@@ -21,6 +21,7 @@ | |||||
#include "framework/common/string_util.h" | #include "framework/common/string_util.h" | ||||
#include "graph/ge_context.h" | #include "graph/ge_context.h" | ||||
#include "runtime/base.h" | #include "runtime/base.h" | ||||
#include "graph/load/new_model_manager/davinci_model.h" | |||||
namespace { | namespace { | ||||
const char *const kJobID = "jobID"; | const char *const kJobID = "jobID"; | ||||
@@ -39,10 +40,12 @@ const std::string kConfigNumsdev = "devNums"; | |||||
const std::string kConfigDevIdList = "devIdList"; | const std::string kConfigDevIdList = "devIdList"; | ||||
const std::string kProfStart = "prof_start"; | const std::string kProfStart = "prof_start"; | ||||
const std::string kProfStop = "prof_stop"; | const std::string kProfStop = "prof_stop"; | ||||
const std::string kProfModelSubscribe = "prof_model_subscribe"; | |||||
const std::string kProfModelUnsubscribe = "prof_model_cancel_subscribe"; | |||||
} // namespace | } // namespace | ||||
namespace ge { | namespace ge { | ||||
ProfilingManager::ProfilingManager() {} | |||||
ProfilingManager::ProfilingManager() : subscribe_count_(0) {} | |||||
ProfilingManager::~ProfilingManager() {} | ProfilingManager::~ProfilingManager() {} | ||||
@@ -54,6 +57,7 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY ProfilingManager &ProfilingMana | |||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY ge::Status ProfilingManager::Init(const Options &options) { | FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY ge::Status ProfilingManager::Init(const Options &options) { | ||||
#ifdef DAVINCI_SUPPORT_PROFILING | #ifdef DAVINCI_SUPPORT_PROFILING | ||||
vector<int32_t>().swap(device_id_); | vector<int32_t>().swap(device_id_); | ||||
subscribe_count_ = 0; | |||||
job_id_ = options.job_id; | job_id_ = options.job_id; | ||||
GELOGI("ProfilingManager::Init job_id:%s", job_id_.c_str()); | GELOGI("ProfilingManager::Init job_id:%s", job_id_.c_str()); | ||||
@@ -382,7 +386,7 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::StopProf | |||||
} | } | ||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::ProfilingTaskDescInfo( | FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::ProfilingTaskDescInfo( | ||||
const std::vector<TaskDescInfo> &task_desc_info, const int32_t &device_id) { | |||||
uint32_t model_id, const std::vector<TaskDescInfo> &task_desc_info, const int32_t &device_id) { | |||||
#ifdef DAVINCI_SUPPORT_PROFILING | #ifdef DAVINCI_SUPPORT_PROFILING | ||||
Msprof::Engine::Reporter *reporter = PluginImpl::GetPluginReporter(); | Msprof::Engine::Reporter *reporter = PluginImpl::GetPluginReporter(); | ||||
if (reporter == nullptr) { | if (reporter == nullptr) { | ||||
@@ -401,7 +405,8 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::Profilin | |||||
.append(op_name).append(" ") | .append(op_name).append(" ") | ||||
.append(std::to_string(block_dim).append(" ") | .append(std::to_string(block_dim).append(" ") | ||||
.append(std::to_string(task_id)).append(" ") | .append(std::to_string(task_id)).append(" ") | ||||
.append(std::to_string(stream_id)).append("\n")); | |||||
.append(std::to_string(stream_id)).append(" ") | |||||
.append(std::to_string(model_id)).append("\n")); | |||||
Msprof::Engine::ReporterData reporter_data{}; | Msprof::Engine::ReporterData reporter_data{}; | ||||
reporter_data.deviceId = device_id; | reporter_data.deviceId = device_id; | ||||
@@ -425,7 +430,7 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::Profilin | |||||
} | } | ||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::ProfilingGraphDescInfo( | FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::ProfilingGraphDescInfo( | ||||
const std::vector<ComputeGraphDescInfo> &compute_graph_desc_info, const int32_t &device_id) { | |||||
uint32_t model_id, const std::vector<ComputeGraphDescInfo> &compute_graph_desc_info, const int32_t &device_id) { | |||||
#ifdef DAVINCI_SUPPORT_PROFILING | #ifdef DAVINCI_SUPPORT_PROFILING | ||||
Msprof::Engine::Reporter *reporter = PluginImpl::GetPluginReporter(); | Msprof::Engine::Reporter *reporter = PluginImpl::GetPluginReporter(); | ||||
GE_IF_BOOL_EXEC(reporter == nullptr, GELOGI("Profiling report is nullptr!"); return;); | GE_IF_BOOL_EXEC(reporter == nullptr, GELOGI("Profiling report is nullptr!"); return;); | ||||
@@ -483,6 +488,8 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::Profilin | |||||
data.append("\""); | data.append("\""); | ||||
} | } | ||||
data.append(" model_id:").append(std::to_string(model_id)); | |||||
data.append("\n"); | data.append("\n"); | ||||
Msprof::Engine::ReporterData reporter_data{}; | Msprof::Engine::ReporterData reporter_data{}; | ||||
@@ -537,7 +544,9 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::PluginUn | |||||
} | } | ||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::ReportProfilingData( | FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::ReportProfilingData( | ||||
const std::vector<TaskDescInfo> &task_desc_info, const std::vector<ComputeGraphDescInfo> &compute_graph_desc_info) { | |||||
uint32_t model_id, const std::vector<TaskDescInfo> &task_desc_info, | |||||
const std::vector<ComputeGraphDescInfo> &compute_graph_desc_info, | |||||
bool check_device) { | |||||
#ifdef DAVINCI_SUPPORT_PROFILING | #ifdef DAVINCI_SUPPORT_PROFILING | ||||
int32_t logic_device_id = 0; | int32_t logic_device_id = 0; | ||||
rtError_t rt_ret = rtGetDevice(&logic_device_id); | rtError_t rt_ret = rtGetDevice(&logic_device_id); | ||||
@@ -546,7 +555,7 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::ReportPr | |||||
return; | return; | ||||
} | } | ||||
GELOGI("current logic_device_id:%d", logic_device_id); | GELOGI("current logic_device_id:%d", logic_device_id); | ||||
if (!is_acl_api_mode_) { | |||||
if (check_device) { | |||||
auto ret = std::find(device_id_.begin(), device_id_.end(), logic_device_id); | auto ret = std::find(device_id_.begin(), device_id_.end(), logic_device_id); | ||||
if (ret == device_id_.end()) { | if (ret == device_id_.end()) { | ||||
GELOGE(FAILED, "get valid phy_device_id failed, profiling report failed."); | GELOGE(FAILED, "get valid phy_device_id failed, profiling report failed."); | ||||
@@ -554,9 +563,9 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::ReportPr | |||||
} | } | ||||
} | } | ||||
GELOGI("start ProfilingTaskDescInfo."); | GELOGI("start ProfilingTaskDescInfo."); | ||||
ProfilingTaskDescInfo(task_desc_info, logic_device_id); | |||||
ProfilingTaskDescInfo(model_id, task_desc_info, logic_device_id); | |||||
GELOGI("start ProfilingGraphDescInfo."); | GELOGI("start ProfilingGraphDescInfo."); | ||||
ProfilingGraphDescInfo(compute_graph_desc_info, logic_device_id); | |||||
ProfilingGraphDescInfo(model_id, compute_graph_desc_info, logic_device_id); | |||||
GELOGI("Report profiling data for GE end."); | GELOGI("Report profiling data for GE end."); | ||||
#endif | #endif | ||||
} | } | ||||
@@ -581,6 +590,105 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY uint64_t ProfilingManager::GetP | |||||
return module; | return module; | ||||
} | } | ||||
void ProfilingManager::UpdateSubscribeDeviceModuleMap(std::string prof_type, | |||||
uint32_t device_id, | |||||
uint64_t module) { | |||||
#ifdef DAVINCI_SUPPORT_PROFILING | |||||
if (prof_type == kProfModelSubscribe) { | |||||
if (subs_dev_module_.find(device_id) != subs_dev_module_.end()) { | |||||
subs_dev_module_[device_id].subscribe_count++; | |||||
} else { | |||||
DeviceSubsInfo dev_info; | |||||
dev_info.module = module; | |||||
dev_info.subscribe_count = 1; | |||||
subs_dev_module_[device_id] = dev_info; | |||||
} | |||||
} else if (prof_type == kProfModelUnsubscribe) { | |||||
if (subs_dev_module_.find(device_id) != subs_dev_module_.end()) { | |||||
if (subs_dev_module_[device_id].subscribe_count > 0) { | |||||
subs_dev_module_[device_id].subscribe_count--; | |||||
} | |||||
} | |||||
} else { | |||||
GELOGI("No need to update device_id module map."); | |||||
} | |||||
#endif | |||||
} | |||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::ProfModelSubscribe( | |||||
uint64_t module, void *model) { | |||||
#ifdef DAVINCI_SUPPORT_PROFILING | |||||
std::lock_guard<std::mutex> lock(mutex_); | |||||
uint64_t model_load_mask = module & PROF_MODEL_LOAD_MASK; | |||||
if ((subscribe_count_ == 0) && (model_load_mask == PROF_MODEL_LOAD_MASK)) { | |||||
// register framework to profiling | |||||
int32_t result = Msprof::Engine::Init(GE_PROFILING_MODULE, &engine_); | |||||
if (result != SUCCESS) { | |||||
GELOGE(FAILED, "Register profiling engine failed."); | |||||
return FAILED; | |||||
} | |||||
GELOGI("Prof subscribe: model load profiling on."); | |||||
} | |||||
subscribe_count_++; | |||||
auto davinci_model = static_cast<DavinciModel *>(model); | |||||
int32_t device_num = 1; | |||||
uint32_t device[1]; | |||||
device[0] = davinci_model->GetDeviceId(); | |||||
rtError_t rt_ret = rtProfilerStart(module, device_num, device); | |||||
if (rt_ret != RT_ERROR_NONE) { | |||||
GELOGE(FAILED, "Runtime profiler start failed."); | |||||
return FAILED; | |||||
} | |||||
UpdateSubscribeDeviceModuleMap(kProfModelSubscribe, device[0], module); | |||||
// Report profiling data | |||||
Status p_ret = davinci_model->ReportProfilingData(false); | |||||
if (p_ret != SUCCESS) { | |||||
GELOGE(p_ret, "Report profiling data failed."); | |||||
return p_ret; | |||||
} | |||||
#endif | |||||
return SUCCESS; | |||||
} | |||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::ProfModelUnsubscribe( | |||||
void *model) { | |||||
#ifdef DAVINCI_SUPPORT_PROFILING | |||||
std::lock_guard<std::mutex> lock(mutex_); | |||||
if (subscribe_count_ == 0) { | |||||
GELOGW("The profiler has not been subscribed, you do not need to cannel the subscription."); | |||||
return SUCCESS; | |||||
} | |||||
auto davinci_model = static_cast<DavinciModel *>(model); | |||||
int32_t dev_num = 1; | |||||
uint32_t device[1]; | |||||
device[0] = davinci_model->GetDeviceId(); | |||||
auto iter = subs_dev_module_.find(device[0]); | |||||
if (iter != subs_dev_module_.end()) { | |||||
if (subs_dev_module_[device[0]].subscribe_count == 1) { | |||||
rtError_t rt_ret = rtProfilerStop(subs_dev_module_[device[0]].module, dev_num, device); | |||||
if (rt_ret != RT_ERROR_NONE) { | |||||
GELOGE(FAILED, "Runtime profiler stop failed."); | |||||
return FAILED; | |||||
} | |||||
} | |||||
UpdateSubscribeDeviceModuleMap(kProfModelUnsubscribe, device[0], subs_dev_module_[device[0]].module); | |||||
} | |||||
subscribe_count_--; | |||||
if (subscribe_count_ == 0) { | |||||
int32_t ret = Msprof::Engine::UnInit(GE_PROFILING_MODULE); | |||||
if (ret != SUCCESS) { | |||||
GELOGE(ret, "Profiling plugin uninit failed, ret:%d", ret); | |||||
return ret; | |||||
} | |||||
} | |||||
#endif | |||||
return SUCCESS; | |||||
} | |||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::ProfInit(uint64_t module) { | FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::ProfInit(uint64_t module) { | ||||
#ifdef DAVINCI_SUPPORT_PROFILING | #ifdef DAVINCI_SUPPORT_PROFILING | ||||
std::lock_guard<std::mutex> lock(mutex_); | std::lock_guard<std::mutex> lock(mutex_); | ||||
@@ -748,6 +856,7 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::ProfSt | |||||
device_id_ptr[i] = static_cast<uint32_t>(device_list[i]); | device_id_ptr[i] = static_cast<uint32_t>(device_list[i]); | ||||
} | } | ||||
GELOGI("Runtime config param: 0x%llx, device num: %d.", module, device_num); | GELOGI("Runtime config param: 0x%llx, device num: %d.", module, device_num); | ||||
rtError_t rt_ret = rtProfilerStart(module, device_num, device_id_ptr.get()); | rtError_t rt_ret = rtProfilerStart(module, device_num, device_id_ptr.get()); | ||||
if (rt_ret != RT_ERROR_NONE) { | if (rt_ret != RT_ERROR_NONE) { | ||||
GELOGE(FAILED, "Runtime profiler config proc failed."); | GELOGE(FAILED, "Runtime profiler config proc failed."); | ||||
@@ -39,6 +39,10 @@ namespace { | |||||
const std::string GE_PROFILING_MODULE = "Framework"; | const std::string GE_PROFILING_MODULE = "Framework"; | ||||
} // namespace | } // namespace | ||||
namespace ge { | namespace ge { | ||||
struct DeviceSubsInfo { | |||||
uint64_t module; | |||||
uint32_t subscribe_count; | |||||
}; | |||||
// register Plugin | // register Plugin | ||||
class FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY PluginImpl : public Msprof::Engine::PluginIntf { | class FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY PluginImpl : public Msprof::Engine::PluginIntf { | ||||
public: | public: | ||||
@@ -73,6 +77,9 @@ class FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY ProfilingManager { | |||||
ge::Status InitFromOptions(const Options &options); | ge::Status InitFromOptions(const Options &options); | ||||
ge::Status InitFromAclCfg(const std::string &config); | ge::Status InitFromAclCfg(const std::string &config); | ||||
ge::Status StartProfiling(int32_t iter, int32_t device_id); | ge::Status StartProfiling(int32_t iter, int32_t device_id); | ||||
void UpdateSubscribeDeviceModuleMap(std::string prof_type, uint32_t device_id, uint64_t module); | |||||
ge::Status ProfModelSubscribe(uint64_t module, void *model); | |||||
ge::Status ProfModelUnsubscribe(void *model); | |||||
ge::Status ProfInit(uint64_t module); | ge::Status ProfInit(uint64_t module); | ||||
ge::Status ProfFinalize(); | ge::Status ProfFinalize(); | ||||
ge::Status ProfStartProfiling(uint64_t module, const std::map<std::string, std::string> &config_para); | ge::Status ProfStartProfiling(uint64_t module, const std::map<std::string, std::string> &config_para); | ||||
@@ -84,13 +91,16 @@ class FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY ProfilingManager { | |||||
bool ProfilingModelLoadOn() const { return is_load_profiling_; } | bool ProfilingModelLoadOn() const { return is_load_profiling_; } | ||||
bool ProfilingModelExecuteOn() const; | bool ProfilingModelExecuteOn() const; | ||||
bool ProfilingOn() const { return is_load_profiling_ && is_execute_profiling_; } // only used by command pattern | bool ProfilingOn() const { return is_load_profiling_ && is_execute_profiling_; } // only used by command pattern | ||||
bool IsAclApiMode() const { return is_acl_api_mode_; } | |||||
int32_t GetOpTraceIterNum() const { return op_trace_iter_num_; } | int32_t GetOpTraceIterNum() const { return op_trace_iter_num_; } | ||||
void ReportProfilingData(const std::vector<TaskDescInfo> &task_desc_info, | |||||
const std::vector<ComputeGraphDescInfo> &compute_graph_desc_info); | |||||
void ReportProfilingData(uint32_t model_id, const std::vector<TaskDescInfo> &task_desc_info, | |||||
const std::vector<ComputeGraphDescInfo> &compute_graph_desc_info, | |||||
bool check_device); | |||||
void Report(const int32_t &device_id, const string &data, Msprof::Engine::Reporter &reporter, | void Report(const int32_t &device_id, const string &data, Msprof::Engine::Reporter &reporter, | ||||
Msprof::Engine::ReporterData &reporter_data); | Msprof::Engine::ReporterData &reporter_data); | ||||
void ProfilingTaskDescInfo(const std::vector<TaskDescInfo> &task_desc_info, const int32_t &device_id); | |||||
void ProfilingGraphDescInfo(const std::vector<ComputeGraphDescInfo> &compute_graph_desc_info, | |||||
void ProfilingTaskDescInfo(uint32_t model_id, const std::vector<TaskDescInfo> &task_desc_info, | |||||
const int32_t &device_id); | |||||
void ProfilingGraphDescInfo(uint32_t model_id, const std::vector<ComputeGraphDescInfo> &compute_graph_desc_info, | |||||
const int32_t &device_id); | const int32_t &device_id); | ||||
void SetProfilingConfig(const string &profiling_cfg); | void SetProfilingConfig(const string &profiling_cfg); | ||||
vector<int32_t> GetProfilingDeviceId() const { return device_id_; } | vector<int32_t> GetProfilingDeviceId() const { return device_id_; } | ||||
