<TensorValue> &inputs,
return SUCCESS;
}
Status SubgraphExecutor::ExecuteAsync(const std::vector<TensorValue> &inputs,
const std::vector<ConstGeTensorDescPtr> &input_desc) {
return ExecuteAsync(inputs, input_desc, {});
}
Status SubgraphExecutor::ExecuteAsyncForKnownShape(const std::vector<TensorValue> &inputs) {
GELOGD("[%s] subgraph is not dynamic.", graph_item_->GetName().c_str());
if (graph_item_->GetAllNodes().size() != 1) {
@ -440,5 +449,37 @@ Status SubgraphExecutor::SetOutputsToParentNode(TaskContext &task_context) {
return SUCCESS;
}
Status SubgraphExecutor::EnableOutputZeroCopy(const vector<TensorValue> &outputs) {
GELOGD("To enable zero copy, output number = %zu", outputs.size());
const auto &output_edges = graph_item_->GetOutputEdges();
// Op -> MetOutput, set the output tensor of Op that output to the NetOutput node
if (outputs.size() != output_edges.size()) {
GELOGE(PARAM_INVALID, "Output number mismatches, expect = %zu, but given = %zu",
output_edges.size(),
outputs.size());
return PARAM_INVALID;
}
for (size_t i = 0; i < outputs.size(); ++i) {
auto &output_tensor = outputs[i];
auto &output_node = output_edges[i].first;
int output_idx = output_edges[i].second;
GELOGD("[%s] Set output tensor[%zu] to [%s]'s output[%d], tensor = %s",
graph_item_->GetName().c_str(),
i,
output_node->NodeName().c_str(),
output_idx,
output_tensor.DebugString().c_str());
GE_CHK_STATUS_RET(subgraph_context_->SetOutput(*output_node, output_idx, output_tensor),
"[%s] Failed to set input tensor[%zu]",
graph_item_->GetName().c_str(),
i);
}
GELOGD("Done enabling zero copy for outputs successfully.");
return SUCCESS;
}
} // namespace hybrid
} // namespace ge

@ -43,7 +43,19 @@ class SubgraphExecutor {
* @param input_desc input tensor descriptions
* @return SUCCESS on success, error code otherwise
*/
Status ExecuteAsync(const std::vector<TensorValue> &inputs, const std::vector<ConstGeTensorDescPtr> &input_desc);
Status ExecuteAsync(const std::vector<TensorValue> &inputs,
const std::vector<ConstGeTensorDescPtr> &input_desc);
/**
* Execute subgraph async, output tensor address(not data) and output tensor descriptions are
* valid after this method returned
* @param inputs input tensors
* @param input_desc input tensor descriptions
* @return SUCCESS on success, error code otherwise
*/
Status ExecuteAsync(const std::vector<TensorValue> &inputs,
const std::vector<ConstGeTensorDescPtr> &input_desc,
const std::vector<TensorValue> &outputs);
/**
* Execute subgraph async, output tensor address(not data) and output tensor descriptions are
@ -76,6 +88,7 @@ class SubgraphExecutor {
private:
Status PrepareForExecution(GraphExecutionContext *ctx, NodeState &node_state);
Status EnableOutputZeroCopy(const std::vector<TensorValue> &outputs);
static Status InferShape(ShapeInferenceEngine *shape_inference_engine, NodeState &node_state);
Status Init(const std::vector<TensorValue> &inputs,
const std::vector<ConstGeTensorDescPtr> &input_desc);

@ -40,9 +40,14 @@ HybridModel::~HybridModel() {
GELOGD("[%s] HybridModel destroyed.", model_name_.c_str());
}
Status HybridModel::Init() {
Status HybridModel::Init(bool is_single_op) {
GELOGD("Start to init hybrid model.");
is_single_op_ = is_single_op;
if (is_single_op) {
GE_CHK_STATUS_RET(HybridModelBuilder(*this).BuildForSingleOp(), "Failed to build hybrid model.");
} else {
GE_CHK_STATUS_RET(HybridModelBuilder(*this).Build(), "Failed to build hybrid model.");
}
GELOGD("HybridModel initialized successfully.");
return SUCCESS;
}

