diff --git a/ge/common/profiling/profiling_manager.cc b/ge/common/profiling/profiling_manager.cc index 86ae7dca..0ea6b1ae 100644 --- a/ge/common/profiling/profiling_manager.cc +++ b/ge/common/profiling/profiling_manager.cc @@ -38,10 +38,8 @@ const std::string kProfModelUnsubscribe = "prof_model_cancel_subscribe"; } // namespace namespace ge { -ProfilingManager::ProfilingManager() : is_load_profiling_(false), - is_execute_profiling_(false), - is_training_trace_(false), - subscribe_count_(0) { +ProfilingManager::ProfilingManager() + : is_load_profiling_(false), is_execute_profiling_(false), is_training_trace_(false), subscribe_count_(0) { prof_cb_.msprofCtrlCallback = nullptr; prof_cb_.msprofReporterCallback = nullptr; } @@ -91,19 +89,18 @@ ge::Status ProfilingManager::InitFromOptions(const Options &options, MsprofGeOpt #ifdef DAVINCI_SUPPORT_PROFILING // enable profiling by env char env_profiling_mode[MMPA_MAX_PATH] = { 0x00 }; - is_load_profiling_ = false; // Change in ProfInit is_execute_profiling_ = false; if (options.profiling_mode == "1" && !options.profiling_options.empty()) { // enable profiling by ge option - if (memcpy_s(prof_conf.options, MSPROF_OPTIONS_DEF_LEN_MAX, options.profiling_options.c_str(), - options.profiling_options.size()) != EOK) { + if (strncpy_s(prof_conf.options, MSPROF_OPTIONS_DEF_LEN_MAX, options.profiling_options.c_str(), + MSPROF_OPTIONS_DEF_LEN_MAX - 1) != EOK) { GELOGE(INTERNAL_ERROR, "copy profiling_options failed."); return INTERNAL_ERROR; } is_execute_profiling_ = true; - GELOGI("The profiling in options is %s, %s. origin option: %s", options.profiling_mode.c_str(), - prof_conf.options, options.profiling_options.c_str()); + GELOGI("The profiling in options is %s, %s. origin option: %s", options.profiling_mode.c_str(), prof_conf.options, + options.profiling_options.c_str()); } else { (void)mmGetEnv("PROFILING_MODE", env_profiling_mode, MMPA_MAX_PATH); (void)mmGetEnv("PROFILING_OPTIONS", prof_conf.options, MSPROF_OPTIONS_DEF_LEN_MAX); @@ -127,11 +124,12 @@ ge::Status ProfilingManager::InitFromOptions(const Options &options, MsprofGeOpt return ge::PARAM_INVALID; } - if (memcpy_s(prof_conf.jobId, sizeof(prof_conf.jobId), options.job_id.c_str(), - sizeof(options.job_id.c_str())) != EOK) { + if (strncpy_s(prof_conf.jobId, MSPROF_OPTIONS_DEF_LEN_MAX, options.job_id.c_str(), + MSPROF_OPTIONS_DEF_LEN_MAX - 1) != EOK) { GELOGE(INTERNAL_ERROR, "copy job_id failed."); return INTERNAL_ERROR; } + GELOGI("Job id: %s, original job id: %s.", prof_conf.jobId, options.job_id.c_str()); #endif return ge::SUCCESS; } @@ -143,6 +141,9 @@ ge::Status ProfilingManager::ParseOptions(const std::string &options) { } try { Json prof_options = Json::parse(options); + if (options.find(kTrainingTrace) == std::string::npos) { + return ge::SUCCESS; + } const std::string training_trace = prof_options[kTrainingTrace]; if (training_trace.empty()) { GELOGI("Training trace will not take effect."); @@ -158,6 +159,7 @@ ge::Status ProfilingManager::ParseOptions(const std::string &options) { if (!fp_point_.empty() && !bp_point_.empty()) { GELOGI("Training trace bp fp is set, bp_point:%s, fp_point:%s.", bp_point_.c_str(), fp_point_.c_str()); } + is_training_trace_ = true; } catch (...) { GELOGE(FAILED, "Json prof_conf options is invalid."); return ge::PARAM_INVALID; @@ -627,6 +629,10 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::ProfSt uint64_t module, const std::map &config_para) { #ifdef DAVINCI_SUPPORT_PROFILING std::lock_guard lock(mutex_); + uint64_t