@@ -122,6 +132,8 @@ class FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY ProfilingManager { | |||||
string task_trace_conf_; | string task_trace_conf_; | ||||
const ProfilingEngineImpl engine_; | const ProfilingEngineImpl engine_; | ||||
map<int32_t, uint64_t> device_id_module_map_; // key: device_id, value: profiling on module | map<int32_t, uint64_t> device_id_module_map_; // key: device_id, value: profiling on module | ||||
map<uint32_t, DeviceSubsInfo> subs_dev_module_; // key: device_id, value: profiling on module | |||||
uint32_t subscribe_count_; | |||||
std::mutex mutex_; | std::mutex mutex_; | ||||
}; | }; | ||||
} // namespace ge | } // namespace ge | ||||
@@ -54,6 +54,7 @@ const std::map<std::string, std::string> PROFILE_COMPONENT_MAP{ | |||||
{"runtime", RTS_PROFILE}, | {"runtime", RTS_PROFILE}, | ||||
}; | }; | ||||
const std::string PROFILE_CONFIG = "config"; | const std::string PROFILE_CONFIG = "config"; | ||||
const std::string PROFILE_MODEL_ID = "modelId"; | |||||
REGISTER_OPTYPE_DEFINE(DATA, "Data"); | REGISTER_OPTYPE_DEFINE(DATA, "Data"); | ||||
REGISTER_OPTYPE_DEFINE(AIPPDATA, "AippData"); | REGISTER_OPTYPE_DEFINE(AIPPDATA, "AippData"); | ||||
@@ -1062,6 +1062,19 @@ Status GeExecutor::ReleaseSingleOpResource(void *stream) { | |||||
return SingleOpManager::GetInstance().ReleaseResource(stream); | return SingleOpManager::GetInstance().ReleaseResource(stream); | ||||
} | } | ||||
Status GeExecutor::GetDeviceIdByModelId(uint32_t model_id, uint32_t &device_id) { | |||||
auto model_manager = ModelManager::GetInstance(); | |||||
GE_CHECK_NOTNULL(model_manager); | |||||
auto davinci_model = model_manager->GetModel(model_id); | |||||
if (davinci_model == nullptr) { | |||||
GELOGE(FAILED, "Model id: %d is invaild or model is not loaded.", model_id); | |||||
return FAILED; | |||||
} | |||||
device_id = davinci_model->GetDeviceId(); | |||||
return SUCCESS; | |||||
} | |||||
Status GeExecutor::GetBatchInfoSize(uint32_t model_id, size_t &shape_count) { | Status GeExecutor::GetBatchInfoSize(uint32_t model_id, size_t &shape_count) { | ||||
std::vector<std::vector<int64_t>> batch_info; | std::vector<std::vector<int64_t>> batch_info; | ||||
int32_t dynamic_type = static_cast<int32_t>(FIXED); | int32_t dynamic_type = static_cast<int32_t>(FIXED); | ||||
@@ -32,11 +32,6 @@ Status LabelAllocator::AssignFunctionalLabels() { | |||||
return INTERNAL_ERROR; | return INTERNAL_ERROR; | ||||
} | } | ||||
if (compute_graph_->GetGraphUnknownFlag()) { | |||||
GELOGD("Graph[%s] is unknown graph, skip label allocator.", compute_graph_->GetName().c_str()); | |||||
return SUCCESS; | |||||
} | |||||
// Add label task for sub graph. | // Add label task for sub graph. | ||||
GELOGI("AssignFunctionalLabels start: %s.", compute_graph_->GetName().c_str()); | GELOGI("AssignFunctionalLabels start: %s.", compute_graph_->GetName().c_str()); | ||||
std::set<NodePtr> functional_nodes; | std::set<NodePtr> functional_nodes; | ||||
@@ -62,7 +57,7 @@ Status LabelAllocator::AssignFunctionalLabels() { | |||||
} | } | ||||
(void)AttrUtils::SetInt(*compute_graph_, ATTR_MODEL_LABEL_NUM, label_index); | (void)AttrUtils::SetInt(*compute_graph_, ATTR_MODEL_LABEL_NUM, label_index); | ||||
GELOGI("AssignFunctionalLabels success."); | |||||
GELOGI("AssignFunctionalLabels success, Num: %u.", label_index); | |||||
return SUCCESS; | return SUCCESS; | ||||
} | } | ||||
@@ -72,13 +67,29 @@ bool LabelAllocator::CollectFunctionalNode(ComputeGraphPtr &graph, std::set<Node | |||||
return false; | return false; | ||||
} | } | ||||
NodePtr parent = graph->GetParentNode(); | |||||
if (parent == nullptr) { | |||||
GELOGE(INTERNAL_ERROR, "ComputeGraph owner not set: %s.", graph->GetName().c_str()); | |||||
if (graph->GetGraphUnknownFlag()) { | |||||
GELOGD("Graph[%s] is unknown graph, skip label allocator.", graph->GetName().c_str()); | |||||
return true; | |||||
} | |||||
NodePtr func_node = graph->GetParentNode(); | |||||
if (func_node == nullptr) { | |||||
GELOGE(INTERNAL_ERROR, "Parent functional node not set: %s.", graph->GetName().c_str()); | |||||
return false; | return false; | ||||
} | } | ||||
(void)functional_nodes.insert(parent); // unique functional node. | |||||
ComputeGraphPtr owner_graph = func_node->GetOwnerComputeGraph(); | |||||
if (owner_graph == nullptr) { | |||||
GELOGE(INTERNAL_ERROR, "ComputeGraph owner not set: %s.", func_node->GetName().c_str()); | |||||
return false; | |||||
} | |||||
if (owner_graph->GetGraphUnknownFlag()) { | |||||
GELOGD("Graph[%s] is unknown graph, skip label allocator.", owner_graph->GetName().c_str()); | |||||
return true; | |||||
} | |||||
(void)functional_nodes.insert(func_node); // unique functional node. | |||||
return true; | return true; | ||||
} | } | ||||
} // namespace ge | } // namespace ge |
@@ -880,6 +880,15 @@ MemoryBlock *BlockMemAssigner::ApplyMemory(size_t block_size, size_t real_size, | |||||
GELOGI("Unreusable block."); | GELOGI("Unreusable block."); | ||||
continue; | continue; | ||||
} | } | ||||
std::string batch_label; | |||||
if (reusable_block->IsSameLabel(batch_label)) { | |||||
std::string op_label; | |||||
(void)ge::AttrUtils::GetStr(node_op_desc, ATTR_NAME_BATCH_LABEL, op_label); | |||||
if (batch_label != op_label) { | |||||
GELOGI("label diff, op name %s", node_op_desc->GetName().c_str()); | |||||
continue; | |||||
} | |||||
} | |||||
// A node can reuse blocks of the same stream and preorder streams | // A node can reuse blocks of the same stream and preorder streams | ||||
if (CanReuseBySize(reusable_block_counts_, *reusable_block, block_size, real_size, continuous)) { | if (CanReuseBySize(reusable_block_counts_, *reusable_block, block_size, real_size, continuous)) { | ||||
@@ -416,6 +416,14 @@ Status ModelBuilder::BuildModelDef(ge::Model &model) { | |||||
return FAILED); | return FAILED); | ||||
GELOGI("For model, max_mem_offset_: %zu, p2p_mem_size: %zu, zero_copy_mem_size_: %zu", max_mem_offset_, | GELOGI("For model, max_mem_offset_: %zu, p2p_mem_size: %zu, zero_copy_mem_size_: %zu", max_mem_offset_, | ||||
p2p_mem_offset_, zero_copy_mem_size_); | p2p_mem_offset_, zero_copy_mem_size_); | ||||
string fp_ceiling_mode; | |||||
if (ge::GetContext().GetOption("ge.fpCeilingMode", fp_ceiling_mode) == SUCCESS) { | |||||
if (!ge::AttrUtils::SetStr(&model, ATTR_FP_CEILING_MODE, fp_ceiling_mode)) { | |||||
GELOGE(FAILED, "Failed to set attr ATTR_FP_CEILING_MODE"); | |||||
return FAILED; | |||||
} | |||||
GELOGI("Set attr ATTR_FP_CEILING_MODE to model, value is %s.", fp_ceiling_mode.c_str()); | |||||
} | |||||
string ge_core_type; | string ge_core_type; | ||||
Status ret = ge::GetContext().GetOption(kCoreType, ge_core_type); | Status ret = ge::GetContext().GetOption(kCoreType, ge_core_type); | ||||
@@ -690,8 +698,8 @@ Status ModelBuilder::BuildModelForGetTask(ge::Model &model) { | |||||
GE_TIMESTAMP_END(AssignLogicalStreams, "GraphBuilder::AssignLogicalStreams"); | GE_TIMESTAMP_END(AssignLogicalStreams, "GraphBuilder::AssignLogicalStreams"); | ||||
// Assign functional op labels. | // Assign functional op labels. | ||||
label_num_ = 0; | |||||
(void)AttrUtils::GetInt(*compute_graph_, ATTR_MODEL_LABEL_NUM, label_num_); | |||||
auto root_graph = GraphUtils::FindRootGraph(compute_graph_); | |||||
(void)AttrUtils::GetInt(*root_graph, ATTR_MODEL_LABEL_NUM, label_num_); | |||||
GE_TIMESTAMP_START(AssignMemory); | GE_TIMESTAMP_START(AssignMemory); | ||||
MemoryAssigner mem_assigner(compute_graph_); | MemoryAssigner mem_assigner(compute_graph_); | ||||
@@ -82,4 +82,13 @@ bool TransOpUtil::CheckPrecisionLoss(const ge::NodePtr &src_node) { | |||||
} | } | ||||
return true; | return true; | ||||
} | } | ||||
std::string TransOpUtil::TransopMapToString() { | |||||
std::string buffer; | |||||
for (auto &key : Instance().transop_index_map_) { | |||||
buffer += key.first + " "; | |||||
} | |||||
return buffer; | |||||
} | |||||
} // namespace ge | } // namespace ge |
@@ -35,6 +35,8 @@ class GE_FUNC_HOST_VISIBILITY GE_FUNC_DEV_VISIBILITY TransOpUtil { | |||||
static bool CheckPrecisionLoss(const NodePtr &src_node); | static bool CheckPrecisionLoss(const NodePtr &src_node); | ||||
static std::string TransopMapToString(); | |||||
private: | private: | ||||
TransOpUtil(); | TransOpUtil(); | ||||
@@ -86,6 +86,7 @@ class DataDumper { | |||||
void SetDumpProperties(const DumpProperties &dump_properties) { dump_properties_ = dump_properties; } | void SetDumpProperties(const DumpProperties &dump_properties) { dump_properties_ = dump_properties; } | ||||
const DumpProperties &GetDumpProperties() const { return dump_properties_; } | const DumpProperties &GetDumpProperties() const { return dump_properties_; } | ||||
bool GetOpDescInfo(uint32_t stream_id, uint32_t task_id, OpDescInfo &op_desc_info) const; | bool GetOpDescInfo(uint32_t stream_id, uint32_t task_id, OpDescInfo &op_desc_info) const; | ||||
const std::vector<OpDescInfo> &GetAllOpDescInfo() const { return op_desc_info_; } | |||||
// Dump exception info | // Dump exception info | ||||
Status DumpExceptionInput(const OpDescInfo &op_desc_info, const string &dump_file); | Status DumpExceptionInput(const OpDescInfo &op_desc_info, const string &dump_file); | ||||
@@ -88,6 +88,7 @@ const uint32_t kDataMemAlignSizeCompare = 64; | |||||
const uint32_t kDumpL1FusionOpMByteSize = 2 * 1024 * 1024; | const uint32_t kDumpL1FusionOpMByteSize = 2 * 1024 * 1024; | ||||
const uint32_t kDumpFlagOfL1Fusion = 0; | const uint32_t kDumpFlagOfL1Fusion = 0; | ||||
const char *const kDefaultBatchLable = "Batch_default"; | const char *const kDefaultBatchLable = "Batch_default"; | ||||
const int32_t kInvalidStream = -1; | |||||
inline bool IsDataOp(const std::string &node_type) { | inline bool IsDataOp(const std::string &node_type) { | ||||
return node_type == DATA_TYPE || node_type == AIPP_DATA_TYPE || node_type == ANN_DATA_TYPE; | return node_type == DATA_TYPE || node_type == AIPP_DATA_TYPE || node_type == ANN_DATA_TYPE; | ||||
@@ -258,7 +259,6 @@ Status DavinciModel::Assign(const GeModelPtr &ge_model) { | |||||
/// | /// | ||||
void DavinciModel::Shrink() { | void DavinciModel::Shrink() { | ||||
ge_model_.reset(); // delete object. | ge_model_.reset(); // delete object. | ||||
op_list_.clear(); | |||||
} | } | ||||
Status DavinciModel::InitModelMem(void *dev_ptr, size_t mem_size, void *weight_ptr, size_t weight_size) { | Status DavinciModel::InitModelMem(void *dev_ptr, size_t mem_size, void *weight_ptr, size_t weight_size) { | ||||
@@ -611,7 +611,9 @@ Status DavinciModel::Init(void *dev_ptr, size_t mem_size, void *weight_ptr, size | |||||
GE_DISMISS_GUARD(stream); | GE_DISMISS_GUARD(stream); | ||||
stream_list_.push_back(stream); | stream_list_.push_back(stream); | ||||
GELOGD("Stream index:%u, stream:%p.", i, stream); | |||||
int32_t rt_stream_id = kInvalidStream; | |||||
(void)rtGetStreamId(stream, &rt_stream_id); | |||||
GELOGI("Logical stream index:%u, stream:%p, rtstream: %d.", i, stream, rt_stream_id); | |||||
} | } | ||||
for (uint32_t i = 0; i < EventNum(); i++) { | for (uint32_t i = 0; i < EventNum(); i++) { | ||||
@@ -653,18 +655,6 @@ Status DavinciModel::Init(void *dev_ptr, size_t mem_size, void *weight_ptr, size | |||||
GE_IF_BOOL_EXEC(IsBroadCastOpData(node), | GE_IF_BOOL_EXEC(IsBroadCastOpData(node), | ||||
(void)ge::AttrUtils::SetStr(op_desc, VAR_ATTR_VAR_IS_BROADCAST, "var_is_restore");); | (void)ge::AttrUtils::SetStr(op_desc, VAR_ATTR_VAR_IS_BROADCAST, "var_is_restore");); | ||||
} | } | ||||
// for profiling | |||||
op_name_map_ = compute_graph->GetGraphOpName(); | |||||
vector<string> op_name; | |||||
GE_IF_BOOL_EXEC(ge::AttrUtils::GetListStr(ge_model_, ATTR_MODEL_TASK_INDEX_OP_NAME, op_name), | |||||
GELOGI("get str of task_index_op_name")); | |||||
if (op_name_map_.empty()) { | |||||
for (size_t idx = 0; idx < op_name.size(); idx++) { | |||||
op_name_map_[idx] = op_name[idx]; | |||||
} | |||||
GELOGI("Infer profiling: op_name_size(%zu)", op_name.size()); | |||||
} | |||||
GE_CHK_STATUS_RET(InitNodes(compute_graph), "Init nodes failed"); | GE_CHK_STATUS_RET(InitNodes(compute_graph), "Init nodes failed"); | ||||
@@ -676,7 +666,9 @@ Status DavinciModel::Init(void *dev_ptr, size_t mem_size, void *weight_ptr, size | |||||
auto all_dump_model = GetDumpProperties().GetAllDumpModel(); | auto all_dump_model = GetDumpProperties().GetAllDumpModel(); | ||||
bool findByOmName = all_dump_model.find(om_name_) != all_dump_model.end(); | bool findByOmName = all_dump_model.find(om_name_) != all_dump_model.end(); | ||||
bool findByModelName = all_dump_model.find(name_) != all_dump_model.end(); | bool findByModelName = all_dump_model.find(name_) != all_dump_model.end(); | ||||
if (all_dump_model.find(ge::DUMP_ALL_MODEL) != all_dump_model.end() || findByOmName || findByModelName) { | |||||
bool dump_l1fusion_op = (all_dump_model.find(ge::DUMP_ALL_MODEL) != all_dump_model.end()) || | |||||
findByOmName || findByModelName; | |||||
if (dump_l1fusion_op) { | |||||
// malloc 2M for dump l1fusion op | // malloc 2M for dump l1fusion op | ||||
GE_CHK_RT_RET(rtMalloc(&l1_fusion_addr_, kDumpL1FusionOpMByteSize, RT_MEMORY_DDR)); | GE_CHK_RT_RET(rtMalloc(&l1_fusion_addr_, kDumpL1FusionOpMByteSize, RT_MEMORY_DDR)); | ||||
@@ -690,16 +682,21 @@ Status DavinciModel::Init(void *dev_ptr, size_t mem_size, void *weight_ptr, size | |||||
need_destroy_aicpu_kernel_ = IsAicpuKernelConnectSpecifiedLayer(); | need_destroy_aicpu_kernel_ = IsAicpuKernelConnectSpecifiedLayer(); | ||||
(void)ge::AttrUtils::GetListStr(ge_model_, ATTR_MODEL_OUT_NODES_NAME, out_node_name_); | (void)ge::AttrUtils::GetListStr(ge_model_, ATTR_MODEL_OUT_NODES_NAME, out_node_name_); | ||||
string fp_ceiling_mode; | |||||
if (ge::AttrUtils::GetStr(ge_model_, ATTR_FP_CEILING_MODE, fp_ceiling_mode)) { | |||||
GELOGI("Get attr ATTR_FP_CEILING_MODE from model, value is %s.", fp_ceiling_mode.c_str()); | |||||
// mode 0: Do not perform saturation processing. By default, IEEE754 is used. | |||||
GE_CHK_RT_RET(rtSetCtxINFMode((fp_ceiling_mode != "0"))); | |||||
} | |||||
// collect profiling for ge | // collect profiling for ge | ||||
if (ProfilingManager::Instance().ProfilingModelLoadOn()) { | |||||
std::vector<ComputeGraphDescInfo> compute_graph_desc_info; | |||||
Status ret1 = GetComputeGraphInfo(compute_graph, compute_graph_desc_info); | |||||
if (ret1 != SUCCESS) { | |||||
GELOGE(ret1, "GetComputeGraphInfo failed."); | |||||
return ret1; | |||||
auto &profiling_manager = ProfilingManager::Instance(); | |||||
if (profiling_manager.ProfilingModelLoadOn()) { | |||||
Status p_ret = ReportProfilingData(!profiling_manager.IsAclApiMode()); | |||||
if (p_ret != SUCCESS) { | |||||
GELOGE(p_ret, "Report profiling data failed."); | |||||
return p_ret; | |||||
} | } | ||||
ProfilingManager::Instance().ReportProfilingData(GetTaskDescInfo(), compute_graph_desc_info); | |||||
GE_CHK_STATUS(SinkModelProfile(), "Sink model profile failed."); | |||||
} | } | ||||
Shrink(); | Shrink(); | ||||
@@ -707,6 +704,20 @@ Status DavinciModel::Init(void *dev_ptr, size_t mem_size, void *weight_ptr, size | |||||
return ret; | return ret; | ||||
} | } | ||||
Status DavinciModel::ReportProfilingData(bool check_device) { | |||||
std::vector<ComputeGraphDescInfo> compute_graph_desc_info; | |||||
Status ret = GetComputeGraphInfo(compute_graph_desc_info); | |||||
if (ret != SUCCESS) { | |||||
GELOGE(ret, "GetComputeGraphInfo failed."); | |||||
return ret; | |||||
} | |||||
ProfilingManager::Instance().ReportProfilingData(model_id_, GetTaskDescInfo(), compute_graph_desc_info, check_device); | |||||
GE_CHK_STATUS(SinkModelProfile(), "Sink model profiler failed."); | |||||
op_list_.clear(); | |||||
return SUCCESS; | |||||
} | |||||
/// | /// | ||||
/// @ingroup ge | /// @ingroup ge | ||||