@ -37,7 +37,7 @@ class HybridModel {
~HybridModel();
Status Init();
Status Init(bool is_single_op = false);
const NodeItem *GetNodeItem(const NodePtr &node) const;
@ -69,6 +69,10 @@ class HybridModel {
return model_id_;
}
bool IsSingleOp() const {
return is_single_op_;
}
TensorValue* GetVariable(const string &name) const;
NodePtr GetVariableNode(const string &name) const;
@ -131,11 +135,13 @@ class HybridModel {
std::map<NodePtr, std::unique_ptr<NodeItem>> node_items_;
bool is_new_model_desc_ = false; // support aipp
bool is_single_op_ = false;
// runtime fields
uint32_t device_id_ = 0;
uint32_t model_id_ = 0;
uint8_t *var_mem_base_ = nullptr;
std::unique_ptr<TensorBuffer> weight_buffer_;
RuntimeParam root_runtime_param_;
};
} // namespace hybrid

@ -147,6 +147,21 @@ Status HybridModelBuilder::Build() {
return SUCCESS;
}
Status HybridModelBuilder::BuildForSingleOp() {
GE_CHK_STATUS_RET(ValidateParams(), "Failed to validate GeRootModel");
hybrid_model_.model_name_ = ge_root_model_->GetRootGraph()->GetName();
GELOGI("[%s] Start to build hybrid model.", GetGraphName());
auto ret = ge_root_model_->GetSubgraphInstanceNameToModel();
const GeModelPtr ge_model = ret[ge_root_model_->GetRootGraph()->GetName()];
GE_CHK_STATUS_RET(IndexTaskDefs(ge_root_model_->GetRootGraph(), ge_model),
"[%s] Failed to index task defs", GetGraphName());
GE_CHK_STATUS_RET(LoadGraph(), "[%s] Failed to load graph", GetGraphName());
GE_CHK_STATUS_RET(InitWeights(), "[%s] Failed to init weights", GetGraphName());
GE_CHK_STATUS_RET(LoadTasks(), "[%s] Failed to load tasks", GetGraphName());
GELOGI("[%s] Done building hybrid model for single op successfully.", GetGraphName());
return SUCCESS;
}
Status HybridModelBuilder::ValidateParams() {
GE_CHECK_NOTNULL(ge_root_model_);
GE_CHECK_NOTNULL(ge_root_model_->GetRootGraph());
@ -951,46 +966,71 @@ Status HybridModelBuilder::InitVariableTensors() {
}
Status HybridModelBuilder::InitWeights() {
// For constant in root graph
const auto &root_graph = ge_root_model_->GetRootGraph();
const auto &subgraph_models = ge_root_model_->GetSubgraphInstanceNameToModel();
auto iter = subgraph_models.find(root_graph->GetName());
if (iter == subgraph_models.end()) {
GELOGD("Root graph model not found");
return SUCCESS;
}
auto &root_model = iter->second;
const auto &weight_buffer = root_model->GetWeight();
if (weight_buffer.GetSize() == 0) {
GELOGD("weight is empty");
return SUCCESS;
}
auto allocator = NpuMemoryAllocator::GetAllocator();
GE_CHECK_NOTNULL(allocator);
hybrid_model_.weight_buffer_ = TensorBuffer::Create(allocator, weight_buffer.size());
GE_CHECK_NOTNULL(hybrid_model_.weight_buffer_);
auto weight_base = reinterpret_cast<uint8_t *>(hybrid_model_.weight_buffer_->GetData());
GE_CHK_RT_RET(rtMemcpy(weight_base,
hybrid_model_.weight_buffer_->GetSize(),
weight_buffer.GetData(),
weight_buffer.GetSize(),
RT_MEMCPY_HOST_TO_DEVICE));
for (auto &it : hybrid_model_.node_items_) {
auto &node_item = it.second;
if (node_item->node_type != CONSTANT) {
GELOGI("Init weight mem successfully, weight base %p, weight size = %zu",
weight_base,
hybrid_model_.weight_buffer_->GetSize());
for (auto &node : root_graph->GetDirectNode()) {
if (node->GetType() != CONSTANT) {
continue;
}
const auto &constant_node = node_item->node;
auto op_desc = constant_node->GetOpDesc();
auto op_desc = node->GetOpDesc();
auto v_weights = ModelUtils::GetWeights(op_desc);
if (v_weights.empty()) {
GELOGE(INTERNAL_ERROR, "[%s] Constant has no value", constant_node->GetName().c_str());
GELOGE(INTERNAL_ERROR, "[%s] Constant has no value", node->GetName().c_str());
return INTERNAL_ERROR;
}
auto *ge_tensor = const_cast<GeTensor *>(v_weights[0].get());