training_trace_mask = module & PROF_TRAINING_TRACE_MASK; + if (training_trace_mask == PROF_TRAINING_TRACE_MASK) { + is_training_trace_ = true; + } int32_t device_num = 0; vector device_list; if (ProfParseParam(config_para, device_num, device_list) != SUCCESS) { diff --git a/ge/graph/build/memory/graph_mem_assigner.cc b/ge/graph/build/memory/graph_mem_assigner.cc index 16d5d38f..b2b67a50 100644 --- a/ge/graph/build/memory/graph_mem_assigner.cc +++ b/ge/graph/build/memory/graph_mem_assigner.cc @@ -402,6 +402,7 @@ Status GraphMemoryAssigner::AssignContinuousInputMemory(const ge::NodePtr &node, GE_ERRORLOG_AND_ERRORMSG(FAILED, error.c_str()); return FAILED; } + continuous_mem_start = iter->second.mem_offset_; for (auto &in_data_anchor : node->GetAllInDataAnchors()) { auto peer_out_data_anchor = in_data_anchor->GetPeerOutAnchor(); GE_IF_BOOL_EXEC(peer_out_data_anchor == nullptr, continue); diff --git a/ge/graph/build/task_generator.cc b/ge/graph/build/task_generator.cc index 7e45ad61..c9ff1914 100644 --- a/ge/graph/build/task_generator.cc +++ b/ge/graph/build/task_generator.cc @@ -567,7 +567,7 @@ Status TaskGenerator::MarkFirstAndLastOps(const vector &ops, bool is_ continue; } string op_type = op_desc->GetType(); - if (!op_desc->GetSubgraphInstanceNames().empty() || separator_types.count(op_type) != 0) { + if ((!is_single_stream && !op_desc->GetSubgraphInstanceNames().empty()) || separator_types.count(op_type) != 0) { continuous_op_lists.emplace_back(vector()); } else { continuous_op_lists.back().emplace_back(op_desc); diff --git a/ge/graph/common/transop_util.cc b/ge/graph/common/transop_util.cc index 9b513fe6..62b4c4e4 100644 --- a/ge/graph/common/transop_util.cc +++ b/ge/graph/common/transop_util.cc @@ -23,7 +23,10 @@ namespace { const int kInvalidTransopDataIndex = -1; const int kTransOpOutIndex = 0; -std::map precision_loss_transfer_map = {{ge::DT_FLOAT, ge::DT_BOOL}}; +std::map precision_loss_transfer_map = { + {ge::DT_FLOAT, ge::DT_BOOL}, + {ge::DT_INT64, ge::DT_BOOL} +}; } // namespace namespace ge { diff --git a/ge/graph/load/graph_loader.cc b/ge/graph/load/graph_loader.cc index 44556422..6b89d6d6 100644 --- a/ge/graph/load/graph_loader.cc +++ b/ge/graph/load/graph_loader.cc @@ -320,10 +320,10 @@ Status GraphLoader::GetMemoryInfo(int64_t &free) { return SUCCESS; } -Status GraphLoader::DestroyAicpuKernel(uint64_t session_id, uint32_t model_id) { +Status GraphLoader::DestroyAicpuKernel(uint64_t session_id, uint32_t model_id, uint32_t sub_model_id) { auto model_manager = ModelManager::GetInstance(); GE_CHECK_NOTNULL(model_manager); - Status ret = model_manager->DestroyAicpuKernel(session_id, model_id); + Status ret = model_manager->DestroyAicpuKernel(session_id, model_id, sub_model_id); if (ret != SUCCESS) { GELOGE(ret, "Destroy aicpu kernel failed."); return ret; diff --git a/ge/graph/load/graph_loader.h b/ge/graph/load/graph_loader.h index 974af5c1..9adf9963 100644 --- a/ge/graph/load/graph_loader.h +++ b/ge/graph/load/graph_loader.h @@ -68,7 +68,7 @@ class GraphLoader { const std::vector &input_desc, OutputData &output_data, std::vector &output_desc); - static Status DestroyAicpuKernel(uint64_t session_id, uint32_t model_id); + static Status DestroyAicpuKernel(uint64_t session_id, uint32_t model_id, uint32_t sub_model_id); static Status DestroyAicpuSessionForInfer(uint32_t model_id); diff --git a/ge/graph/load/new_model_manager/davinci_model.cc b/ge/graph/load/new_model_manager/davinci_model.cc index 02aa3b61..ba2de8d9 100644 --- a/ge/graph/load/new_model_manager/davinci_model.cc +++ b/ge/graph/load/new_model_manager/davinci_model.cc @@ -734,7 +734,6 @@ Status DavinciModel::ReportProfilingData() { } ProfilingManager::Instance().ReportProfilingData(model_id_, GetTaskDescInfo(), compute_graph_desc_info); GE_CHK_STATUS(SinkModelProfile(), "Sink model profiler failed."); - op_list_.clear(); return SUCCESS; } diff --git a/ge/graph/load/new_model_manager/davinci_model.h b/ge/graph/load/new_model_manager/davinci_model.h index 8120ee71..998c2112 100644 --- a/ge/graph/load/new_model_manager/davinci_model.h +++ b/ge/graph/load/new_model_manager/davinci_model.h @@ -136,6 +136,20 @@ class DavinciModel { /// void SetId(uint32_t model_id) { model_id_ = model_id; } + /// + /// @ingroup ge + /// @brief Get SubModelId + /// @return sub model ID + /// + uint32_t SubModelId() const { return sub_model_id_; } + + /// + /// @ingroup ge + /// @brief Set SubModelId + /// @return sub model ID + /// + void SetSubModelId(uint32_t sub_model_id) { sub_model_id_ = sub_model_id; } + static void *Run(DavinciModel *model_pointer); /// @@ -815,6 +829,7 @@ class DavinciModel { uint32_t model_id_; uint32_t runtime_model_id_; + uint32_t sub_model_id_ = 0; string name_; // used for inference data dump diff --git a/ge/graph/load/new_model_manager/model_manager.cc b/ge/graph/load/new_model_manager/model_manager.cc index 80c6191b..55f882e3 100644 --- a/ge/graph/load/new_model_manager/model_manager.cc +++ b/ge/graph/load/new_model_manager/model_manager.cc @@ -81,7 +81,8 @@ ModelManager::ModelManager() { session_id_bias_ = 0; } -Status ModelManager::KernelLaunchEx(aicpu::FWKAdapter::FWKOperateType op_type, uint64_t session_id, uint32_t model_id) { +Status ModelManager::KernelLaunchEx(aicpu::FWKAdapter::FWKOperateType op_type, uint64_t session_id, uint32_t model_id, + uint32_t sub_model_id) { STR_FWK_OP_KERNEL param_base = {}; void *devicebase = nullptr; void *aicpu_kernel_addr = nullptr; @@ -91,10 +92,11 @@ Status ModelManager::KernelLaunchEx(aicpu::FWKAdapter::FWKOperateType op_type, u param_base.fwkKernelBase.fwk_kernel.sessionID = session_id; if (op_type == aicpu::FWKAdapter::FWKOperateType::FWK_ADPT_KERNEL_DESTROY) { std::vector v_aicpu_kernel; - std::string model_key = std::to_string(session_id) + "_" + std::to_string(model_id); + std::string model_key = std::to_string(session_id) + "_" + std::to_string(model_id) + "_" + + std::to_string(sub_model_id); auto iter = model_aicpu_kernel_.find(model_key); if (iter != model_aicpu_kernel_.end()) { - GELOGD("kernel destroy session_id %lu, model_id %u.", session_id, model_id); + GELOGD("kernel destroy session_id %lu, model_id %u, sub_model_id %u..", session_id, model_id, sub_model_id); v_aicpu_kernel = model_aicpu_kernel_.at(model_key); // Insert size of aicpu kernel vector in the first element v_aicpu_kernel.insert(v_aicpu_kernel.begin(), v_aicpu_kernel.size()); @@ -192,7 +194,7 @@ void ModelManager::DestroyAicpuSession(uint64_t session_id) { GE_CHK_RT(rtSetDevice(static_cast(GetContext().DeviceId()))); } - Status ret = KernelLaunchEx(aicpu::FWKAdapter::FWKOperateType::FWK_ADPT_SESSION_DESTROY, session_id, 0); + Status ret = KernelLaunchEx(aicpu::FWKAdapter::FWKOperateType::FWK_ADPT_SESSION_DESTROY, session_id, 0, 0); if (ret != SUCCESS) { GELOGW("The session: %lu destroy failed.", session_id); } else { @@ -218,20 +220,22 @@ ge::Status ModelManager::DestroyAicpuSessionForInfer(uint32_t model_id) { auto it = model_map_.find(model_id); if (it == model_map_.end()) { - GELOGE(GE_EXEC_MODEL_ID_INVALID, "model id %u does