/// @brief Travel all nodes and determine if destruction is required. | /// @brief Travel all nodes and determine if destruction is required. | ||||
@@ -2900,34 +2911,25 @@ Status DavinciModel::DistributeTask() { | |||||
SaveDumpTask(task->GetTaskID(), task->GetStreamId(), op, task->GetDumpArgs()); | SaveDumpTask(task->GetTaskID(), task->GetStreamId(), op, task->GetDumpArgs()); | ||||
} | } | ||||
} | } | ||||
// get op_name by task_index | |||||
if (task->GetCtx() != nullptr) { | |||||
auto iter = op_name_map_.find(task_index); | |||||
if (iter == op_name_map_.end()) { | |||||
continue; | |||||
} | |||||
// else task index is found in op_name_map_ | |||||
TaskDescInfo task_desc_info; | |||||
string op_name = op_name_map_[task_index]; | |||||
if (!om_name_.empty()) { | |||||
task_desc_info.model_name = om_name_; | |||||
} else { | |||||
task_desc_info.model_name = name_; | |||||
} | |||||
task_desc_info.op_name = op_name; | |||||
task_desc_info.block_dim = model_task_def->task(task_index).kernel().block_dim(); | |||||
task_desc_info.task_id = task->GetTaskID(); | |||||
task_desc_info.stream_id = task->GetStreamId(); | |||||
task_desc_info_.emplace_back(task_desc_info); | |||||
if (flag) { | |||||
if (task->GetSktTaskID() != 0xFFFFFFFF) { | |||||
TaskDescInfo task_desc_info; | |||||
string op_name = "super_kernel_" + to_string(task_index); | |||||
task_desc_info.op_name = op_name; | |||||
task_desc_info.task_id = task->GetSktTaskID(); | |||||
task_desc_info_.emplace_back(task_desc_info); | |||||
} | |||||
// Load task info for profiling | |||||
TaskDescInfo task_desc_info; | |||||
if (!om_name_.empty()) { | |||||
task_desc_info.model_name = om_name_; | |||||
} else { | |||||
task_desc_info.model_name = name_; | |||||
} | |||||
task_desc_info.op_name = op->GetName(); | |||||
task_desc_info.block_dim = model_task_def->task(task_index).kernel().block_dim(); | |||||
task_desc_info.task_id = task->GetTaskID(); | |||||
task_desc_info.stream_id = task->GetStreamId(); | |||||
task_desc_info_.emplace_back(task_desc_info); | |||||
if (flag) { | |||||
if (task->GetSktTaskID() != 0xFFFFFFFF) { | |||||
TaskDescInfo task_desc_info; | |||||
string op_name = "super_kernel_" + to_string(task_index); | |||||
task_desc_info.op_name = op_name; | |||||
task_desc_info.task_id = task->GetSktTaskID(); | |||||
task_desc_info_.emplace_back(task_desc_info); | |||||
} | } | ||||
} | } | ||||
} | } | ||||
@@ -3817,50 +3819,31 @@ void DavinciModel::SaveHcclFollowStream(int64_t main_stream_id, rtStream_t strea | |||||
main_follow_stream_mapping_[main_stream_id].emplace_back(stream); | main_follow_stream_mapping_[main_stream_id].emplace_back(stream); | ||||
} | } | ||||
Status DavinciModel::GetComputeGraphInfo(const ComputeGraphPtr &graph, vector<ComputeGraphDescInfo> &graph_desc_info) { | |||||
Status DavinciModel::GetComputeGraphInfo(vector<ComputeGraphDescInfo> &graph_desc_info) { | |||||
GELOGI("GetComputeGraphInfo start."); | GELOGI("GetComputeGraphInfo start."); | ||||
for (auto &node : graph->GetAllNodes()) { | |||||
auto &all_op_desc = data_dumper_.GetAllOpDescInfo(); | |||||
for (auto &op_desc : all_op_desc) { | |||||
ComputeGraphDescInfo compute_graph_info; | ComputeGraphDescInfo compute_graph_info; | ||||
auto op_desc = node->GetOpDesc(); | |||||
if (op_desc == nullptr) { | |||||
GELOGE(PARAM_INVALID, "op_desc is nullptr."); | |||||
return PARAM_INVALID; | |||||
if (!om_name_.empty()) { | |||||
compute_graph_info.model_name = om_name_; | |||||
} else { | |||||
compute_graph_info.model_name = name_; | |||||
} | } | ||||
compute_graph_info.op_name = op_desc.op_name; | |||||
compute_graph_info.op_type = op_desc.op_type; | |||||
compute_graph_info.input_format = op_desc.input_format; | |||||
compute_graph_info.input_shape = op_desc.input_shape; | |||||
compute_graph_info.input_data_type = op_desc.input_data_type; | |||||
compute_graph_info.output_format = op_desc.output_format; | |||||
compute_graph_info.output_shape = op_desc.output_shape; | |||||
compute_graph_info.output_data_type = op_desc.output_data_type; | |||||
auto op_mode = static_cast<uint32_t>(domi::ImplyType::INVALID); | |||||
if (AttrUtils::GetInt(op_desc, ATTR_NAME_IMPLY_TYPE, op_mode) && | |||||
op_mode == static_cast<uint32_t>(domi::ImplyType::TVM)) { | |||||
if (!om_name_.empty()) { | |||||
compute_graph_info.model_name = om_name_; | |||||
} else { | |||||
compute_graph_info.model_name = name_; | |||||
} | |||||
compute_graph_info.op_name = op_desc->GetName(); | |||||
compute_graph_info.op_type = op_desc->GetType(); | |||||
for (size_t i = 0; i < op_desc->GetAllInputsSize(); ++i) { | |||||
GeTensorDescPtr input_desc = op_desc->MutableInputDesc(i); | |||||
if (input_desc == nullptr) { | |||||
continue; | |||||
} | |||||
compute_graph_info.input_format.emplace_back(input_desc->GetFormat()); | |||||
compute_graph_info.input_shape.emplace_back(input_desc->GetShape().GetDims()); | |||||
compute_graph_info.input_data_type.emplace_back(input_desc->GetDataType()); | |||||
} | |||||
for (size_t j = 0; j < op_desc->GetOutputsSize(); ++j) { | |||||
GeTensorDesc output_desc = op_desc->GetOutputDesc(j); | |||||
compute_graph_info.output_format.emplace_back(output_desc.GetFormat()); | |||||
compute_graph_info.output_shape.emplace_back(output_desc.GetShape().GetDims()); | |||||
compute_graph_info.output_data_type.emplace_back(output_desc.GetDataType()); | |||||
} | |||||
graph_desc_info.emplace_back(compute_graph_info); | |||||
} | |||||
graph_desc_info.emplace_back(compute_graph_info); | |||||
} | } | ||||
GELOGI("GetComputeGraphInfo end."); | GELOGI("GetComputeGraphInfo end."); | ||||
return SUCCESS; | return SUCCESS; | ||||
} | } | ||||
void DavinciModel::SetTotalFixedAddrsSize(string tensor_name, int64_t fix_addr_size) { | void DavinciModel::SetTotalFixedAddrsSize(string tensor_name, int64_t fix_addr_size) { | ||||
if (tensor_name_to_fixed_addr_size_.find(tensor_name) == tensor_name_to_fixed_addr_size_.end()) { | if (tensor_name_to_fixed_addr_size_.find(tensor_name) == tensor_name_to_fixed_addr_size_.end()) { | ||||
tensor_name_to_fixed_addr_size_[tensor_name] = total_fixed_addr_size_; | tensor_name_to_fixed_addr_size_[tensor_name] = total_fixed_addr_size_; | ||||
@@ -439,6 +439,8 @@ class DavinciModel { | |||||
Status SinkTimeProfile(const InputData ¤t_data); | Status SinkTimeProfile(const InputData ¤t_data); | ||||
Status ReportProfilingData(bool check_device = true); | |||||
void SaveDumpOpInfo(const RuntimeParam &model_param, const OpDescPtr &op, uint32_t task_id, uint32_t stream_id) { | void SaveDumpOpInfo(const RuntimeParam &model_param, const OpDescPtr &op, uint32_t task_id, uint32_t stream_id) { | ||||
data_dumper_.SaveDumpOpInfo(model_param, op, task_id, stream_id); | data_dumper_.SaveDumpOpInfo(model_param, op, task_id, stream_id); | ||||
} | } | ||||
@@ -830,7 +832,7 @@ class DavinciModel { | |||||
Status TransAllVarData(ComputeGraphPtr &graph, uint32_t graph_id); | Status TransAllVarData(ComputeGraphPtr &graph, uint32_t graph_id); | ||||
// get desc info of graph for profiling | // get desc info of graph for profiling | ||||
Status GetComputeGraphInfo(const ComputeGraphPtr &graph, vector<ComputeGraphDescInfo> &graph_desc_info); | |||||
Status GetComputeGraphInfo(vector<ComputeGraphDescInfo> &graph_desc_info); | |||||
void SetDataDumperArgs(const ComputeGraphPtr &compute_graph); | void SetDataDumperArgs(const ComputeGraphPtr &compute_graph); | ||||
@@ -949,7 +951,6 @@ class DavinciModel { | |||||
std::map<std::string, uint32_t> used_tbe_handle_map_; | std::map<std::string, uint32_t> used_tbe_handle_map_; | ||||
// for profiling task and graph info | // for profiling task and graph info | ||||
std::map<uint32_t, std::string> op_name_map_; | |||||
std::vector<TaskDescInfo> task_desc_info_; | std::vector<TaskDescInfo> task_desc_info_; | ||||
int64_t maxDumpOpNum_; | int64_t maxDumpOpNum_; | ||||
@@ -43,6 +43,8 @@ const std::string kCmdTypeProfInit = "prof_init"; | |||||
const std::string kCmdTypeProfFinalize = "prof_finalize"; | const std::string kCmdTypeProfFinalize = "prof_finalize"; | ||||
const std::string kCmdTypeProfStart = "prof_start"; | const std::string kCmdTypeProfStart = "prof_start"; | ||||
const std::string kCmdTypeProfStop = "prof_stop"; | const std::string kCmdTypeProfStop = "prof_stop"; | ||||
const std::string kCmdTypeProfModelSubscribe = "prof_model_subscribe"; | |||||
const std::string kCmdTypeProfModelUnsubscribe = "prof_model_cancel_subscribe"; | |||||
const char *const kBatchLoadBuf = "batchLoadsoFrombuf"; | const char *const kBatchLoadBuf = "batchLoadsoFrombuf"; | ||||
const char *const kDeleteCustOp = "deleteCustOp"; | const char *const kDeleteCustOp = "deleteCustOp"; | ||||
struct CustAicpuSoBuf { | struct CustAicpuSoBuf { | ||||
@@ -334,11 +336,9 @@ Status ModelManager::LoadModelOnline(uint32_t &model_id, const shared_ptr<ge::Ge | |||||
GELOGI("Parse model %u success.", model_id); | GELOGI("Parse model %u success.", model_id); | ||||
if (ProfilingManager::Instance().ProfilingModelLoadOn()) { | |||||
davinci_model->SetProfileTime(MODEL_LOAD_START, (timespec.tv_sec * 1000 * 1000 * 1000 + | |||||
timespec.tv_nsec)); // 1000 ^ 3 converts second to nanosecond | |||||
davinci_model->SetProfileTime(MODEL_LOAD_END); | |||||
} | |||||
davinci_model->SetProfileTime(MODEL_LOAD_START, (timespec.tv_sec * 1000 * 1000 * 1000 + | |||||
timespec.tv_nsec)); // 1000 ^ 3 converts second to nanosecond | |||||
davinci_model->SetProfileTime(MODEL_LOAD_END); | |||||
} while (0); | } while (0); | ||||
GE_CHK_RT(rtDeviceReset(static_cast<int32_t>(GetContext().DeviceId()))); | GE_CHK_RT(rtDeviceReset(static_cast<int32_t>(GetContext().DeviceId()))); | ||||
@@ -565,7 +565,9 @@ Status ModelManager::HandleCommand(const Command &command) { | |||||
{kCmdTypeProfile, HandleProfileCommand}, {kCmdTypeDump, HandleDumpCommand}, | {kCmdTypeProfile, HandleProfileCommand}, {kCmdTypeDump, HandleDumpCommand}, | ||||
{kCmdTypeProfiling, HandleAclProfilingCommand}, {kCmdTypeProfInit, HandleProfInitCommand}, | {kCmdTypeProfiling, HandleAclProfilingCommand}, {kCmdTypeProfInit, HandleProfInitCommand}, | ||||
{kCmdTypeProfFinalize, HandleProfFinalizeCommand}, {kCmdTypeProfStart, HandleProfStartCommand}, | {kCmdTypeProfFinalize, HandleProfFinalizeCommand}, {kCmdTypeProfStart, HandleProfStartCommand}, | ||||
{kCmdTypeProfStop, HandleProfStopCommand}}; | |||||
{kCmdTypeProfStop, HandleProfStopCommand}, | |||||
{kCmdTypeProfModelSubscribe, HandleProfModelSubscribeCommand}, | |||||
{kCmdTypeProfModelUnsubscribe, HandleProfModelUnsubscribeCommand}}; | |||||
auto iter = cmds.find(command.cmd_type); | auto iter = cmds.find(command.cmd_type); | ||||
if (iter == cmds.end()) { | if (iter == cmds.end()) { | ||||
@@ -591,6 +593,77 @@ Status ModelManager::HandleAclProfilingCommand(const Command &command) { | |||||
return SUCCESS; | return SUCCESS; | ||||
} | } | ||||
Status ModelManager::GetModelByCmd(const Command &command, | |||||
std::shared_ptr<DavinciModel> &davinci_model) { | |||||
if (command.cmd_params.size() < kCmdParSize) { | |||||
GELOGE(PARAM_INVALID, "When the cmd_type is '%s', the size of cmd_params must larger than 2.", | |||||
command.cmd_type.c_str()); | |||||
return PARAM_INVALID; | |||||
} | |||||
std::string map_key = command.cmd_params[0]; | |||||
std::string value = command.cmd_params[1]; | |||||
if (map_key == PROFILE_MODEL_ID) { | |||||
int32_t model_id = 0; | |||||
try { | |||||
model_id = std::stoi(value); | |||||
} catch (std::invalid_argument &) { | |||||
GELOGE(PARAM_INVALID, "Model id: %s is invalid.", value.c_str()); | |||||
return PARAM_INVALID; | |||||
} catch (std::out_of_range &) { | |||||
GELOGE(PARAM_INVALID, "Model id: %s is out of range.", value.c_str()); | |||||
return PARAM_INVALID; | |||||
} catch (...) { | |||||
GELOGE(FAILED, "Model id: %s cannot change to int.", value.c_str()); | |||||
return FAILED; | |||||
} | |||||
auto model_manager = ModelManager::GetInstance(); | |||||
GE_CHECK_NOTNULL(model_manager); | |||||
davinci_model = model_manager->GetModel(static_cast<uint32_t>(model_id)); | |||||
if (davinci_model == nullptr) { | |||||
GELOGE(FAILED, "Model id: %d is invaild or model is not loaded.", model_id); | |||||
return FAILED; | |||||
} | |||||
} else { | |||||
GELOGE(FAILED, "The model_id parameter is not found in the command."); | |||||
return FAILED; | |||||
} | |||||
return SUCCESS; | |||||
} | |||||
Status ModelManager::HandleProfModelSubscribeCommand(const Command &command) { | |||||
std::shared_ptr<DavinciModel> davinci_model = nullptr; | |||||
Status ret = GetModelByCmd(command, davinci_model); | |||||
if (ret != SUCCESS) { | |||||
return ret; | |||||
} | |||||
if (ProfilingManager::Instance().ProfModelSubscribe(command.module_index, | |||||
static_cast<void *>(davinci_model.get())) != SUCCESS) { | |||||
GELOGE(FAILED, "Handle prof model subscribe failed."); | |||||
return FAILED; | |||||
} | |||||
return SUCCESS; | |||||
} | |||||
Status ModelManager::HandleProfModelUnsubscribeCommand(const Command &command) { | |||||
std::shared_ptr<DavinciModel> davinci_model = nullptr; | |||||
Status ret = GetModelByCmd(command, davinci_model); | |||||
if (ret != SUCCESS) { | |||||
return ret; | |||||
} | |||||
if (ProfilingManager::Instance().ProfModelUnsubscribe(static_cast<void *>(davinci_model.get())) != SUCCESS) { | |||||
GELOGE(FAILED, "Handle prof model unsubscribe failed."); | |||||
return FAILED; | |||||
} | |||||
return SUCCESS; | |||||
} | |||||
Status ModelManager::HandleProfInitCommand(const Command &command) { | Status ModelManager::HandleProfInitCommand(const Command &command) { | ||||
uint64_t module_index = command.module_index; | uint64_t module_index = command.module_index; | ||||
if (ProfilingManager::Instance().ProfInit(module_index) != SUCCESS) { | if (ProfilingManager::Instance().ProfInit(module_index) != SUCCESS) { | ||||
@@ -973,11 +1046,9 @@ Status ModelManager::LoadModelOffline(uint32_t &model_id, const ModelData &model | |||||
GELOGI("Parse model %u success.", model_id); | GELOGI("Parse model %u success.", model_id); | ||||
if (ProfilingManager::Instance().ProfilingModelLoadOn()) { | |||||
davinci_model->SetProfileTime(MODEL_LOAD_START, (timespec.tv_sec * 1000 * 1000 * 1000 + | |||||
timespec.tv_nsec)); // 1000 ^ 3 converts second to nanosecond | |||||
davinci_model->SetProfileTime(MODEL_LOAD_END); | |||||
} | |||||
davinci_model->SetProfileTime(MODEL_LOAD_START, (timespec.tv_sec * 1000 * 1000 * 1000 + | |||||
timespec.tv_nsec)); // 1000 ^ 3 converts second to nanosecond | |||||
davinci_model->SetProfileTime(MODEL_LOAD_END); | |||||
GE_IF_BOOL_EXEC(ret == SUCCESS, device_count++); | GE_IF_BOOL_EXEC(ret == SUCCESS, device_count++); | ||||
return SUCCESS; | return SUCCESS; | ||||
@@ -158,10 +158,15 @@ class FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY ModelManager { | |||||
static ge::Status HandleAclProfilingCommand(const Command &command); | static ge::Status HandleAclProfilingCommand(const Command &command); | ||||
static ge::Status HandleProfileCommand(const Command &command); | static ge::Status HandleProfileCommand(const Command &command); | ||||
static ge::Status HandleDumpCommand(const Command &command); | static ge::Status HandleDumpCommand(const Command &command); | ||||
static ge::Status HandleProfModelSubscribeCommand(const Command &command); | |||||
static ge::Status HandleProfModelUnsubscribeCommand(const Command &command); | |||||
static ge::Status HandleProfInitCommand(const Command &command); | static ge::Status HandleProfInitCommand(const Command &command); | ||||
static ge::Status HandleProfFinalizeCommand(const Command &command); | static ge::Status HandleProfFinalizeCommand(const Command &command); | ||||