auto output_desc = op_desc->MutableOutputDesc(0);
GE_CHECK_NOTNULL(output_desc);
auto tensor_size = ge_tensor->GetData().GetSize();
GELOGD("[%s] Start to init Constant node [%s], size = %ld",
GE_CHECK_NOTNULL(ge_tensor);
const GeTensorDesc &tensor_desc = ge_tensor->GetTensorDesc();
int64_t tensor_size = 0;
GE_CHK_GRAPH_STATUS_RET(TensorUtils::GetSize(*op_desc->MutableOutputDesc(0), tensor_size),
"[%s] Failed to get tensor size",
node->GetName().c_str());
int64_t data_offset = 0;
GE_CHK_GRAPH_STATUS_RET(TensorUtils::GetDataOffset(tensor_desc, data_offset),
"[%s] Failed to get data offset",
node->GetName().c_str());
GELOGD("[%s] Start to init Constant node [%s], size = %ld, offset = %ld",
GetGraphName(),
constant_node->GetName().c_str(),
tensor_size);
node->GetName().c_str(),
tensor_size,
data_offset);
auto tensor_buffer = TensorBuffer::Create(allocator, tensor_size);
auto tensor_buffer = TensorBuffer::Create(weight_base + data_offset, tensor_size);
GE_CHECK_NOTNULL(tensor_buffer);
std::unique_ptr<TensorValue> constant_tensor(new (std::nothrow)TensorValue(std::move(tensor_buffer)));
GE_CHECK_NOTNULL(constant_tensor);
constant_tensor->SetName("Constant_" + op_desc->GetName());
if (tensor_size > 0) {
GE_CHK_RT_RET(rtMemcpy(constant_tensor->MutableData(),
constant_tensor->GetSize(),
ge_tensor->GetData().data(),
ge_tensor->GetData().size(),
RT_MEMCPY_HOST_TO_DEVICE));
}
hybrid_model_.constant_tensors_.emplace(constant_node, std::move(constant_tensor));
GELOGD("[%s] Constant node [%s] added, size = %ld", GetGraphName(), constant_node->GetName().c_str(), tensor_size);
hybrid_model_.constant_tensors_.emplace(node, std::move(constant_tensor));
GELOGD("[%s] Constant node [%s] added, size = %ld", GetGraphName(), node->GetName().c_str(), tensor_size);
}
return SUCCESS;
}
@ -1038,6 +1078,53 @@ Status HybridModelBuilder::LoadGeModel(ComputeGraph &sub_graph, const GeModelPtr
return SUCCESS;
}
Status HybridModelBuilder::IndexTaskDefs(const ComputeGraphPtr &sub_graph, const GeModelPtr &ge_model) {
// index task defs
GELOGD("To index tasks for subgraph: %s", sub_graph->GetName().c_str());
std::unordered_map<int64_t, NodePtr> node_map;
for (const auto &node : sub_graph->GetDirectNode()) {
GE_CHECK_NOTNULL(node);
GE_CHECK_NOTNULL(node->GetOpDesc());
auto node_id = node->GetOpDesc()->GetId();
GELOGD("op_index = %ld, node_name = %s", node_id, node->GetName().c_str());
node_map.emplace(node_id, node);
}
auto tasks = ge_model->GetModelTaskDefPtr()->task();
for (int i = 0; i < tasks.size(); ++i) {
const domi::TaskDef &task_def = tasks[i];
GELOGI("Task id = %d, task type = %d", i, task_def.type());
auto task_type = static_cast<rtModelTaskType_t>(task_def.type());
uint32_t op_index = -1;
if (task_type == RT_MODEL_TASK_KERNEL) {
op_index = task_def.kernel().context().op_index();
} else if (task_type == RT_MODEL_TASK_KERNEL_EX) {
op_index = task_def.kernel_ex().op_index();
} else if (task_type == RT_MODEL_TASK_HCCL) {
op_index = task_def.kernel_hccl().op_index();
} else {
GELOGD("Skip task type: %d", static_cast<int>(task_type));
continue;
}
auto iter = node_map.find(op_index);
if (iter == node_map.end()) {
GELOGE(INTERNAL_ERROR, "Failed to get node by index = %u", op_index);
return INTERNAL_ERROR;
}
auto &node = iter->second;
if (task_type == RT_MODEL_TASK_KERNEL) {
ge_model->GetTBEKernelStore().LoadTBEKernelBinToOpDesc(node->GetOpDesc());
}
GELOGD("Task loaded for node: %s, task type = %d, op_index = %u", node->GetName().c_str(), task_type, op_index);
hybrid_model_.task_defs_[node].emplace_back(task_def);
}
return SUCCESS;
}
Status HybridModelBuilder::IndexTaskDefs() {
const auto &root_graph = ge_root_model_->GetRootGraph();
if (SetOutputNameAttr(*root_graph) != SUCCESS) {