not exists.", model_id); - return GE_EXEC_MODEL_ID_INVALID; + GELOGE(ACL_ERROR_GE_EXEC_MODEL_ID_INVALID, "model id %u does not exists.", model_id); + return ACL_ERROR_GE_EXEC_MODEL_ID_INVALID; } uint64_t session_id = it->second->GetSessionId(); DestroyAicpuSession(session_id); return SUCCESS; } -ge::Status ModelManager::DestroyAicpuKernel(uint64_t session_id, uint32_t model_id) { +ge::Status ModelManager::DestroyAicpuKernel(uint64_t session_id, uint32_t model_id, uint32_t sub_model_id) { GELOGD("destroy aicpu kernel in session_id %lu, model_id %u.", session_id, model_id); std::lock_guard lock(map_mutex_); - std::string model_key = std::to_string(session_id) + "_" + std::to_string(model_id); + std::string model_key = std::to_string(session_id) + "_" + std::to_string(model_id) + "_" + + std::to_string(sub_model_id); if (model_aicpu_kernel_.find(model_key) != model_aicpu_kernel_.end()) { - Status ret = KernelLaunchEx(aicpu::FWKAdapter::FWKOperateType::FWK_ADPT_KERNEL_DESTROY, session_id, model_id); + Status ret = KernelLaunchEx(aicpu::FWKAdapter::FWKOperateType::FWK_ADPT_KERNEL_DESTROY, session_id, model_id, + sub_model_id); if (ret != SUCCESS) { GELOGE(FAILED, "Destroy aicpu kernel failed."); return FAILED; @@ -240,10 +244,12 @@ ge::Status ModelManager::DestroyAicpuKernel(uint64_t session_id, uint32_t model_ return SUCCESS; } -ge::Status ModelManager::CreateAicpuKernel(uint64_t session_id, uint32_t model_id, uint64_t kernel_id) { +ge::Status ModelManager::CreateAicpuKernel(uint64_t session_id, uint32_t model_id, uint32_t sub_model_id, + uint64_t kernel_id) { std::lock_guard lock(map_mutex_); std::vector v_aicpu_kernel; - std::string model_key = std::to_string(session_id) + "_" + std::to_string(model_id); + std::string model_key = std::to_string(session_id) + "_" + std::to_string(model_id) + "_" + + std::to_string(sub_model_id); if (model_aicpu_kernel_.find(model_key) != model_aicpu_kernel_.end()) { v_aicpu_kernel = model_aicpu_kernel_.at(model_key); } @@ -378,7 +384,8 @@ Status ModelManager::DeleteModel(uint32_t id) { auto hybrid_model_it = hybrid_model_map_.find(id); if (it != model_map_.end()) { uint64_t session_id = it->second->GetSessionId(); - std::string model_key = std::to_string(session_id) + "_" + std::to_string(id); + std::string model_key = std::to_string(session_id) + "_" + std::to_string(id) + "_" + + std::to_string(it->second->SubModelId()); auto iter_aicpu_kernel = model_aicpu_kernel_.find(model_key); if (iter_aicpu_kernel != model_aicpu_kernel_.end()) { (void)model_aicpu_kernel_.erase(iter_aicpu_kernel); @@ -905,7 +912,7 @@ Status ModelManager::GetInputOutputDescInfo(const uint32_t model_id, vector davinci_model = GetModel(model_id); - GE_CHK_BOOL_RET_STATUS(davinci_model != nullptr, GE_EXEC_MODEL_ID_INVALID, + GE_CHK_BOOL_RET_STATUS(davinci_model != nullptr, ACL_ERROR_GE_EXEC_MODEL_ID_INVALID, "GetInputOutputDescInfo Failed, Invalid model id %u!", model_id); davinci_model->SetModelDescVersion(new_model_desc); @@ -1224,7 +1231,8 @@ Status ModelManager::ExecuteModel(uint32_t model_id, rtStream_t stream, bool asy // Zero copy is enabled by default, no need to judge. uint64_t session_id_davinci = davinci_model->GetSessionId(); uint32_t model_id_davinci = davinci_model->GetModelId(); - Status status = DestroyAicpuKernel(session_id_davinci, model_id_davinci); + uint32_t sub_model_id = davinci_model->SubModelId(); + Status status = DestroyAicpuKernel(session_id_davinci, model_id_davinci, sub_model_id); if (status != SUCCESS) { GELOGW("Destroy specified