static ge::Status HandleProfStartCommand(const Command &command); | static ge::Status HandleProfStartCommand(const Command &command); | ||||
static ge::Status HandleProfStopCommand(const Command &command); | static ge::Status HandleProfStopCommand(const Command &command); | ||||
static ge::Status GetModelByCmd(const Command &command, | |||||
std::shared_ptr<DavinciModel> &davinci_model); | |||||
/// | /// | ||||
/// @ingroup domi_ome | /// @ingroup domi_ome | ||||
/// @brief get model memory usage | /// @brief get model memory usage | ||||
@@ -45,7 +45,7 @@ Status ZeroCopyTask::SetTaskArgsOffset(uintptr_t addr, size_t offset) { | |||||
if (it == task_addr_offset_.end()) { | if (it == task_addr_offset_.end()) { | ||||
task_addr_offset_[addr] = {offset}; | task_addr_offset_[addr] = {offset}; | ||||
} else { | } else { | ||||
it->second.push_back(offset); | |||||
it->second.insert(offset); | |||||
} | } | ||||
GELOGI("[ZCPY] %s set task, virtual_addr: 0x%lx, args_addr: %p, size: %zu, offset: %zu", name_.c_str(), addr, | GELOGI("[ZCPY] %s set task, virtual_addr: 0x%lx, args_addr: %p, size: %zu, offset: %zu", name_.c_str(), addr, | ||||
@@ -103,7 +103,7 @@ class ZeroCopyTask { | |||||
bool is_updated_; | bool is_updated_; | ||||
string batch_label_; | string batch_label_; | ||||
// <address from Op, {offset in args}> | // <address from Op, {offset in args}> | ||||
map<uintptr_t, vector<size_t>> task_addr_offset_; | |||||
map<uintptr_t, set<size_t>> task_addr_offset_; | |||||
}; | }; | ||||
} // namespace ge | } // namespace ge | ||||
#endif // GE_GRAPH_LOAD_NEW_MODEL_MANAGER_ZERO_COPY_TASK_H_ | #endif // GE_GRAPH_LOAD_NEW_MODEL_MANAGER_ZERO_COPY_TASK_H_ |
@@ -133,6 +133,22 @@ bool IsTailingOptimization() { | |||||
GELOGW("OPTION_EXEC_ENABLE_TAILING_OPTIMIZATION not set, use BFSTopologicalSorting by default."); | GELOGW("OPTION_EXEC_ENABLE_TAILING_OPTIMIZATION not set, use BFSTopologicalSorting by default."); | ||||
return false; | return false; | ||||
} | } | ||||
ge::Status CheckFpCeilingMode() { | |||||
static const std::unordered_set<std::string> kValidFpCeilingMode = {"0", "1", "2"}; | |||||
string mode; | |||||
auto ret = ge::GetContext().GetOption("ge.fpCeilingMode", mode); | |||||
if (ret == ge::GRAPH_SUCCESS) { | |||||
if (kValidFpCeilingMode.count(mode) == 0) { | |||||
GELOGE(ge::GE_GRAPH_OPTIONS_INVALID, "The fp_ceiling_mode %s is invalid, options are 0, 1, and 2.", mode.c_str()); | |||||
return ge::GE_GRAPH_OPTIONS_INVALID; | |||||
} | |||||
GELOGI("The parameter fp_ceiling_mode is set to %s.", mode.c_str()); | |||||
return ge::SUCCESS; | |||||
} | |||||
GELOGW("The parameter fp_ceiling_mode is not set."); | |||||
return ge::SUCCESS; | |||||
} | |||||
} // namespace | } // namespace | ||||
namespace ge { | namespace ge { | ||||
@@ -168,6 +184,12 @@ Status GraphManager::Initialize(const std::map<string, string> &options) { | |||||
return ret; | return ret; | ||||
} | } | ||||
ret = CheckFpCeilingMode(); | |||||
if (ret != SUCCESS) { | |||||
GELOGE(ret, "[Initialize] Check fp-ceiling-mode options failed."); | |||||
return ret; | |||||
} | |||||
ret = graph_context_->Initialize(options); | ret = graph_context_->Initialize(options); | ||||
if (ret != SUCCESS) { | if (ret != SUCCESS) { | ||||
GELOGE(ret, "[Initialize] GraphContext initialize failed."); | GELOGE(ret, "[Initialize] GraphContext initialize failed."); | ||||
@@ -25,6 +25,10 @@ | |||||
namespace ge { | namespace ge { | ||||
Status MemcpyAddrAsyncPass::Run(ComputeGraphPtr graph) { | Status MemcpyAddrAsyncPass::Run(ComputeGraphPtr graph) { | ||||
GE_CHECK_NOTNULL(graph); | GE_CHECK_NOTNULL(graph); | ||||
if (graph->GetGraphUnknownFlag()) { | |||||
GELOGD("Graph[%s] is unknown graph, skip.", graph->GetName().c_str()); | |||||
return SUCCESS; | |||||
} | |||||
int64_t value = 0; | int64_t value = 0; | ||||
rtError_t rt_ret = rtGetRtCapability(FEATURE_TYPE_MEMCPY, MEMCPY_INFO_SUPPORT_ZEROCOPY, &value); | rtError_t rt_ret = rtGetRtCapability(FEATURE_TYPE_MEMCPY, MEMCPY_INFO_SUPPORT_ZEROCOPY, &value); | ||||
@@ -201,9 +205,10 @@ NodePtr MemcpyAddrAsyncPass::CreateMemcpyAddrAsyncNode(const ComputeGraphPtr &gr | |||||
const OutDataAnchorPtr &out_data_anchor, | const OutDataAnchorPtr &out_data_anchor, | ||||
const NodePtr &out_of_user_data) { | const NodePtr &out_of_user_data) { | ||||
GELOGD("Start CreateMemcpyAddrAsyncNode."); | GELOGD("Start CreateMemcpyAddrAsyncNode."); | ||||
static uint32_t new_node_index = 0; | |||||
OpDescPtr pre_op_desc = out_data_anchor->GetOwnerNode()->GetOpDesc(); | OpDescPtr pre_op_desc = out_data_anchor->GetOwnerNode()->GetOpDesc(); | ||||
GE_CHK_BOOL_EXEC(pre_op_desc != nullptr, return nullptr, "Op_desc of pre node is invalid."); | GE_CHK_BOOL_EXEC(pre_op_desc != nullptr, return nullptr, "Op_desc of pre node is invalid."); | ||||
std::string node_name = pre_op_desc->GetName() + "_" + MEMCPYADDRASYNC; | |||||
std::string node_name = pre_op_desc->GetName() + "_" + MEMCPYADDRASYNC + "_" + std::to_string(new_node_index++); | |||||
OpDescPtr op_desc = MakeShared<OpDesc>(node_name, MEMCPYADDRASYNC); | OpDescPtr op_desc = MakeShared<OpDesc>(node_name, MEMCPYADDRASYNC); | ||||
GE_CHECK_NOTNULL_EXEC(op_desc, return nullptr); | GE_CHECK_NOTNULL_EXEC(op_desc, return nullptr); | ||||
@@ -103,6 +103,12 @@ Status NetOutputPass::GetOutputNode(const ge::ComputeGraphPtr &graph, std::vecto | |||||
GELOGI("user set out node [%s] is found in user def targets, out node is prio!", ele.first->GetName().c_str()); | GELOGI("user set out node [%s] is found in user def targets, out node is prio!", ele.first->GetName().c_str()); | ||||
targets_.erase(iter); | targets_.erase(iter); | ||||
} | } | ||||
auto op_desc = ele.first->GetOpDesc(); | |||||
GE_CHECK_NOTNULL(op_desc); | |||||
if (op_desc->HasAttr(ATTR_ATC_USER_DEFINE_OUTPUT_NODES)) { | |||||
is_user_define_ouput_nodes = true; | |||||
} | |||||
output_nodes_info.push_back({ele.first, ele.second, -1}); | output_nodes_info.push_back({ele.first, ele.second, -1}); | ||||
} | } | ||||
GELOGI("Output node set by user or leaf node, size:%zu.", output_nodes_info.size()); | GELOGI("Output node set by user or leaf node, size:%zu.", output_nodes_info.size()); | ||||
@@ -414,7 +420,7 @@ Status NetOutputPass::ProcessWithNetoutput(const ge::ComputeGraphPtr &graph, con | |||||
Status NetOutputPass::AddCtrlEdgesBetweenLeafAndNetOutput(const ge::ComputeGraphPtr &graph, | Status NetOutputPass::AddCtrlEdgesBetweenLeafAndNetOutput(const ge::ComputeGraphPtr &graph, | ||||
const ge::NodePtr &net_out_node) { | const ge::NodePtr &net_out_node) { | ||||
GE_CHECK_NOTNULL(net_out_node); | GE_CHECK_NOTNULL(net_out_node); | ||||
if (!GetLocalOmgContext().user_out_nodes.empty()) { | |||||
if (!GetLocalOmgContext().user_out_nodes.empty() || is_user_define_ouput_nodes) { | |||||
GELOGI("No need to add ctrl edge to netoutput because user out nodes have been set."); | GELOGI("No need to add ctrl edge to netoutput because user out nodes have been set."); | ||||
return SUCCESS; | return SUCCESS; | ||||
} | } | ||||
@@ -220,6 +220,7 @@ class NetOutputPass : public GraphPass { | |||||
bool is_include_special_node_ = false; | bool is_include_special_node_ = false; | ||||
std::set<NodePtr> targets_; | std::set<NodePtr> targets_; | ||||
friend class ReUpdateNetOutputPass; | friend class ReUpdateNetOutputPass; | ||||
bool is_user_define_ouput_nodes = false; | |||||
}; | }; | ||||
} // namespace ge | } // namespace ge | ||||
#endif // GE_GRAPH_PASSES_NET_OUTPUT_PASS_H_ | #endif // GE_GRAPH_PASSES_NET_OUTPUT_PASS_H_ |
@@ -117,7 +117,6 @@ | |||||
#include "graph/passes/variable_op_pass.h" | #include "graph/passes/variable_op_pass.h" | ||||
#include "graph/passes/variable_prepare_op_pass.h" | #include "graph/passes/variable_prepare_op_pass.h" | ||||
#include "graph/passes/variable_ref_delete_op_pass.h" | #include "graph/passes/variable_ref_delete_op_pass.h" | ||||
#include "graph/passes/mark_agnostic_pass.h" | |||||
namespace ge { | namespace ge { | ||||
@@ -219,6 +218,9 @@ NodePtr CreateTransNode(const std::string &name, const std::string &node_type, c | |||||
auto index = TransOpUtil::GetTransOpDataIndex(node_type); | auto index = TransOpUtil::GetTransOpDataIndex(node_type); | ||||
if (index < 0) { | if (index < 0) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage( | |||||
"E19025", {"situation", "reason"}, | |||||
{"The trans node type[" + node_type + "]", "it must be " + TransOpUtil::TransopMapToString()}); | |||||
GELOGE(INTERNAL_ERROR, "The trans node type %s does not exists", node_type.c_str()); | GELOGE(INTERNAL_ERROR, "The trans node type %s does not exists", node_type.c_str()); | ||||
return nullptr; | return nullptr; | ||||
} | } | ||||
@@ -387,6 +389,8 @@ Status RecoverTransRoadForVar(const NodePtr &var, const VarTransRoad &road) { | |||||
auto trans_name = var->GetName() + "_trans_" + std::to_string(index++); | auto trans_name = var->GetName() + "_trans_" + std::to_string(index++); | ||||
auto ret = RecoverOneTransNodeForVar(trans_name, *iter, last_node, last_node); | auto ret = RecoverOneTransNodeForVar(trans_name, *iter, last_node, last_node); | ||||
if (ret != SUCCESS) { | if (ret != SUCCESS) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage( | |||||
"E15001", {"variable", "index", "type"}, {var->GetName(), std::to_string(index), iter->node_type}); | |||||
GELOGE(INTERNAL_ERROR, "Failed to recover trans node for variable %s, index %d, type %s", var->GetName().c_str(), | GELOGE(INTERNAL_ERROR, "Failed to recover trans node for variable %s, index %d, type %s", var->GetName().c_str(), | ||||
index, iter->node_type.c_str()); | index, iter->node_type.c_str()); | ||||
return INTERNAL_ERROR; | return INTERNAL_ERROR; | ||||
@@ -419,6 +423,8 @@ Status RecoverTransRoadForVarRef(const std::set<NodePtr> &nodes, const VarTransR | |||||
auto trans_name = var->GetName() + "_trans_" + std::to_string(index++); | auto trans_name = var->GetName() + "_trans_" + std::to_string(index++); | ||||
auto ret = RecoverOneTransNodeForVarRef(trans_name, *iter, last_node, last_node); | auto ret = RecoverOneTransNodeForVarRef(trans_name, *iter, last_node, last_node); | ||||
if (ret != SUCCESS) { | if (ret != SUCCESS) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage( | |||||
"E15001", {"variable", "index", "type"}, {var->GetName(), std::to_string(index), iter->node_type}); | |||||
GELOGE(INTERNAL_ERROR, "Failed to recover trans node for variable %s, index %d, type %s", | GELOGE(INTERNAL_ERROR, "Failed to recover trans node for variable %s, index %d, type %s", | ||||
var->GetName().c_str(), index, iter->node_type.c_str()); | var->GetName().c_str(), index, iter->node_type.c_str()); | ||||
return INTERNAL_ERROR; | return INTERNAL_ERROR; | ||||
@@ -571,6 +577,8 @@ Status CheckIfDynamicBatchScene(NodePtr &data_node, bool &is_dynamic_batch, Node | |||||
std::string related_node_name; | std::string related_node_name; | ||||
if (AttrUtils::GetStr(data_node->GetOpDesc(), kMbatchSwitchnName, related_node_name)) { | if (AttrUtils::GetStr(data_node->GetOpDesc(), kMbatchSwitchnName, related_node_name)) { | ||||
if (related_node_name.empty()) { | if (related_node_name.empty()) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage( | |||||
"E15002", {"opname", "value", "reason"}, {data_node->GetName(), "flag", "but the value is empty"}); | |||||
GELOGE(INTERNAL_ERROR, "The data node %s has switchn node flag, but the value is empty", | GELOGE(INTERNAL_ERROR, "The data node %s has switchn node flag, but the value is empty", | ||||
data_node->GetName().c_str()); | data_node->GetName().c_str()); | ||||
return INTERNAL_ERROR; | return INTERNAL_ERROR; | ||||
@@ -582,6 +590,9 @@ Status CheckIfDynamicBatchScene(NodePtr &data_node, bool &is_dynamic_batch, Node | |||||
} | } | ||||
} | } | ||||
if (switchn_node == nullptr) { | if (switchn_node == nullptr) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage( | |||||
"E15002", {"opname", "value", "reason"}, | |||||
{data_node->GetName(), related_node_name, "but can not find it on the graph"}); | |||||
GELOGE(INTERNAL_ERROR, "The data node %s has switchn node %s, but can not find it on the graph", | GELOGE(INTERNAL_ERROR, "The data node %s has switchn node %s, but can not find it on the graph", | ||||
data_node->GetName().c_str(), related_node_name.c_str()); | data_node->GetName().c_str(), related_node_name.c_str()); | ||||
return INTERNAL_ERROR; | return INTERNAL_ERROR; | ||||
@@ -682,6 +693,10 @@ Status ProcessInputNC1HWC0DynShape(NodePtr &node_ptr, bool &is_dynamic_batch, No | |||||
ge::GeShape old_shape = input->GetShape(); | ge::GeShape old_shape = input->GetShape(); | ||||
bool support = ((old_format == FORMAT_NC1HWC0) || (old_format == FORMAT_NCHW) || (old_format == FORMAT_NHWC)); | bool support = ((old_format == FORMAT_NC1HWC0) || (old_format == FORMAT_NCHW) || (old_format == FORMAT_NHWC)); | ||||
if (!support) { | if (!support) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage( | |||||
"E19014", {"opname", "value", "reason"}, | |||||
{op_desc->GetName(), "format[" + TypeUtils::FormatToSerialString(old_format) + "]", | |||||
"only support FORMAT_NC1HWC0,FORMAT_NCHW,FORMAT_NHWC"}); | |||||
GELOGE(INTERNAL_ERROR, "The format [%s] is unsupported", TypeUtils::FormatToSerialString(old_format).c_str()); | GELOGE(INTERNAL_ERROR, "The format [%s] is unsupported", TypeUtils::FormatToSerialString(old_format).c_str()); | ||||
return FAILED; | return FAILED; | ||||
} | } | ||||
@@ -762,6 +777,9 @@ Status GetStorageFormatAndShape(OpDescPtr &op_desc, const GeTensorDescPtr &tenso | |||||
op_desc->GetName().c_str(), TypeUtils::FormatToSerialString(storage_format).c_str(), | op_desc->GetName().c_str(), TypeUtils::FormatToSerialString(storage_format).c_str(), | ||||
formats::JoinToString(storage_shape).c_str()); | formats::JoinToString(storage_shape).c_str()); | ||||
} else { | } else { | ||||
ErrorManager::GetInstance().ATCReportErrMessage( | |||||
"15003", {"opname", "format"}, | |||||
{op_desc->GetName(), TypeUtils::FormatToSerialString(storage_format)}); | |||||
GELOGE(PARAM_INVALID, "Update node by storage format failed, storage_shape not set. " | GELOGE(PARAM_INVALID, "Update node by storage format failed, storage_shape not set. " | ||||
"node: [%s], storage_format [%s]", | "node: [%s], storage_format [%s]", | ||||
op_desc->GetName().c_str(), TypeUtils::FormatToSerialString(storage_format).c_str()); | op_desc->GetName().c_str(), TypeUtils::FormatToSerialString(storage_format).c_str()); | ||||
@@ -900,9 +918,14 @@ Status ProcessNetoutputNodeDynShape(NodePtr &node) { | |||||
// check if is_output_adjust_hw_layout is set | // check if is_output_adjust_hw_layout is set | ||||
if (NeedUpdateFormatByOutputTypeParm(op_desc, index)) { | if (NeedUpdateFormatByOutputTypeParm(op_desc, index)) { | ||||
if ((old_format != FORMAT_NCHW) && (old_format != FORMAT_NHWC) && (old_format != FORMAT_NC1HWC0)) { | if ((old_format != FORMAT_NCHW) && (old_format != FORMAT_NHWC) && (old_format != FORMAT_NC1HWC0)) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage( | |||||
"E19014", {"opname", "value", "reason"}, | |||||
{op_desc->GetName(), "format[" + TypeUtils::FormatToSerialString(old_format) + "]", | |||||
"only support FORMAT_NC1HWC0,FORMAT_NCHW,FORMAT_NHWC"}); | |||||
GELOGE(INTERNAL_ERROR, "Format is not one of NCHW, NHWC, NC1HWC0."); | GELOGE(INTERNAL_ERROR, "Format is not one of NCHW, NHWC, NC1HWC0."); | ||||
return FAILED; | return FAILED; | ||||
} | } | ||||
GeTensorDesc old_desc(old_shape, old_format, old_dtype); | GeTensorDesc old_desc(old_shape, old_format, old_dtype); | ||||
if (ProcessNetoutputNodeFp16Nc1hwc0DynShape(old_desc, net_output_input_desc, src_node) != SUCCESS) { | if (ProcessNetoutputNodeFp16Nc1hwc0DynShape(old_desc, net_output_input_desc, src_node) != SUCCESS) { | ||||