@ -35,6 +35,7 @@ class HybridModelBuilder {
explicit HybridModelBuilder(HybridModel &hybrid_model);
~HybridModelBuilder() = default;
Status Build();
Status BuildForSingleOp();
private:
static Status UpdateAnchorStatus(const NodePtr &node);
@ -64,6 +65,7 @@ class HybridModelBuilder {
Status ParseDependentInputNodes(NodeItem &node_item, const std::vector<string> &dependencies);
Status ParseDependentForFusedSubgraph(NodeItem &node_item);
Status IndexTaskDefs();
Status IndexTaskDefs(const ComputeGraphPtr &sub_graph, const GeModelPtr &ge_model);
Status IndexSpecialNodes();
Status InitRuntimeParams();
Status InitModelMem();

@ -49,6 +49,7 @@ Status AiCoreNodeExecutor::Initialize() {
Status AiCoreNodeExecutor::LoadTask(const HybridModel &model, const NodePtr &node, shared_ptr<NodeTask> &task) const {
GE_CHECK_NOTNULL(node);
GELOGI("AiCoreNodeExecutor(%s) LoadTask Start.", node->GetName().c_str());
bool is_single_op = model.IsSingleOp();
auto *task_defs = model.GetTaskDefs(node);
if (task_defs == nullptr || task_defs->empty()) {
@ -66,7 +67,8 @@ Status AiCoreNodeExecutor::LoadTask(const HybridModel &model, const NodePtr &nod
AiCoreTaskBuilder builder(node->GetOpDesc(), *task_defs);
std::unique_ptr<NodeTask> node_task;
GE_CHK_STATUS_RET(builder.BuildTask(node_task, true), "[%s] Failed to build op tasks.", node->GetName().c_str());
GE_CHK_STATUS_RET(builder.BuildTask(node_task, true, is_single_op),
"[%s] Failed to build op tasks.", node->GetName().c_str());
task = std::move(node_task);
GELOGI("AiCoreNodeExecutor(%s) LoadTask End.", node->GetName().c_str());
return SUCCESS;

@ -65,7 +65,7 @@ Status AiCoreOpTask::RegisterTbeHandle(const OpDesc &op_desc) {
}
TBEHandleStore &kernel_store = TBEHandleStore::GetInstance();
rtError_t rt_ret = rtQueryFunctionRegistered(stub_name_.c_str());
if (rt_ret != RT_ERROR_NONE) {
if (rt_ret != RT_ERROR_NONE || is_single_op_) {
void *bin_handle = nullptr;
if (!kernel_store.FindTBEHandle(stub_name_.c_str(), bin_handle)) {
GELOGI("TBE: can't find the kernel_name[%s] in HandleMap", stub_name_.c_str());