GELOGE(INTERNAL_ERROR, "Process netoutput fp16 nc1hwc0."); | GELOGE(INTERNAL_ERROR, "Process netoutput fp16 nc1hwc0."); | ||||
@@ -1035,6 +1058,9 @@ Status GraphPrepare::CheckRefInputNode(const NodePtr &node, const std::string &i | |||||
} | } | ||||
bool is_acceptable = (acceptable_types.find(input_type) != acceptable_types.end()); | bool is_acceptable = (acceptable_types.find(input_type) != acceptable_types.end()); | ||||
if (!is_acceptable) { | if (!is_acceptable) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage( | |||||
"E15005", {"opname", "optype", "opname1", "optype1"}, | |||||
{op_desc->GetName(), node->GetType(), input_op_desc->GetName(), input_op_desc->GetType()}); | |||||
GELOGE(PARAM_INVALID, "The ref input of ref node %s[%s] must be ref node or variable, but %s[%s]isn't.", | GELOGE(PARAM_INVALID, "The ref input of ref node %s[%s] must be ref node or variable, but %s[%s]isn't.", | ||||
node->GetName().c_str(), node->GetType().c_str(), input_op_desc->GetName().c_str(), | node->GetName().c_str(), node->GetType().c_str(), input_op_desc->GetName().c_str(), | ||||
input_op_desc->GetType().c_str()); | input_op_desc->GetType().c_str()); | ||||
@@ -1127,6 +1153,9 @@ Status GraphPrepare::UpdateInput(const std::vector<GeTensor> &user_input) { | |||||
} | } | ||||
if ((index < 0) || (static_cast<size_t>(index) >= user_input.size())) { | if ((index < 0) || (static_cast<size_t>(index) >= user_input.size())) { | ||||
std::string situation = "data op index[" + std::to_string(index) + "]"; | |||||
std::string reason = "it must less than user_input size[" + std::to_string(user_input.size()) + "]"; | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E19025", {"situation", "reason"}, {situation, reason}); | |||||
GELOGE(PARAM_INVALID, "user_input size = %zu, graph data op index = %ld.", user_input.size(), index); | GELOGE(PARAM_INVALID, "user_input size = %zu, graph data op index = %ld.", user_input.size(), index); | ||||
return FAILED; | return FAILED; | ||||
} | } | ||||
@@ -1139,6 +1168,9 @@ Status GraphPrepare::UpdateInput(const std::vector<GeTensor> &user_input) { | |||||
if (need_check_internal_format) { | if (need_check_internal_format) { | ||||
bool is_internal = TypeUtils::IsInternalFormat(format) || TypeUtils::IsInternalFormat(origin_format); | bool is_internal = TypeUtils::IsInternalFormat(format) || TypeUtils::IsInternalFormat(origin_format); | ||||
if (is_internal) { | if (is_internal) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage("E19025", {"situation", "reason"}, | |||||
{"Input format[" + TypeUtils::FormatToSerialString(format) + "] or origin_format[" + | |||||
TypeUtils::FormatToSerialString(origin_format) + "]", "it is not support"}); | |||||
GELOGE(PARAM_INVALID, "Input format %s or origin_format %s is not support.", | GELOGE(PARAM_INVALID, "Input format %s or origin_format %s is not support.", | ||||
TypeUtils::FormatToSerialString(format).c_str(), | TypeUtils::FormatToSerialString(format).c_str(), | ||||
TypeUtils::FormatToSerialString(origin_format).c_str()); | TypeUtils::FormatToSerialString(origin_format).c_str()); | ||||
@@ -1150,6 +1182,8 @@ Status GraphPrepare::UpdateInput(const std::vector<GeTensor> &user_input) { | |||||
uint32_t length = 1; | uint32_t length = 1; | ||||
bool type_ret = TypeUtils::GetDataTypeLength(data_type, length); | bool type_ret = TypeUtils::GetDataTypeLength(data_type, length); | ||||
if (!type_ret) { | if (!type_ret) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage("E19025", {"situation", "reason"}, | |||||
{"Input datatype[" + TypeUtils::DataTypeToSerialString(data_type) + "]", "it is not support"}); | |||||
GELOGE(PARAM_INVALID, "Input datatype %s is not support.", | GELOGE(PARAM_INVALID, "Input datatype %s is not support.", | ||||
TypeUtils::DataTypeToSerialString(data_type).c_str()); | TypeUtils::DataTypeToSerialString(data_type).c_str()); | ||||
return FAILED; | return FAILED; | ||||
@@ -1164,6 +1198,10 @@ Status GraphPrepare::UpdateInput(const std::vector<GeTensor> &user_input) { | |||||
return FAILED); | return FAILED); | ||||
bool size_check = (size != 0 && shape_size != size); | bool size_check = (size != 0 && shape_size != size); | ||||
if (size_check) { | if (size_check) { | ||||
std::string situation = "input data size[" + std::to_string(size) + | |||||
"] and shape_size[" + std::to_string(size) + "]"; | |||||
std::string reason = "because size != 0 and shape_size != size"; | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E19025", {"situation", "reason"}, {situation, reason}); | |||||
GELOGE(PARAM_INVALID, "input data size =%ld, shape_size =%ld.", size, shape_size); | GELOGE(PARAM_INVALID, "input data size =%ld, shape_size =%ld.", size, shape_size); | ||||
return FAILED; | return FAILED; | ||||
} | } | ||||
@@ -1503,6 +1541,8 @@ Status GraphPrepare::VerifyConstOp(const NodePtr &node) { | |||||
uint32_t length = 1; | uint32_t length = 1; | ||||
bool type_ret = TypeUtils::GetDataTypeLength(data_type, length); | bool type_ret = TypeUtils::GetDataTypeLength(data_type, length); | ||||
if (!type_ret) { | if (!type_ret) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage("E19025", {"situation", "reason"}, | |||||
{"Input datatype[" + TypeUtils::DataTypeToSerialString(data_type) + "]", "it is not support"}); | |||||
GELOGE(PARAM_INVALID, "Input datatype %s is not support.", TypeUtils::DataTypeToSerialString(data_type).c_str()); | GELOGE(PARAM_INVALID, "Input datatype %s is not support.", TypeUtils::DataTypeToSerialString(data_type).c_str()); | ||||
return FAILED; | return FAILED; | ||||
} | } | ||||
@@ -1512,14 +1552,20 @@ Status GraphPrepare::VerifyConstOp(const NodePtr &node) { | |||||
if (shape_size == 0) { | if (shape_size == 0) { | ||||
if (ge_tensor_desc.GetShape().GetDims().size() == 0) { | if (ge_tensor_desc.GetShape().GetDims().size() == 0) { | ||||
// shape = [], means it's a sclar tensor. | // shape = [], means it's a sclar tensor. | ||||
GE_CHK_BOOL_EXEC(data_size / length == 1, return PARAM_INVALID, "Const is invalid scalar tensor."); | |||||
GE_CHK_BOOL_EXEC(data_size / length == 1, | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {"Const is invalid scalar tensor."}); | |||||
return PARAM_INVALID, "Const is invalid scalar tensor."); | |||||
} else { | } else { | ||||
// shape = [x, y, 0,...], means it's a vector tensor that value is []. | // shape = [x, y, 0,...], means it's a vector tensor that value is []. | ||||
GE_CHK_BOOL_EXEC(data_size == 0, return PARAM_INVALID, "Const is invalid vector scalar."); | |||||
GE_CHK_BOOL_EXEC(data_size == 0, | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {"Const is invalid vector scalar."}); | |||||
return PARAM_INVALID, "Const is invalid vector scalar."); | |||||
} | } | ||||
} else { | } else { | ||||
GE_CHK_BOOL_EXEC(data_size == static_cast<size_t>(shape_size * length) && data_size != 0, return PARAM_INVALID, | |||||
"Const input data size is not equal with tensor desc shape"); | |||||
GE_CHK_BOOL_EXEC(data_size == static_cast<size_t>(shape_size * length) && data_size != 0, | |||||
ErrorManager::GetInstance().ATCReportErrMessage( | |||||
"E10043", {"reason"}, {"Const input data size is not equal with tensor desc shape"}); | |||||
return PARAM_INVALID, "Const input data size is not equal with tensor desc shape"); | |||||
} | } | ||||
return SUCCESS; | return SUCCESS; | ||||
} | } | ||||
@@ -1543,6 +1589,9 @@ Status GraphPrepare::CheckUserInput(const std::vector<GeTensor> &user_input) { | |||||
return GE_GRAPH_INIT_FAILED; | return GE_GRAPH_INIT_FAILED; | ||||
} | } | ||||
if ((index < 0) || (static_cast<size_t>(index) >= user_input.size())) { | if ((index < 0) || (static_cast<size_t>(index) >= user_input.size())) { | ||||
std::string situation = "data op index[" + std::to_string(index) + "]"; | |||||
std::string reason = "it must less than user_input size[" + std::to_string(user_input.size()) + "]"; | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E19025", {"situation", "reason"}, {situation, reason}); | |||||
GELOGE(GE_GRAPH_INIT_FAILED, "user_input size:%zu, data op index:%ld.", user_input.size(), index); | GELOGE(GE_GRAPH_INIT_FAILED, "user_input size:%zu, data op index:%ld.", user_input.size(), index); | ||||
return GE_GRAPH_INIT_FAILED; | return GE_GRAPH_INIT_FAILED; | ||||
} | } | ||||
@@ -1550,6 +1599,9 @@ Status GraphPrepare::CheckUserInput(const std::vector<GeTensor> &user_input) { | |||||
for (size_t i = 0; i < desc.GetShape().GetDimNum(); ++i) { | for (size_t i = 0; i < desc.GetShape().GetDimNum(); ++i) { | ||||
if (desc.GetShape().GetDim(i) < 0) { | if (desc.GetShape().GetDim(i) < 0) { | ||||
std::string situation = "data dim[" + std::to_string(i) + "][" + std::to_string(desc.GetShape().GetDim(i)) + "]" ; | |||||
std::string reason = "it need >= 0"; | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E19025", {"situation", "reason"}, {situation, reason}); | |||||
GELOGE(GE_GRAPH_INIT_FAILED, "data dim %zu is not supported, need >= 0, real:%ld.", i, | GELOGE(GE_GRAPH_INIT_FAILED, "data dim %zu is not supported, need >= 0, real:%ld.", i, | ||||
desc.GetShape().GetDim(i)); | desc.GetShape().GetDim(i)); | ||||
return GE_GRAPH_INIT_FAILED; | return GE_GRAPH_INIT_FAILED; | ||||
@@ -1627,7 +1679,6 @@ Status GraphPrepare::PrepareOptimize() { | |||||
try { | try { | ||||
(void)original_graph_passes.AddPass("PrepareOptimize::ShapeOperateOpRemovePass", new ShapeOperateOpRemovePass); | (void)original_graph_passes.AddPass("PrepareOptimize::ShapeOperateOpRemovePass", new ShapeOperateOpRemovePass); | ||||
(void)original_graph_passes.AddPass("PrepareOptimize::ReplaceTransShapePass", new ReplaceTransShapePass); | (void)original_graph_passes.AddPass("PrepareOptimize::ReplaceTransShapePass", new ReplaceTransShapePass); | ||||
(void)original_graph_passes.AddPass("PrepareOptimize::MarkAgnosticPass", new MarkAgnosticPass); | |||||
} catch (std::bad_alloc &e) { | } catch (std::bad_alloc &e) { | ||||
GELOGE(INTERNAL_ERROR, "Add pass failed, bad memory allocation occurs."); | GELOGE(INTERNAL_ERROR, "Add pass failed, bad memory allocation occurs."); | ||||
return INTERNAL_ERROR; | return INTERNAL_ERROR; | ||||
@@ -53,16 +53,6 @@ | |||||
} \ | } \ | ||||
} while (0) | } while (0) | ||||
#define AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(expr, _status, errormsg) \ | |||||
do { \ | |||||
bool b = (expr); \ | |||||
if (!b) { \ | |||||
GELOGE(_status, errormsg); \ | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {errormsg}); \ | |||||
return _status; \ | |||||
} \ | |||||
} while (0) | |||||
namespace { | namespace { | ||||
const int32_t DEFAULT_MATRIX_R0C0_YUV2RGB = 298; | const int32_t DEFAULT_MATRIX_R0C0_YUV2RGB = 298; | ||||
const int32_t DEFAULT_MATRIX_R0C1_YUV2RGB = 0; | const int32_t DEFAULT_MATRIX_R0C1_YUV2RGB = 0; | ||||
@@ -316,9 +306,8 @@ NodePtr AippOp::FindDataByIndex(const ComputeGraphPtr &graph, int rank) { | |||||
} | } | ||||
return node; | return node; | ||||
} | } | ||||
GELOGE(PARAM_INVALID, "Can not find the data node by index %d", rank); | |||||
string errormsg = "Can not find the data node by aipp parameter related_input_rank " + to_string(rank); | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {errormsg}); | |||||
string error_msg = "Can not find the data node by aipp parameter related_input_rank " + to_string(rank); | |||||
GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str()); | |||||
return nullptr; | return nullptr; | ||||
} | } | ||||
Status AippOp::GetAndCheckTarget(const ComputeGraphPtr &graph, int rank, NodePtr &target, | Status AippOp::GetAndCheckTarget(const ComputeGraphPtr &graph, int rank, NodePtr &target, | ||||
@@ -363,10 +352,10 @@ Status AippOp::GetAndCheckTarget(const ComputeGraphPtr &graph, int rank, NodePtr | |||||
} | } | ||||
if (!edge_indexes.empty() && (*edge_indexes.rbegin() >= data_node->GetOutDataNodes().size())) { | if (!edge_indexes.empty() && (*edge_indexes.rbegin() >= data_node->GetOutDataNodes().size())) { | ||||
GELOGE(PARAM_INVALID, "input_edge_idx %u should smaller than out edge size of target input %zu", | |||||
*edge_indexes.rbegin(), data_node->GetOutDataNodes().size()); | |||||
string errormsg = "The aipp parameter input_edge_idx should be smaller than the target input's outnodes."; | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {errormsg}); | |||||
string error_msg = "The aipp parameter input_edge_idx[" + std::to_string(*edge_indexes.rbegin()) + | |||||
"] should be smaller than the target input[" + | |||||
std::to_string(data_node->GetOutDataNodes().size()) +"]'s outnodes."; | |||||
GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str()); | |||||
return PARAM_INVALID; | return PARAM_INVALID; | ||||
} | } | ||||
target = data_node; | target = data_node; | ||||
@@ -439,8 +428,7 @@ Status AippOp::ConvertRelatedInputNameToRank() { | |||||
if (!convert_flag) { | if (!convert_flag) { | ||||
string error_msg = "Top name " + related_input_name + "convert rank failed, Please" | string error_msg = "Top name " + related_input_name + "convert rank failed, Please" | ||||
" ensure top name in aipp config is the top name of data node."; | " ensure top name in aipp config is the top name of data node."; | ||||
ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {error_msg}); | |||||
GELOGE(PARAM_INVALID, "Top name[%s] converts rank failed.", related_input_name.c_str()); | |||||
GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str()); | |||||
return PARAM_INVALID; | return PARAM_INVALID; | ||||
} | } | ||||
@@ -537,87 +525,87 @@ Status AippOp::SetDefaultParams() { | |||||
Status AippOp::ValidateParams() { | Status AippOp::ValidateParams() { | ||||
GE_CHECK_NOTNULL(aipp_params_); | GE_CHECK_NOTNULL(aipp_params_); | ||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->aipp_mode() != domi::AippOpParams::undefined, PARAM_INVALID, | |||||
"When insert AIPP op, aipp_mode must be configured as static or dynamic "); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->var_reci_chn_0_size() <= 1, PARAM_INVALID, | |||||
"The parameter var_reci_chn_0 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->var_reci_chn_1_size() <= 1, PARAM_INVALID, | |||||
"The parameter var_reci_chn_1 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->var_reci_chn_2_size() <= 1, PARAM_INVALID, | |||||
"The parameter var_reci_chn_2 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->var_reci_chn_3_size() <= 1, PARAM_INVALID, | |||||
"The parameter var_reci_chn_3 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->matrix_r0c0_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r0c0 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->matrix_r0c1_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r0c1 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->matrix_r0c2_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r0c2 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->matrix_r1c0_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r1c0 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->matrix_r1c1_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r1c1 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->matrix_r1c2_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r1c2 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->matrix_r2c0_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r2c0 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->matrix_r2c1_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r2c1 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->matrix_r2c2_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r2c2 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->output_bias_0_size() <= 1, PARAM_INVALID, | |||||
"The parameter output_bias_0 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->output_bias_1_size() <= 1, PARAM_INVALID, | |||||