@ -50,6 +50,8 @@ class AiCoreOpTask {
uint32_t GetBlockDim() const {return block_dim_;}
void SetSingleOp(bool is_single_op) {is_single_op_ = is_single_op;};
protected:
Status UpdateTilingInfo(TaskContext &context);
virtual std::string GetKeyForOpParamSize() const;
@ -72,6 +74,7 @@ class AiCoreOpTask {
uint32_t args_size_ = 0;
uint32_t block_dim_ = 1;
bool clear_atomic_ = true;
bool is_single_op_ = false;
std::vector<int> output_indices_to_skip_;
};

@ -37,7 +37,9 @@ AiCoreTaskBuilder::AiCoreTaskBuilder(const OpDescPtr &op_desc, const std::vector
: op_desc_(op_desc), task_defs_(task_defs) {
}
Status AiCoreTaskBuilder::BuildTask(std::unique_ptr<NodeTask> &node_task, bool ignore_failure_on_atomic) {
Status AiCoreTaskBuilder::BuildTask(std::unique_ptr<NodeTask> &node_task,
bool ignore_failure_on_atomic,
bool is_single_op) {
GE_CHECK_NOTNULL(op_desc_);
if (task_defs_.size() > kNumTaskWithAtomicAddrCleanTask) {
GELOGE(INTERNAL_ERROR,
@ -68,6 +70,7 @@ Status AiCoreTaskBuilder::BuildTask(std::unique_ptr<NodeTask> &node_task, bool i
auto atomic_task =
std::unique_ptr<AtomicAddrCleanOpTask>(new(std::nothrow)AtomicAddrCleanOpTask());
GE_CHECK_NOTNULL(atomic_task);
atomic_task->SetSingleOp(is_single_op);
GE_CHK_STATUS_RET(atomic_task->Init(*op_desc_, task_defs_.front()),
"[%s] Failed to init task for AtomicAddrClean",
op_desc_->GetName().c_str());
@ -77,6 +80,7 @@ Status AiCoreTaskBuilder::BuildTask(std::unique_ptr<NodeTask> &node_task, bool i
// build aicore task
auto aicore_task = std::unique_ptr<AiCoreOpTask>(new(std::nothrow)AiCoreOpTask());
GE_CHECK_NOTNULL(aicore_task);
aicore_task->SetSingleOp(is_single_op);
GE_CHK_STATUS_RET(aicore_task->Init(*op_desc_, task_defs_.back()),
"[%s] Failed to init task for AtomicAddrClean",
op_desc_->GetName().c_str());

@ -47,7 +47,7 @@ class AiCoreTaskBuilder {
AiCoreTaskBuilder(const OpDescPtr &op_desc, const std::vector<domi::TaskDef> &task_defs);
~AiCoreTaskBuilder() = default;
Status BuildTask(std::unique_ptr<NodeTask> &node_task, bool ignore_failure_on_atomic);
Status BuildTask(std::unique_ptr<NodeTask> &node_task, bool ignore_failure_on_atomic, bool is_single_op = false);
private:
bool ExpectAtomicAddrCleanTask();

@ -256,9 +256,27 @@ Status DynamicSingleOp::ExecuteAsync(const vector<GeTensorDesc> &input_desc,
const vector<DataBuffer> &input_buffers,
vector<GeTensorDesc> &output_desc,
vector<DataBuffer> &output_buffers) {
GE_CHECK_NOTNULL(op_task_);
GE_CHK_STATUS_RET_NOLOG(ValidateParams(input_desc, input_buffers, output_desc, output_buffers));
if (hybrid_model_executor_ != nullptr) {
GELOGD("Execute multi-task dynamic single op by hybrid model executor");
hybrid::HybridModelExecutor::ExecuteArgs args;
for (auto &input : input_buffers) {
args.inputs.emplace_back(hybrid::TensorValue(input.data, input.length));
}
for (auto &output : output_buffers) {
args.outputs.emplace_back(hybrid::TensorValue(output.data, output.length));
}
for (auto &tensor_desc : input_desc) {
auto desc = MakeShared<GeTensorDesc>(tensor_desc);
GE_CHECK_NOTNULL(desc);
args.input_desc.emplace_back(desc);
}
return hybrid_model_executor_->Execute(args);
}
std::lock_guard<std::mutex> lk(*stream_mutex_);
GE_CHECK_NOTNULL(op_task_);
GE_CHK_STATUS_RET_NOLOG(op_task_->LaunchKernel(input_desc, input_buffers, output_desc, output_buffers, stream_));
GE_CHK_STATUS_RET_NOLOG(ProfilingTaskInfo(op_task_.get(), kShapeTypeDynamic));