"The parameter output_bias_1 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->output_bias_2_size() <= 1, PARAM_INVALID, | |||||
"The parameter output_bias_2 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->input_bias_0_size() <= 1, PARAM_INVALID, | |||||
"The parameter input_bias_0 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->input_bias_1_size() <= 1, PARAM_INVALID, | |||||
"The parameter input_bias_1 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->input_bias_2_size() <= 1, PARAM_INVALID, | |||||
"The parameter input_bias_2 can not be configed repeatedly"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->input_edge_idx_size() <= 1, PARAM_INVALID, | |||||
"The parameter input_edge_idx can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->aipp_mode() != domi::AippOpParams::undefined, PARAM_INVALID, | |||||
"When insert AIPP op, aipp_mode must be configured as static or dynamic "); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->var_reci_chn_0_size() <= 1, PARAM_INVALID, | |||||
"The parameter var_reci_chn_0 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->var_reci_chn_1_size() <= 1, PARAM_INVALID, | |||||
"The parameter var_reci_chn_1 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->var_reci_chn_2_size() <= 1, PARAM_INVALID, | |||||
"The parameter var_reci_chn_2 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->var_reci_chn_3_size() <= 1, PARAM_INVALID, | |||||
"The parameter var_reci_chn_3 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r0c0_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r0c0 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r0c1_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r0c1 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r0c2_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r0c2 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r1c0_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r1c0 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r1c1_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r1c1 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r1c2_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r1c2 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r2c0_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r2c0 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r2c1_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r2c1 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r2c2_size() <= 1, PARAM_INVALID, | |||||
"The parameter matrix_r2c2 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->output_bias_0_size() <= 1, PARAM_INVALID, | |||||
"The parameter output_bias_0 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->output_bias_1_size() <= 1, PARAM_INVALID, | |||||
"The parameter output_bias_1 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->output_bias_2_size() <= 1, PARAM_INVALID, | |||||
"The parameter output_bias_2 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_bias_0_size() <= 1, PARAM_INVALID, | |||||
"The parameter input_bias_0 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_bias_1_size() <= 1, PARAM_INVALID, | |||||
"The parameter input_bias_1 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_bias_2_size() <= 1, PARAM_INVALID, | |||||
"The parameter input_bias_2 can not be configed repeatedly"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_edge_idx_size() <= 1, PARAM_INVALID, | |||||
"The parameter input_edge_idx can not be configed repeatedly"); | |||||
const domi::AippOpParams::AippMode aipp_mode = aipp_params_->aipp_mode(); | const domi::AippOpParams::AippMode aipp_mode = aipp_params_->aipp_mode(); | ||||
if (aipp_mode == domi::AippOpParams::dynamic) { | if (aipp_mode == domi::AippOpParams::dynamic) { | ||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG( | |||||
GE_CHK_LOG_AND_ERRORMSG( | |||||
aipp_params_->max_src_image_size() > 0, PARAM_INVALID, | aipp_params_->max_src_image_size() > 0, PARAM_INVALID, | ||||
"For dynamic AIPP params, max_src_image_size must be set which number should be greater than 0"); | "For dynamic AIPP params, max_src_image_size must be set which number should be greater than 0"); | ||||
} else { | } else { | ||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->input_format() != domi::AippOpParams::UNDEFINED, PARAM_INVALID, | |||||
"Input format of AIPP conf is undefined"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->src_image_size_w() >= 0, PARAM_INVALID, | |||||
"Src_image_size_w must not be configed smaller than 0"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->src_image_size_h() >= 0, PARAM_INVALID, | |||||
"Src_image_size_h must not be configed smaller than 0"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->load_start_pos_w() >= 0, PARAM_INVALID, | |||||
"Load_start_pos_w must not be configed smaller than 0"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->load_start_pos_h() >= 0, PARAM_INVALID, | |||||
"Load_start_pos_h must not be configed smaller than 0"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->crop_size_w() >= 0, PARAM_INVALID, | |||||
"Crop_size_w must not be configed smaller than 0"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->resize_output_w() >= 0, PARAM_INVALID, | |||||
"Resize_output_w must not be configed smaller than 0"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->resize_output_h() >= 0, PARAM_INVALID, | |||||
"Resize_output_h must not be configed smaller than 0"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->left_padding_size() >= 0, PARAM_INVALID, | |||||
"Left_padding_size must not be configed smaller than 0"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->right_padding_size() >= 0, PARAM_INVALID, | |||||
"Right_padding_size must not be configed smaller than 0"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->top_padding_size() >= 0, PARAM_INVALID, | |||||
"Top_padding_size must not be configed smaller than 0"); | |||||
AIPP_RETURN_STATUS_AND_REPROT_ERRORMSG(aipp_params_->bottom_padding_size() >= 0, PARAM_INVALID, | |||||
"Bottom_padding_size must not be configed smaller than 0"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_format() != domi::AippOpParams::UNDEFINED, PARAM_INVALID, | |||||
"Input format of AIPP conf is undefined"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->src_image_size_w() >= 0, PARAM_INVALID, | |||||
"Src_image_size_w must not be configed smaller than 0"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->src_image_size_h() >= 0, PARAM_INVALID, | |||||
"Src_image_size_h must not be configed smaller than 0"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->load_start_pos_w() >= 0, PARAM_INVALID, | |||||
"Load_start_pos_w must not be configed smaller than 0"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->load_start_pos_h() >= 0, PARAM_INVALID, | |||||
"Load_start_pos_h must not be configed smaller than 0"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->crop_size_w() >= 0, PARAM_INVALID, | |||||
"Crop_size_w must not be configed smaller than 0"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->resize_output_w() >= 0, PARAM_INVALID, | |||||
"Resize_output_w must not be configed smaller than 0"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->resize_output_h() >= 0, PARAM_INVALID, | |||||
"Resize_output_h must not be configed smaller than 0"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->left_padding_size() >= 0, PARAM_INVALID, | |||||
"Left_padding_size must not be configed smaller than 0"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->right_padding_size() >= 0, PARAM_INVALID, | |||||
"Right_padding_size must not be configed smaller than 0"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->top_padding_size() >= 0, PARAM_INVALID, | |||||
"Top_padding_size must not be configed smaller than 0"); | |||||
GE_CHK_LOG_AND_ERRORMSG(aipp_params_->bottom_padding_size() >= 0, PARAM_INVALID, | |||||
"Bottom_padding_size must not be configed smaller than 0"); | |||||
} | } | ||||
return SUCCESS; | return SUCCESS; | ||||
@@ -790,17 +778,20 @@ Status AippOp::CreateAippData(const NodePtr &aipp_node) { | |||||
int64_t batch_count = -1; | int64_t batch_count = -1; | ||||
if (GetDataDimN(data_node, ori_data_format, batch_count) != ge::SUCCESS) { | if (GetDataDimN(data_node, ori_data_format, batch_count) != ge::SUCCESS) { | ||||
GELOGE(PARAM_INVALID, "Get data_node dims and transfer to nchw_dims failed!"); | |||||
string error_msg = "Get data_node dims and transfer to nchw_dims failed!"; | |||||
GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str()); | |||||
return PARAM_INVALID; | return PARAM_INVALID; | ||||
} | } | ||||
if (batch_count <= 0) { | if (batch_count <= 0) { | ||||
GELOGE(PARAM_INVALID, "Batch count %ld is invalid", batch_count); | |||||
string error_msg = "Batch count[" + std::to_string(batch_count) + "] is invalid, it must positive."; | |||||
GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str()); | |||||
return PARAM_INVALID; | return PARAM_INVALID; | ||||
} | } | ||||
int64_t max_dynamic_aipp_size = CalcMaxSize(batch_count); | int64_t max_dynamic_aipp_size = CalcMaxSize(batch_count); | ||||
if (max_dynamic_aipp_size < 0) { | if (max_dynamic_aipp_size < 0) { | ||||
GELOGE(PARAM_INVALID, "The dynamic aipp size is not positive."); | |||||
string error_msg = "The dynamic aipp size is not positive"; | |||||
GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str()); | |||||
return PARAM_INVALID; | return PARAM_INVALID; | ||||
} | } | ||||
@@ -124,19 +124,13 @@ Status InsertNewOpUtil::CheckInputNamePositionNotRepeat() { | |||||
if (another_item->related_input_name().empty()) { | if (another_item->related_input_name().empty()) { | ||||
string error_msg = "Can not both set related_input_name and related_input_rank!" | string error_msg = "Can not both set related_input_name and related_input_rank!" | ||||
" Please ensure param is the same with the first aipp config(related_input_name)."; | " Please ensure param is the same with the first aipp config(related_input_name)."; | ||||
ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {error_msg}); | |||||
GELOGE(PARAM_INVALID, | |||||
"Can not both set related_input_rank and related_input_name!" | |||||
" Please ensure param is the same with the first aipp config(related_input_name)."); | |||||
GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str()); | |||||
return PARAM_INVALID; | return PARAM_INVALID; | ||||
} | } | ||||
if (item->related_input_name() == another_item->related_input_name()) { | if (item->related_input_name() == another_item->related_input_name()) { | ||||
string error_msg = "Can not insert aipp to the same postion! Please ensure related_input_name" | string error_msg = "Can not insert aipp to the same postion! Please ensure related_input_name" | ||||
" param is different in different aipp config."; | " param is different in different aipp config."; | ||||
ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {error_msg}); | |||||
GELOGE(PARAM_INVALID, | |||||
"Can not insert aipp op to the same postion! Please ensure related_input_rank param " | |||||
"is different in different aipp config."); | |||||
GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str()); | |||||
return PARAM_INVALID; | return PARAM_INVALID; | ||||
} | } | ||||
} | } | ||||
@@ -156,19 +150,13 @@ Status InsertNewOpUtil::CheckInputRankPositionNoRepeat() { | |||||
if (!another_item->related_input_name().empty()) { | if (!another_item->related_input_name().empty()) { | ||||
string error_msg = "Can not both set related_input_rank and related_input_name!" | string error_msg = "Can not both set related_input_rank and related_input_name!" | ||||
" Please ensure param is the same with the first aipp config(related_input_rank)."; | " Please ensure param is the same with the first aipp config(related_input_rank)."; | ||||
ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {error_msg}); | |||||
GELOGE(PARAM_INVALID, | |||||
"Can not both set related_input_rank and related_input_name!" | |||||
" Please ensure param is the same with the first aipp config(related_input_rank)."); | |||||
GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str()); | |||||
return PARAM_INVALID; | return PARAM_INVALID; | ||||
} | } | ||||
if (item->related_input_rank() == another_item->related_input_rank()) { | if (item->related_input_rank() == another_item->related_input_rank()) { | ||||
string error_msg = "Can not insert aipp to the same postion! Please ensure related_input_rank" | string error_msg = "Can not insert aipp to the same postion! Please ensure related_input_rank" | ||||
" param is different in different aipp config."; | " param is different in different aipp config."; | ||||
ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {error_msg}); | |||||
GELOGE(PARAM_INVALID, | |||||
"Can not insert aipp op to the same postion! Please ensure related_input_rank param " | |||||
"is different in different aipp config."); | |||||
GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str()); | |||||
return PARAM_INVALID; | return PARAM_INVALID; | ||||
} | } | ||||
} | } | ||||
@@ -224,9 +212,10 @@ Status InsertNewOpUtil::CheckGraph(const ComputeGraphPtr &graph) { | |||||
} | } | ||||
} | } | ||||
} | } | ||||
GE_CHK_BOOL_RET_STATUS((aippNodes.size() == 0) || (aippNodes.size() == next_nodes_cnt), PARAM_INVALID, | |||||
"Can not config part of outputs of Data node to support AIPP, config all " | |||||
"of the outputs of Data to support AIPP, or config none of them"); | |||||
GE_CHK_LOG_AND_ERRORMSG((aippNodes.size() == 0) || (aippNodes.size() == next_nodes_cnt), | |||||
PARAM_INVALID, | |||||
"Can not config part of outputs of Data node to support AIPP, config all " | |||||
"of the outputs of Data to support AIPP, or config none of them"); | |||||
std::unique_ptr<domi::AippOpParams> aippParams(new (std::nothrow) domi::AippOpParams()); | std::unique_ptr<domi::AippOpParams> aippParams(new (std::nothrow) domi::AippOpParams()); | ||||
GE_CHECK_NOTNULL(aippParams); | GE_CHECK_NOTNULL(aippParams); | ||||
@@ -238,16 +227,19 @@ Status InsertNewOpUtil::CheckGraph(const ComputeGraphPtr &graph) { | |||||
GE_CHK_STATUS(GetAippParams(currAippParam, aippNodes[i])); | GE_CHK_STATUS(GetAippParams(currAippParam, aippNodes[i])); | ||||
if (aippMode == domi::AippOpParams::static_) { | if (aippMode == domi::AippOpParams::static_) { | ||||
GE_CHK_BOOL_RET_STATUS(aippParams->input_format() == currAippParam->input_format(), PARAM_INVALID, | |||||
"The input_format of all aipp_ops after one Data should be the same"); | |||||
GE_CHK_BOOL_RET_STATUS(aippParams->src_image_size_w() == currAippParam->src_image_size_w(), PARAM_INVALID, | |||||
"The src_image_size_w of all aipp_ops after one Data should be the same"); | |||||
GE_CHK_BOOL_RET_STATUS(aippParams->src_image_size_h() == currAippParam->src_image_size_h(), PARAM_INVALID, | |||||
"The src_image_size_h of all aipp_ops after one Data should be the same"); | |||||
GE_CHK_LOG_AND_ERRORMSG( | |||||
aippParams->input_format() == currAippParam->input_format(), | |||||
PARAM_INVALID, "The input_format of all aipp_ops after one Data should be the same"); | |||||
GE_CHK_LOG_AND_ERRORMSG( | |||||
aippParams->src_image_size_w() == currAippParam->src_image_size_w(), | |||||
PARAM_INVALID, "The src_image_size_w of all aipp_ops after one Data should be the same"); | |||||
GE_CHK_LOG_AND_ERRORMSG( | |||||
aippParams->src_image_size_h() == currAippParam->src_image_size_h(), | |||||
PARAM_INVALID, "The src_image_size_h of all aipp_ops after one Data should be the same"); | |||||
} else { | } else { | ||||
GE_CHK_BOOL_RET_STATUS(aippParams->max_src_image_size() == currAippParam->max_src_image_size(), | |||||
PARAM_INVALID, | |||||
"The max_src_image_size of all aipp_ops after one Data should be the same"); | |||||
GE_CHK_LOG_AND_ERRORMSG( | |||||
aippParams->max_src_image_size() == currAippParam->max_src_image_size(), | |||||
PARAM_INVALID, "The max_src_image_size of all aipp_ops after one Data should be the same"); | |||||
} | } | ||||
}); | }); | ||||
} | } | ||||
@@ -290,7 +282,8 @@ Status InsertNewOpUtil::UpdateDataNodeByAipp(const ComputeGraphPtr &graph) { | |||||
for (auto &switchn : updated_switchn) { | for (auto &switchn : updated_switchn) { | ||||
auto data_iter = switchn_names_to_data.find(switchn->GetName()); | auto data_iter = switchn_names_to_data.find(switchn->GetName()); | ||||
if (data_iter == switchn_names_to_data.end()) { | if (data_iter == switchn_names_to_data.end()) { | ||||
GELOGE(INTERNAL_ERROR, "Failed to find relative data node by switchn %s", switchn->GetName().c_str()); | |||||
string error_msg = "Failed to find relative data node by switchn[" + switchn->GetName() + "]"; | |||||
GE_ERRORLOG_AND_ERRORMSG(INTERNAL_ERROR, error_msg.c_str()); | |||||
return INTERNAL_ERROR; | return INTERNAL_ERROR; | ||||
} | } | ||||
GE_RETURN_IF_ERROR(UpdateDataBySwitchN(switchn, data_iter->second)); | GE_RETURN_IF_ERROR(UpdateDataBySwitchN(switchn, data_iter->second)); | ||||
@@ -477,7 +470,8 @@ Status InsertNewOpUtil::UpdateDataBySwitchN(const NodePtr &switchn, const NodePt | |||||
} | } | ||||
} | } | ||||
if (max_index >= switchn->GetOpDesc()->GetOutputsSize()) { | if (max_index >= switchn->GetOpDesc()->GetOutputsSize()) { | ||||
GELOGE(INTERNAL_ERROR, "No max size found from switchn node %s", switchn->GetName().c_str()); | |||||
string error_msg = "No max size found from switchn node[" + switchn->GetName()+ "]"; | |||||
GE_ERRORLOG_AND_ERRORMSG(INTERNAL_ERROR, error_msg.c_str()); | |||||
return INTERNAL_ERROR; | return INTERNAL_ERROR; | ||||
} | } | ||||
auto output_desc = switchn->GetOpDesc()->MutableOutputDesc(max_index); | auto output_desc = switchn->GetOpDesc()->MutableOutputDesc(max_index); | ||||
@@ -595,6 +595,8 @@ Status MultiBatchGraphCopyer::CheckCopyResult(const std::vector<NodePtr> &start_ | |||||
} | } | ||||
auto dims = NodeUtils::GetOutputDesc(*node, kDataOutIndex).GetShape().GetDims(); | auto dims = NodeUtils::GetOutputDesc(*node, kDataOutIndex).GetShape().GetDims(); | ||||
if (!IsAllDimsPositive(dims)) { | if (!IsAllDimsPositive(dims)) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage("E15004", {"opname", "shape"}, | |||||
{node->GetName(), formats::ShapeToString(dims)}); | |||||
GELOGE(INTERNAL_ERROR, "Failed to copy multi batch graph, the node %s still has unknown shape %s", | GELOGE(INTERNAL_ERROR, "Failed to copy multi batch graph, the node %s still has unknown shape %s", | ||||
node->GetName().c_str(), formats::ShapeToString(dims).c_str()); | node->GetName().c_str(), formats::ShapeToString(dims).c_str()); | ||||
return INTERNAL_ERROR; | return INTERNAL_ERROR; | ||||
@@ -1025,6 +1027,13 @@ Status MultiBatchGraphCopyer::InsertIdentityAfterSwitchN() { | |||||
} | } | ||||
Status ProcessMultiBatch(ComputeGraphPtr &graph) { | Status ProcessMultiBatch(ComputeGraphPtr &graph) { | ||||
const char *multi_batch_with_case = std::getenv("MULTI_BATCH_WITH_CASE"); | |||||
if (multi_batch_with_case != nullptr) { | |||||
PassManager pass_manager; | |||||
GE_CHK_STATUS_RET(pass_manager.AddPass("MultiBatchClonePass", new (std::nothrow) MultiBatchClonePass)); | |||||
return pass_manager.Run(graph); | |||||
} | |||||
std::vector<std::vector<int64_t>> shapes; | std::vector<std::vector<int64_t>> shapes; | ||||
if (!InitDynamicParams(shapes)) { | if (!InitDynamicParams(shapes)) { | ||||
GELOGD("There is no multi-batch options, no need to process multi-batch copy"); | GELOGD("There is no multi-batch options, no need to process multi-batch copy"); | ||||
@@ -124,6 +124,8 @@ Status ParserDataToDynmaicInfo(const vector<vector<int64_t>> &shapes, | |||||
auto tmp_index = cur_data_index; | auto tmp_index = cur_data_index; | ||||
for (size_t i = 0; i < static_cast<size_t>(dynamic_dims_num); ++i) { | for (size_t i = 0; i < static_cast<size_t>(dynamic_dims_num); ++i) { | ||||
if (tmp_index >= dynamic_gear_info.size()) { | if (tmp_index >= dynamic_gear_info.size()) { | ||||
ErrorManager::GetInstance().ATCReportErrMessage( | |||||
"E10045", {"name", "shape"}, {data_name, formats::JoinToString(data_shape)}); | |||||
GELOGE(PARAM_INVALID, "Data: %s shape: %s make dynamic dims overflow", data_name.c_str(), | GELOGE(PARAM_INVALID, "Data: %s shape: %s make dynamic dims overflow", data_name.c_str(), | ||||
formats::JoinToString(data_shape).c_str()); | formats::JoinToString(data_shape).c_str()); | ||||
return FAILED; | return FAILED; | ||||
@@ -131,6 +133,8 @@ Status ParserDataToDynmaicInfo(const vector<vector<int64_t>> &shapes, | |||||
one_gear.push_back(dynamic_gear_info[tmp_index++]); | one_gear.push_back(dynamic_gear_info[tmp_index++]); | ||||
} | } | ||||
} else { | } else { | ||||
ErrorManager::GetInstance().ATCReportErrMessage( | |||||
"E10046", {"name", "shape"}, {data_name, formats::JoinToString(data_shape)}); | |||||
GELOGE(PARAM_INVALID, "Dynamic dims num of data: %s shape: %s can not be more than one gear dynamic info size", | GELOGE(PARAM_INVALID, "Dynamic dims num of data: %s shape: %s can not be more than one gear dynamic info size", | ||||
data_name.c_str(), formats::JoinToString(data_shape).c_str()); | data_name.c_str(), formats::JoinToString(data_shape).c_str()); | ||||
return FAILED; | return FAILED; | ||||
@@ -100,7 +100,9 @@ Status SliceKernel::Compute(const OpDescPtr attr, const std::vector<ConstGeTenso | |||||
} | } | ||||
// construct tensorDesc | // construct tensorDesc | ||||
ge::GeShape output_shape(output_dims); | ge::GeShape output_shape(output_dims); | ||||
GeTensorDesc output_tensor_desc(output_shape, FORMAT_NCHW, data_type); | |||||
auto attr_output_tensor_desc = attr->GetOutputDesc(0); | |||||
GeTensorDesc output_tensor_desc(attr_output_tensor_desc); | |||||
output_tensor_desc.SetShape(output_shape); | |||||
GeTensorPtr output_ptr = MakeShared<GeTensor>(output_tensor_desc); | GeTensorPtr output_ptr = MakeShared<GeTensor>(output_tensor_desc); | ||||
if (output_ptr == nullptr) { | if (output_ptr == nullptr) { | ||||
GELOGW("make_shared ge::GeTensor failed, node name %s.", attr->GetName().c_str()); | GELOGW("make_shared ge::GeTensor failed, node name %s.", attr->GetName().c_str()); | ||||
@@ -259,7 +259,9 @@ Status NodeDoneCallback::ProfilingReport() { | |||||
return profiling_ret; | return profiling_ret; | ||||
} | } | ||||
ProfilingManager::Instance().ReportProfilingData(task_desc_info, compute_graph_info); | |||||
auto &profiling_manager = ProfilingManager::Instance(); | |||||
profiling_manager.ReportProfilingData(model->GetModelId(), task_desc_info, compute_graph_info, | |||||
!profiling_manager.IsAclApiMode()); | |||||
return SUCCESS; | return SUCCESS; | ||||
} | } | ||||
@@ -17,8 +17,6 @@ | |||||
#include "aicore_node_executor.h" | #include "aicore_node_executor.h" | ||||
#include "cce/taskdown_common.hpp" | #include "cce/taskdown_common.hpp" | ||||
#include "hybrid/executor/hybrid_execution_context.h" | #include "hybrid/executor/hybrid_execution_context.h" | ||||
#include "init/gelib.h" | |||||
#include "hybrid/executor/hybrid_execution_context.h" | |||||
namespace ge { | namespace ge { | ||||
namespace hybrid { | namespace hybrid { | ||||
@@ -28,19 +26,10 @@ AiCoreNodeTask::AiCoreNodeTask(std::vector<std::unique_ptr<AiCoreOpTask>> &&task | |||||
} | } | ||||
Status AiCoreNodeExecutor::Initialize() { | Status AiCoreNodeExecutor::Initialize() { | ||||
auto ge_lib = GELib::GetInstance(); | |||||
GE_CHECK_NOTNULL(ge_lib); | |||||
if (!ge_lib->InitFlag()) { | |||||
GELOGE(GE_CLI_GE_NOT_INITIALIZED, "Ge_lib is uninitialized, failed."); | |||||
return GE_CLI_GE_NOT_INITIALIZED; | |||||
compiler_ = TaskCompilerFactory::GetInstance().GetTaskCompiler(); | |||||
if (compiler_ != nullptr) { | |||||
GE_CHK_STATUS_RET(compiler_->Initialize(), "Failed to init aicore task compiler."); | |||||
} | } | ||||
auto &kernel_manager = ge_lib->OpsKernelManagerObj(); | |||||
auto aic_ops_store = kernel_manager.GetOpsKernelInfoStore("AIcoreEngine"); | |||||
GE_CHECK_NOTNULL(aic_ops_store); | |||||
compiler_.reset(new(std::nothrow)AiCoreTaskCompiler(aic_ops_store)); | |||||
GE_CHECK_NOTNULL(compiler_); | |||||
return SUCCESS; | return SUCCESS; | ||||
} | } | ||||
@@ -120,6 +109,12 @@ Status AiCoreNodeExecutor::CompileTask(const HybridModel &model, | |||||
GE_CHECK_NOTNULL(op_desc); | GE_CHECK_NOTNULL(op_desc); | ||||
GELOGI("AiCoreNodeExecutor(%s) CompileTask Start.", node->GetName().c_str()); | GELOGI("AiCoreNodeExecutor(%s) CompileTask Start.", node->GetName().c_str()); | ||||
auto ori_node_name = node->GetName(); | |||||
if (compiler_ == nullptr) { | |||||
GELOGE(FAILED, "[%s] Can not find any valid aicore task compiler.", ori_node_name.c_str()); | |||||
return FAILED; | |||||
} | |||||
AiCoreNodeTaskRegistry ®istry = AiCoreNodeTaskRegistry::GetInstance(); | AiCoreNodeTaskRegistry ®istry = AiCoreNodeTaskRegistry::GetInstance(); | ||||
std::string shape_key; | std::string shape_key; | ||||
GE_CHK_STATUS_RET(GenNodeKey(node, shape_key), "GenNodeKey failed, op name = %s.", node->GetName().c_str()); | GE_CHK_STATUS_RET(GenNodeKey(node, shape_key), "GenNodeKey failed, op name = %s.", node->GetName().c_str()); | ||||
@@ -133,7 +128,6 @@ Status AiCoreNodeExecutor::CompileTask(const HybridModel &model, | |||||
} | } | ||||
std::vector<domi::TaskDef> task_defs; | std::vector<domi::TaskDef> task_defs; | ||||
auto ori_node_name = node->GetName(); | |||||
op_desc->SetName(ori_node_name + "_" + shape_key); | op_desc->SetName(ori_node_name + "_" + shape_key); | ||||
GE_CHK_STATUS_RET(compiler_->CompileOp(node, task_defs), "Compile op(%s) failed.", ori_node_name.c_str()); | GE_CHK_STATUS_RET(compiler_->CompileOp(node, task_defs), "Compile op(%s) failed.", ori_node_name.c_str()); | ||||
op_desc->SetName(ori_node_name); | op_desc->SetName(ori_node_name); | ||||
@@ -239,5 +233,23 @@ bool AiCoreNodeTask::IsNoOp(TaskContext &task_context) { | |||||
return true; | return true; | ||||
} | } | ||||
TaskCompilerFactory &TaskCompilerFactory::GetInstance() { | |||||
static TaskCompilerFactory instance; | |||||
return instance; | |||||
} | |||||
void TaskCompilerFactory::Register(CreateFn fn) { | |||||
compiler_func_ = fn; | |||||
} | |||||
std::unique_ptr<TaskCompiler> TaskCompilerFactory::GetTaskCompiler() { | |||||
auto compiler_instance = std::unique_ptr<TaskCompiler>(compiler_func_()); | |||||
return compiler_instance; | |||||
} | |||||
CompilerFunctionRegistrar::CompilerFunctionRegistrar(CreateFn fn) { | |||||
TaskCompilerFactory::GetInstance().Register(fn); | |||||
} | |||||
} // namespace hybrid | } // namespace hybrid | ||||
} // namespace ge | } // namespace ge |
@@ -18,13 +18,21 @@ | |||||
#define GE_HYBRID_KERNEL_AICORE_NODE_EXECUTOR_H_ | #define GE_HYBRID_KERNEL_AICORE_NODE_EXECUTOR_H_ | ||||
#include "hybrid/node_executor/aicore/aicore_task_builder.h" | #include "hybrid/node_executor/aicore/aicore_task_builder.h" | ||||
#include "hybrid/node_executor/aicore/aicore_task_compiler.h" | |||||
#include "hybrid/node_executor/node_executor.h" | #include "hybrid/node_executor/node_executor.h" | ||||
#include <map> | #include <map> | ||||
#include <mutex> | #include <mutex> | ||||
namespace ge { | namespace ge { | ||||
namespace hybrid { | namespace hybrid { | ||||
class TaskCompiler { | |||||
public: | |||||
TaskCompiler() = default; | |||||
virtual ~TaskCompiler() = default; | |||||
virtual Status CompileOp(const NodePtr &node, std::vector<domi::TaskDef> &tasks) = 0; | |||||
virtual Status Initialize() = 0; | |||||
}; | |||||
class AiCoreNodeTaskRegistry { | class AiCoreNodeTaskRegistry { | ||||
public: | public: | ||||
~AiCoreNodeTaskRegistry() = default; | ~AiCoreNodeTaskRegistry() = default; | ||||
@@ -65,8 +73,33 @@ class AiCoreNodeExecutor : public NodeExecutor { | |||||
private: | private: | ||||
static Status GenNodeKey(const NodePtr &node, std::string &node_key); | static Status GenNodeKey(const NodePtr &node, std::string &node_key); | ||||
std::unique_ptr<AiCoreTaskCompiler> compiler_; | |||||
std::unique_ptr<TaskCompiler> compiler_; | |||||
}; | |||||
using CreateFn = TaskCompiler *(*)(); | |||||
class TaskCompilerFactory { | |||||
public: | |||||
static TaskCompilerFactory &GetInstance(); | |||||
void Register(CreateFn fn); | |||||
std::unique_ptr<TaskCompiler> GetTaskCompiler(); | |||||
private: | |||||
CreateFn compiler_func_; | |||||
}; | |||||
class CompilerFunctionRegistrar { | |||||
public: | |||||
CompilerFunctionRegistrar(CreateFn fn); | |||||
~CompilerFunctionRegistrar() = default; | |||||
}; | }; | ||||
} // namespace hybrid | } // namespace hybrid | ||||
} // namespace ge | } // namespace ge | ||||
#endif //GE_HYBRID_KERNEL_AICORE_NODE_EXECUTOR_H_ | |||||
#define REGISTER_TASK_COMPILER(compiler) \ | |||||
static ::ge::hybrid::CompilerFunctionRegistrar register_compiler_function \ | |||||
__attribute__((unused)) = \ | |||||
::ge::hybrid::CompilerFunctionRegistrar([]()->::ge::hybrid::TaskCompiler* { \ | |||||
return new (std::nothrow) compiler(); \ | |||||
}) \ | |||||
#endif //GE_HYBRID_KERNEL_AICORE_NODE_EXECUTOR_H_ |
@@ -18,6 +18,7 @@ | |||||
#include "framework/common/debug/log.h" | #include "framework/common/debug/log.h" | ||||
#include "graph/debug/ge_attr_define.h" | #include "graph/debug/ge_attr_define.h" | ||||
#include "opskernel_manager/ops_kernel_builder_manager.h" | #include "opskernel_manager/ops_kernel_builder_manager.h" | ||||
#include "init/gelib.h" | |||||
namespace ge { | namespace ge { | ||||
namespace hybrid { | namespace hybrid { | ||||
@@ -25,11 +26,22 @@ namespace { | |||||
uintptr_t kWeightBase = 0x10000000; | uintptr_t kWeightBase = 0x10000000; | ||||
uintptr_t kMemBase = 0x20000000; | uintptr_t kMemBase = 0x20000000; | ||||
uint64_t kFakeSize = 0x10000000UL; | uint64_t kFakeSize = 0x10000000UL; | ||||
REGISTER_TASK_COMPILER(AiCoreTaskCompiler); | |||||
} | } | ||||
std::mutex AiCoreTaskCompiler::mu_; | std::mutex AiCoreTaskCompiler::mu_; | ||||
AiCoreTaskCompiler::AiCoreTaskCompiler(OpsKernelInfoStorePtr aic_kernel_store) | |||||
: aic_kernel_store_(std::move(aic_kernel_store)) {} | |||||
Status AiCoreTaskCompiler::Initialize() { | |||||
auto ge_lib = GELib::GetInstance(); | |||||
GE_CHECK_NOTNULL(ge_lib); | |||||
if (!ge_lib->InitFlag()) { | |||||
GELOGE(GE_CLI_GE_NOT_INITIALIZED, "Ge_lib is uninitialized, failed."); | |||||
return GE_CLI_GE_NOT_INITIALIZED; | |||||
} | |||||
auto &kernel_manager = ge_lib->OpsKernelManagerObj(); | |||||
aic_kernel_store_ = kernel_manager.GetOpsKernelInfoStore("AIcoreEngine"); | |||||
GE_CHECK_NOTNULL(aic_kernel_store_); | |||||
return SUCCESS; | |||||
} | |||||
Status AiCoreTaskCompiler::DoCompileOp(const NodePtr &node) const { | Status AiCoreTaskCompiler::DoCompileOp(const NodePtr &node) const { | ||||
GE_CHECK_NOTNULL(node); | GE_CHECK_NOTNULL(node); | ||||
@@ -19,15 +19,17 @@ | |||||
#include <mutex> | #include <mutex> | ||||
#include "opskernel_manager/ops_kernel_manager.h" | #include "opskernel_manager/ops_kernel_manager.h" | ||||
#include "aicore_node_executor.h" | |||||
namespace ge { | namespace ge { | ||||
namespace hybrid { | namespace hybrid { | ||||
class AiCoreTaskCompiler { | |||||
class AiCoreTaskCompiler : public TaskCompiler { | |||||
public: | public: | ||||
explicit AiCoreTaskCompiler(OpsKernelInfoStorePtr aic_kernel_store); | |||||
AiCoreTaskCompiler() = default; | |||||
~AiCoreTaskCompiler() = default; | ~AiCoreTaskCompiler() = default; | ||||
Status CompileOp(const NodePtr &node, std::vector<domi::TaskDef> &tasks); | |||||
Status CompileOp(const NodePtr &node, std::vector<domi::TaskDef> &tasks) override; | |||||
Status Initialize() override; | |||||