@ -28,6 +28,7 @@
#include "runtime/stream.h"
#include "task/op_task.h"
#include "cce/aicpu_engine_struct.h"
#include "hybrid/executor/hybrid_model_executor.h"
namespace ge {
class StreamResource;
@ -46,7 +47,7 @@ class SingleOp {
Status GetArgs(const std::vector<DataBuffer> &inputs, const std::vector<DataBuffer> &outputs);
friend class SingleOpModel;
StreamResource *stream_resource_;
StreamResource *stream_resource_ = nullptr;
std::mutex *stream_mutex_;
rtStream_t stream_ = nullptr;
std::vector<void *> input_addr_list_;
@ -77,6 +78,8 @@ class DynamicSingleOp {
std::vector<DataBuffer> &outputs) const;
std::unique_ptr<OpTask> op_task_;
std::unique_ptr<hybrid::HybridModel> hybrid_model_;
std::unique_ptr<hybrid::HybridModelExecutor> hybrid_model_executor_;
uintptr_t resource_id_ = 0;
std::mutex *stream_mutex_;
rtStream_t stream_ = nullptr;

@ -31,6 +31,8 @@
#include "task/aicpu_task_builder.h"
#include "task/aicpu_kernel_task_builder.h"
#include "task/tbe_task_builder.h"
#include "hybrid/executor/hybrid_model_executor.h"
#include "hybrid/node_executor/node_executor.h"
static std::atomic<std::uint64_t> aicpu_kernel_id(0);
@ -42,6 +44,20 @@ namespace ge {
namespace {
const size_t kDataOutputNum = 1;
} // namespace
static Status IfInferDepend(GeModelPtr &ge_model, bool &flag) {
auto comp_graph = GraphUtils::GetComputeGraph(ge_model->GetGraph());
for (const auto &node : comp_graph->GetAllNodes()) {
auto op_desc = node->GetOpDesc();
GE_CHECK_NOTNULL(op_desc);
const auto &depends = op_desc->GetOpInferDepends();
if (!depends.empty()) {
flag = true;
return SUCCESS;
}
}
return SUCCESS;
}
SingleOpModel::SingleOpModel(const std::string &model_name, const void *model_data, uint32_t model_size)
: model_name_(model_name), ori_model_data_(model_data), ori_model_size_(model_size) {}
@ -478,6 +494,30 @@ Status SingleOpModel::BuildDynamicOp(StreamResource &resource, DynamicSingleOp &
single_op.num_outputs_ = netoutput_op_->GetAllInputsSize();
GE_CHK_STATUS_RET_NOLOG(InitModelMem(resource));
model_params_.memory_size = UINT_MAX;
auto ge_model = model_helper_.GetGeModel();
GE_CHECK_NOTNULL(ge_model);
bool infer_depend_flag = false;
GE_CHK_STATUS_RET_NOLOG(IfInferDepend(ge_model, infer_depend_flag));
if (ge_model->GetModelTaskDefPtr()->task_size() > 1 || infer_depend_flag) {
GELOGD("Build single op HybridModel.");
GE_CHK_STATUS_RET_NOLOG(hybrid::NodeExecutorManager::GetInstance().EnsureInitialized());
auto root_model = model_helper_.GetGeRootModel();
GE_CHECK_NOTNULL(root_model);
root_model->SetRootGraph(GraphUtils::GetComputeGraph(ge_model->GetGraph()));
root_model->SetSubgraphInstanceNameToModel(root_model->GetRootGraph()->GetName(), ge_model);
single_op.hybrid_model_.reset(new (std::nothrow)hybrid::HybridModel(root_model));
GE_CHECK_NOTNULL(single_op.hybrid_model_);
GE_CHK_STATUS_RET(single_op.hybrid_model_->Init(true), "Failed to init hybrid model");
int32_t device_id = 0;
GE_CHK_RT_RET(rtGetDevice(&device_id));
single_op.hybrid_model_executor_.reset(new (std::nothrow)hybrid::HybridModelExecutor(single_op.hybrid_model_.get(),
device_id,
resource.GetStream()));
GE_CHECK_NOTNULL(single_op.hybrid_model_executor_);
GE_CHK_STATUS_RET(single_op.hybrid_model_executor_->Init(), "Failed to init hybrid model");
return SUCCESS;
}
return BuildTaskListForDynamicOp(single_op);
}
} // namespace ge