private: | private: | ||||
Status DoCompileOp(const NodePtr &node) const; | Status DoCompileOp(const NodePtr &node) const; | ||||
Status DoGenerateTask(const Node &node, std::vector<domi::TaskDef> &tasks); | Status DoGenerateTask(const Node &node, std::vector<domi::TaskDef> &tasks); | ||||
@@ -56,6 +56,7 @@ const int kDefaultDeviceIdForInfer = -1; | |||||
const uint32_t kAicoreOverflow = (0x1 << 0); | const uint32_t kAicoreOverflow = (0x1 << 0); | ||||
const uint32_t kAtomicOverflow = (0x1 << 1); | const uint32_t kAtomicOverflow = (0x1 << 1); | ||||
const uint32_t kAllOverflow = (kAicoreOverflow | kAtomicOverflow); | const uint32_t kAllOverflow = (kAicoreOverflow | kAtomicOverflow); | ||||
const char *const kGlobalOptionFpCeilingModeDefault = "2"; | |||||
} // namespace | } // namespace | ||||
static std::shared_ptr<GELib> instancePtr_ = nullptr; | static std::shared_ptr<GELib> instancePtr_ = nullptr; | ||||
@@ -79,6 +80,11 @@ Status GELib::Initialize(const map<string, string> &options) { | |||||
return ret; | return ret; | ||||
} | } | ||||
instancePtr_->SetDefaultPrecisionMode(new_options); | instancePtr_->SetDefaultPrecisionMode(new_options); | ||||
if (new_options.find("ge.fpCeilingMode") == new_options.end()) { | |||||
new_options["ge.fpCeilingMode"] = kGlobalOptionFpCeilingModeDefault; | |||||
} | |||||
GetMutableGlobalOptions().insert(new_options.begin(), new_options.end()); | GetMutableGlobalOptions().insert(new_options.begin(), new_options.end()); | ||||
GetThreadLocalContext().SetGlobalOption(GetMutableGlobalOptions()); | GetThreadLocalContext().SetGlobalOption(GetMutableGlobalOptions()); | ||||
GE_TIMESTAMP_START(Init); | GE_TIMESTAMP_START(Init); | ||||
@@ -32,7 +32,6 @@ | |||||
#include "graph/anchor.h" | #include "graph/anchor.h" | ||||
#include "graph/debug/ge_attr_define.h" | #include "graph/debug/ge_attr_define.h" | ||||
#include "graph/graph.h" | #include "graph/graph.h" | ||||
#include "graph/manager/graph_var_manager.h" | |||||
#include "graph/op_desc.h" | #include "graph/op_desc.h" | ||||
#include "graph/utils/graph_utils.h" | #include "graph/utils/graph_utils.h" | ||||
#include "graph/utils/type_utils.h" | #include "graph/utils/type_utils.h" | ||||
@@ -64,8 +63,6 @@ using std::vector; | |||||
static bool is_dynamic_input = false; | static bool is_dynamic_input = false; | ||||
// 310 limited 8G size | |||||
const char *const kGraphMemoryManagerMallocMaxSize = "8*1024*1024*1024"; | |||||
const char *const kModeSupport = "only support 0(model to framework model), " | const char *const kModeSupport = "only support 0(model to framework model), " | ||||
"1(framework model to json), 3(only pre-check), 5(pbtxt to json)"; | "1(framework model to json), 3(only pre-check), 5(pbtxt to json)"; | ||||
const char *const kModelToJsonSupport = "only support 0(Caffe) 3(TensorFlow) 5(Onnx)"; | const char *const kModelToJsonSupport = "only support 0(Caffe) 3(TensorFlow) 5(Onnx)"; | ||||
@@ -908,13 +905,6 @@ domi::Status GenerateModel(std::map<string, string> &options, std::string output | |||||
return domi::FAILED; | return domi::FAILED; | ||||
} | } | ||||
geRet = ge::VarManager::Instance(0)->SetMemoryMallocSize(options); | |||||
if (geRet != ge::SUCCESS) { | |||||
GELOGE(ge::FAILED, "SetMemoryMallocSize failed."); | |||||
(void)ge::GELib::GetInstance()->Finalize(); | |||||
return domi::FAILED; | |||||
} | |||||
ge::Graph graph; | ge::Graph graph; | ||||
std::vector<ge::GeTensor> inputs; | std::vector<ge::GeTensor> inputs; | ||||
if (FLAGS_framework == domi::MINDSPORE) { | if (FLAGS_framework == domi::MINDSPORE) { | ||||
@@ -1016,7 +1006,6 @@ static void SetEnvForSingleOp(std::map<string, string> &options) { | |||||
options.emplace(ge::OP_SELECT_IMPL_MODE, FLAGS_op_select_implmode); | options.emplace(ge::OP_SELECT_IMPL_MODE, FLAGS_op_select_implmode); | ||||
options.emplace(ge::OPTYPELIST_FOR_IMPLMODE, FLAGS_optypelist_for_implmode); | options.emplace(ge::OPTYPELIST_FOR_IMPLMODE, FLAGS_optypelist_for_implmode); | ||||
options.emplace(ge::AUTO_TUNE_MODE, FLAGS_auto_tune_mode); | options.emplace(ge::AUTO_TUNE_MODE, FLAGS_auto_tune_mode); | ||||
options.emplace(ge::GRAPH_MEMORY_MAX_SIZE, kGraphMemoryManagerMallocMaxSize); | |||||
options.emplace(ge::OP_DEBUG_LEVEL, to_string(FLAGS_op_debug_level)); | options.emplace(ge::OP_DEBUG_LEVEL, to_string(FLAGS_op_debug_level)); | ||||
options.emplace(ge::DEBUG_DIR, FLAGS_debug_dir); | options.emplace(ge::DEBUG_DIR, FLAGS_debug_dir); | ||||
options.emplace(ge::OP_COMPILER_CACHE_DIR, FLAGS_op_compiler_cache_dir); | options.emplace(ge::OP_COMPILER_CACHE_DIR, FLAGS_op_compiler_cache_dir); | ||||
@@ -1053,13 +1042,6 @@ domi::Status GenerateSingleOp(const std::string& json_file_path) { | |||||
return domi::FAILED; | return domi::FAILED; | ||||
} | } | ||||
ret = ge::VarManager::Instance(0)->SetMemoryMallocSize(options); | |||||
if (ret != ge::SUCCESS) { | |||||
GELOGE(ge::FAILED, "SetMemoryMallocSize failed."); | |||||
(void)ge::GELib::GetInstance()->Finalize(); | |||||
return domi::FAILED; | |||||
} | |||||
vector<ge::SingleOpBuildParam> build_params; | vector<ge::SingleOpBuildParam> build_params; | ||||
if (ge::SingleOpParser::ParseSingleOpList(json_file_path, build_params) != ge::SUCCESS) { | if (ge::SingleOpParser::ParseSingleOpList(json_file_path, build_params) != ge::SUCCESS) { | ||||
DOMI_LOGE("parse single op json file failed"); | DOMI_LOGE("parse single op json file failed"); | ||||
@@ -1158,8 +1140,6 @@ domi::Status GenerateOmModel() { | |||||
(FLAGS_enable_compress_weight == "true") ? | (FLAGS_enable_compress_weight == "true") ? | ||||
ge::kEnableCompressWeightTrue : ge::kEnableCompressWeightFalse)); | ge::kEnableCompressWeightTrue : ge::kEnableCompressWeightFalse)); | ||||
options.insert(std::pair<string, string>(string(ge::GRAPH_MEMORY_MAX_SIZE), kGraphMemoryManagerMallocMaxSize)); | |||||
options.insert(std::pair<string, string>(string(ge::ENABLE_SINGLE_STREAM), FLAGS_enable_single_stream)); | options.insert(std::pair<string, string>(string(ge::ENABLE_SINGLE_STREAM), FLAGS_enable_single_stream)); | ||||
options.insert(std::pair<string, string>(string(ge::DEBUG_DIR), FLAGS_debug_dir)); | options.insert(std::pair<string, string>(string(ge::DEBUG_DIR), FLAGS_debug_dir)); | ||||
@@ -485,6 +485,10 @@ Status SetOutputNodeInfo(ge::Graph &graph, const std::string &output_type, const | |||||
GELOGE(domi::FAILED, "Check out node (%s) fail.", user_out_nodes[i].first.c_str()); | GELOGE(domi::FAILED, "Check out node (%s) fail.", user_out_nodes[i].first.c_str()); | ||||
return domi::FAILED; | return domi::FAILED; | ||||
} | } | ||||
// add user_define_output_nodes attr. | |||||
(void)ge::AttrUtils::SetStr(op_desc, ATTR_ATC_USER_DEFINE_OUTPUT_NODES, "true"); | |||||
if (i < output_formats.size()) { | if (i < output_formats.size()) { | ||||
if (output_formats[i] == domi::DOMI_TENSOR_NC1HWC0) { | if (output_formats[i] == domi::DOMI_TENSOR_NC1HWC0) { | ||||
GELOGI("The output node [%s] should be set NC1HWC0", user_out_nodes[i].first.c_str()); | GELOGI("The output node [%s] should be set NC1HWC0", user_out_nodes[i].first.c_str()); | ||||
@@ -339,6 +339,7 @@ const std::set<std::string> ir_builder_suppported_options = {INPUT_FORMAT, | |||||
OUT_NODES, | OUT_NODES, | ||||
INPUT_FP16_NODES, | INPUT_FP16_NODES, | ||||
LOG_LEVEL, | LOG_LEVEL, | ||||
OP_DEBUG_LEVEL, | |||||
DEBUG_DIR, | DEBUG_DIR, | ||||
OP_COMPILER_CACHE_DIR, | OP_COMPILER_CACHE_DIR, | ||||
OP_COMPILER_CACHE_MODE}; | OP_COMPILER_CACHE_MODE}; | ||||
@@ -28,7 +28,7 @@ | |||||
#if !defined(__ANDROID__) && !defined(ANDROID) | #if !defined(__ANDROID__) && !defined(ANDROID) | ||||
#define DOMI_LOGE(...) GE_LOG_ERROR(GE_MODULE_NAME, ge::FAILED, __VA_ARGS__) | #define DOMI_LOGE(...) GE_LOG_ERROR(GE_MODULE_NAME, ge::FAILED, __VA_ARGS__) | ||||
#else | #else | ||||
#include<android/log.h> | |||||
#include <android/log.h> | |||||
#if defined(BUILD_VERSION_PERF) | #if defined(BUILD_VERSION_PERF) | ||||
#define DOMI_LOGE(fmt, ...) | #define DOMI_LOGE(fmt, ...) | ||||
#else | #else | ||||
@@ -83,12 +83,12 @@ | |||||
} while (0); | } while (0); | ||||
// If expr is not GRAPH_SUCCESS, print the log and return FAILED | // If expr is not GRAPH_SUCCESS, print the log and return FAILED | ||||
#define GE_CHK_GRAPH_STATUS_RET(expr, ...) \ | |||||
do { \ | |||||
if ((expr) != ge::GRAPH_SUCCESS) { \ | |||||
DOMI_LOGE(__VA_ARGS__); \ | |||||
return FAILED; \ | |||||
} \ | |||||
#define GE_CHK_GRAPH_STATUS_RET(expr, ...) \ | |||||
do { \ | |||||
if ((expr) != ge::GRAPH_SUCCESS) { \ | |||||
DOMI_LOGE(__VA_ARGS__); \ | |||||
return FAILED; \ | |||||
} \ | |||||
} while (0); | } while (0); | ||||
// If expr is not SUCCESS, print the log and execute a custom statement | // If expr is not SUCCESS, print the log and execute a custom statement | ||||
@@ -99,13 +99,13 @@ | |||||
} while (0); | } while (0); | ||||
// If expr is not true, print the log and return the specified status | // If expr is not true, print the log and return the specified status | ||||
#define GE_CHK_BOOL_RET_STATUS(expr, _status, ...) \ | |||||
do { \ | |||||
bool b = (expr); \ | |||||
if (!b) { \ | |||||
GELOGE(_status, __VA_ARGS__); \ | |||||
return _status; \ | |||||
} \ | |||||
#define GE_CHK_BOOL_RET_STATUS(expr, _status, ...) \ | |||||
do { \ | |||||
bool b = (expr); \ | |||||
if (!b) { \ | |||||
GELOGE(_status, __VA_ARGS__); \ | |||||
return _status; \ | |||||
} \ | |||||
} while (0); | } while (0); | ||||
// If expr is not true, print the log and return the specified status | // If expr is not true, print the log and return the specified status | ||||
@@ -253,4 +253,20 @@ | |||||
exec_expr1; \ | exec_expr1; \ | ||||
} | } | ||||
#define GE_ERRORLOG_AND_ERRORMSG(_status, errormsg) \ | |||||
{ \ | |||||
GELOGE(_status, "%s", errormsg); \ | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {errormsg}); \ | |||||
} | |||||
#define GE_CHK_LOG_AND_ERRORMSG(expr, _status, errormsg) \ | |||||
do { \ | |||||
bool b = (expr); \ | |||||
if (!b) { \ | |||||
GELOGE(_status, "%s", errormsg); \ | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {errormsg}); \ | |||||
return _status; \ | |||||
} \ | |||||
} while (0) | |||||
#endif // INC_FRAMEWORK_COMMON_DEBUG_LOG_H_ | #endif // INC_FRAMEWORK_COMMON_DEBUG_LOG_H_ |
@@ -70,6 +70,7 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY extern const std::string PROFIL | |||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY extern const std::string PROFILE_STOP_VALUE; | FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY extern const std::string PROFILE_STOP_VALUE; | ||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY extern const std::map<std::string, std::string> PROFILE_COMPONENT_MAP; | FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY extern const std::map<std::string, std::string> PROFILE_COMPONENT_MAP; | ||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY extern const std::string PROFILE_CONFIG; | FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY extern const std::string PROFILE_CONFIG; | ||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY extern const std::string PROFILE_MODEL_ID; | |||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY extern const std::string MODEL_ATTR_TASKS; | FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY extern const std::string MODEL_ATTR_TASKS; | ||||
FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY extern const std::string MODEL_ATTR_TASK_GEN_BASE_ADDR; | FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY extern const std::string MODEL_ATTR_TASK_GEN_BASE_ADDR; | ||||
@@ -567,10 +568,10 @@ enum ModelCheckType { | |||||
/// @brief dynamic input type | /// @brief dynamic input type | ||||
/// | /// | ||||
enum DynamicInputType { | enum DynamicInputType { | ||||
FIXED = 0, // default mode | |||||
DYNAMIC_BATCH = 1, | |||||
DYNAMIC_IMAGE = 2, | |||||
DYNAMIC_DIMS = 3 | |||||
FIXED = 0, // default mode | |||||
DYNAMIC_BATCH = 1, | |||||
DYNAMIC_IMAGE = 2, | |||||
DYNAMIC_DIMS = 3 | |||||
}; | }; | ||||
/// | /// | ||||
@@ -38,14 +38,14 @@ class DynamicSingleOp; | |||||
struct RunModelData { | struct RunModelData { | ||||
uint32_t index; // Data index | uint32_t index; // Data index | ||||
uint32_t modelId; | uint32_t modelId; | ||||
std::vector<DataBuffer> blobs; // All input/output data buffer | |||||
uint32_t timestamp; // Data creation time | |||||
uint32_t timeout; // Processing timeout | |||||
uint64_t request_id = 0; // Request ID | |||||
uint64_t dynamic_batch_size = 0; // Dynamic batch size scene, set dynamic size, not supported by default:0 | |||||
uint64_t dynamic_image_height = 0; // Dynamic image size scene, set image height, not supported by default:0 | |||||
uint64_t dynamic_image_width = 0; // Dynamic image size scene, set image width, not supported by default:0 | |||||
std::vector<uint64_t> dynamic_dims; // Dynamic dims scene, set dynamic dims, not supported by default:empty | |||||
std::vector<DataBuffer> blobs; // All input/output data buffer | |||||
uint32_t timestamp; // Data creation time | |||||
uint32_t timeout; // Processing timeout | |||||
uint64_t request_id = 0; // Request ID | |||||
uint64_t dynamic_batch_size = 0; // Dynamic batch size scene, set dynamic size, not supported by default:0 | |||||
uint64_t dynamic_image_height = 0; // Dynamic image size scene, set image height, not supported by default:0 | |||||
uint64_t dynamic_image_width = 0; // Dynamic image size scene, set image width, not supported by default:0 | |||||
std::vector<uint64_t> dynamic_dims; // Dynamic dims scene, set dynamic dims, not supported by default:empty | |||||
}; | }; | ||||
class GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY GeExecutor { | class GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY GeExecutor { | ||||
@@ -264,14 +264,14 @@ class GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY GeExecutor { | |||||
static ge::Status LoadDynamicSingleOp(const std::string &model_name, const ge::ModelData &modelData, void *stream, | static ge::Status LoadDynamicSingleOp(const std::string &model_name, const ge::ModelData &modelData, void *stream, | ||||
DynamicSingleOp **single_op); | DynamicSingleOp **single_op); | ||||
static ge::Status ExecuteAsync(DynamicSingleOp *executor, | |||||
const std::vector<GeTensorDesc> &input_desc, | |||||
const std::vector<DataBuffer> &inputs, | |||||
std::vector<GeTensorDesc> &output_desc, | |||||
static ge::Status ExecuteAsync(DynamicSingleOp *executor, const std::vector<GeTensorDesc> &input_desc, | |||||
const std::vector<DataBuffer> &inputs, std::vector<GeTensorDesc> &output_desc, | |||||
std::vector<DataBuffer> &outputs); | std::vector<DataBuffer> &outputs); | ||||
static ge::Status ReleaseSingleOpResource(void *stream); | static ge::Status ReleaseSingleOpResource(void *stream); | ||||
static ge::Status GetDeviceIdByModelId(uint32_t model_id, uint32_t &device_id); | |||||
ge::Status GetBatchInfoSize(uint32_t model_id, size_t &shape_count); | ge::Status GetBatchInfoSize(uint32_t model_id, size_t &shape_count); | ||||
ge::Status GetOrigInputInfo(uint32_t model_id, uint32_t index, OriginInputInfo &orig_input_info); | ge::Status GetOrigInputInfo(uint32_t model_id, uint32_t index, OriginInputInfo &orig_input_info); | ||||
ge::Status GetAllAippInputOutputDims(uint32_t model_id, uint32_t index, std::vector<InputOutputDims> &input_dims, | ge::Status GetAllAippInputOutputDims(uint32_t model_id, uint32_t index, std::vector<InputOutputDims> &input_dims, | ||||
@@ -1 +1 @@ | |||||
Subproject commit 0d0d2fb016d44f9a575ad8f8c2cb8858bba3acec | |||||
Subproject commit 37465b85d30b67a0edcc6ea4acd2f11a9697c7af |
@@ -1 +1 @@ | |||||
Subproject commit 84ea76e94054fcfac5b80ded6e0ec4db1f37d3e0 | |||||
Subproject commit 5fa1f3ed9b1785b9fd1623d624de91838dff615e |