@ -61,6 +61,10 @@ DynamicSingleOp *StreamResource::GetDynamicOperator(const void *key) {
return it->second.get();
}
rtStream_t StreamResource::GetStream() const {
return stream_;
}
void StreamResource::SetStream(rtStream_t stream) {
stream_ = stream;
}

@ -37,6 +37,7 @@ class StreamResource {
StreamResource(StreamResource &&) = delete;
StreamResource &operator=(const StreamResource &) = delete;
StreamResource &operator=(StreamResource &&) = delete;
rtStream_t GetStream() const;
void SetStream(rtStream_t stream);
SingleOp *GetOperator(const void *key);

@ -562,6 +562,46 @@ set(SINGLE_OP_SRC_FILES
"${GE_CODE_DIR}/ge/single_op/single_op_manager.cc"
"${GE_CODE_DIR}/ge/single_op/task/aicpu_task_builder.cc"
"${GE_CODE_DIR}/ge/single_op/task/aicpu_kernel_task_builder.cc"
"${GE_CODE_DIR}/ge/hybrid/common/tensor_value.cc"
"${GE_CODE_DIR}/ge/hybrid/common/npu_memory_allocator.cc"
"${GE_CODE_DIR}/ge/hybrid/executor/rt_callback_manager.cc"
"${GE_CODE_DIR}/ge/hybrid/executor/node_state.cc"
"${GE_CODE_DIR}/ge/hybrid/executor/node_done_manager.cc"
"${GE_CODE_DIR}/ge/hybrid/executor/hybrid_profiler.cc"
"${GE_CODE_DIR}/ge/hybrid/executor/hybrid_model_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/executor/hybrid_model_async_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/executor/hybrid_execution_context.cc"
"${GE_CODE_DIR}/ge/hybrid/executor/subgraph_context.cc"
"${GE_CODE_DIR}/ge/hybrid/executor/subgraph_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/executor/worker/task_compile_engine.cc"
"${GE_CODE_DIR}/ge/hybrid/executor/worker/shape_inference_engine.cc"
"${GE_CODE_DIR}/ge/hybrid/executor/worker/execution_engine.cc"
"${GE_CODE_DIR}/ge/hybrid/model/hybrid_model.cc"
"${GE_CODE_DIR}/ge/hybrid/model/hybrid_model_builder.cc"
"${GE_CODE_DIR}/ge/hybrid/model/node_item.cc"
"${GE_CODE_DIR}/ge/hybrid/model/graph_item.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/aicore/aicore_node_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/aicore/aicore_op_task.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/aicore/aicore_task_builder.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/aicore/aicore_task_compiler.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/aicpu/aicpu_ext_info.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/aicpu/aicpu_node_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/compiledsubgraph/known_node_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/ge_local/ge_local_node_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/host_cpu/host_cpu_node_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/host_cpu/kernel_factory.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/host_cpu/kernel/no_op_kernel.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/host_cpu/kernel/variable_kernel.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/host_cpu/kernel/assign_kernel.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/host_cpu/kernel/random_uniform_kernel.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/host_cpu/kernel/data_kernel.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/controlop/control_op_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/partitioned_call/partitioned_call_node_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/hccl/hccl_node_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/rts/rts_node_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/node_executor.cc"
"${GE_CODE_DIR}/ge/hybrid/node_executor/task_context.cc"
"${GE_CODE_DIR}/ge/hybrid/hybrid_davinci_model.cc"
)
# test files

@ -17,7 +17,6 @@
#include <gtest/gtest.h>
#include <vector>
#include "cce/taskdown_common.hpp"
#include "runtime/rt.h"
#define protected public

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