aicpu kernel failed, session id is %lu, model id is %u.", session_id_davinci, model_id_davinci); @@ -1244,7 +1252,7 @@ Status ModelManager::CreateAicpuSession(uint64_t session_id) { auto it = sess_ids_.find(session_id); // never been created by any model if (it == sess_ids_.end()) { - Status ret = KernelLaunchEx(aicpu::FWKAdapter::FWKOperateType::FWK_ADPT_SESSION_CREATE, session_id, 0); + Status ret = KernelLaunchEx(aicpu::FWKAdapter::FWKOperateType::FWK_ADPT_SESSION_CREATE, session_id, 0, 0); if (ret == SUCCESS) { (void)sess_ids_.insert(session_id); GELOGI("The session: %lu create success.", session_id); @@ -1558,6 +1566,12 @@ Status ModelManager::LaunchKernelCheckAicpuOp(std::vector &aicpu_op size_t aicpu_op_nums = aicpu_optype_list.size(); size_t tf_op_nums = aicpu_tf_optype_list.size(); size_t op_nums = aicpu_op_nums + tf_op_nums; + std::function callback = [&]() { + for (auto mem : allocated_mem) { + GE_CHK_RT(rtFree(mem)); + } + }; + GE_MAKE_GUARD(release, callback); // malloc sysOpInfoList in SysOpCheckInfo status = rtMalloc(&d_req_op_list, op_nums * sizeof(SysOpInfo), RT_MEMORY_HBM); if (status != RT_ERROR_NONE) { @@ -1637,8 +1651,8 @@ Status ModelManager::LaunchKernelCheckAicpuOp(std::vector &aicpu_op return RT_ERROR_TO_GE_STATUS(status); } allocated_mem.push_back(args); - GE_CHK_RT( - rtMemcpy(args, sizeof(SysOpCheckInfo), reinterpret_cast(&op_check_info_req), sizeof(SysOpCheckInfo), RT_MEMCPY_HOST_TO_DEVICE)); + GE_CHK_RT(rtMemcpy(args, sizeof(SysOpCheckInfo), reinterpret_cast(&op_check_info_req), sizeof(SysOpCheckInfo), + RT_MEMCPY_HOST_TO_DEVICE)); GE_CHK_RT(rtMemcpy(reinterpret_cast(static_cast(static_cast(reinterpret_cast(args)) + op_check_info_req.offSetLen)), sizeof(SysOpCheckResp), reinterpret_cast(&op_check_info_res), sizeof(SysOpCheckResp), RT_MEMCPY_HOST_TO_DEVICE)); GE_CHK_RT(rtStreamCreate(&stream, 0)); @@ -1647,24 +1661,21 @@ Status ModelManager::LaunchKernelCheckAicpuOp(std::vector &aicpu_op status = rtStreamSynchronize(stream); if (status != RT_ERROR_NONE) { GELOGE(RT_FAILED, "Call rt stream sync failed, status: 0x%x", status); + GE_CHK_RT(rtStreamDestroy(stream)); return RT_ERROR_TO_GE_STATUS(status); } // Check the response - SysOpCheckResp *d_op_check_info_res = reinterpret_cast(reinterpret_cast(static_cast(static_cast(reinterpret_cast(args)) + op_check_info_req.offSetLen))); + SysOpCheckResp *d_op_check_info_res = + reinterpret_cast(reinterpret_cast(static_cast(static_cast( + reinterpret_cast(args)) + op_check_info_req.offSetLen))); (void)memset_s(&op_check_info_res, sizeof(SysOpCheckResp), 0, sizeof(SysOpCheckResp)); GE_CHK_RT(rtMemcpy(&op_check_info_res, sizeof(SysOpCheckResp), d_op_check_info_res, sizeof(SysOpCheckResp), RT_MEMCPY_DEVICE_TO_HOST)); - std::function callback = [&]() { - for (auto mem : allocated_mem) { - GE_CHK_RT(rtFree(mem)); - } - GE_CHK_RT(rtStreamDestroy(stream)); - }; if (op_check_info_res.isWithoutJson) { GELOGI("No need to check aicpu in this scenoria."); - GE_MAKE_GUARD(release, callback); + GE_CHK_RT(rtStreamDestroy(stream)); return SUCCESS; } uint64_t res_op_nums = op_check_info_res.opListNum; @@ -1682,7 +1693,7 @@ Status ModelManager::LaunchKernelCheckAicpuOp(std::vector &aicpu_op sizeof(SysOpInfo) * res_op_nums, RT_MEMCPY_DEVICE_TO_HOST)); if (res_ret_code_list.size() != res_aicpu_op_info_list.size() || res_ret_code_list.size() != res_op_nums) { GELOGE(FAILED, "Number of retcode is not equal to number of op type."); - GE_MAKE_GUARD(release, callback); + GE_CHK_RT(rtStreamDestroy(stream)); return FAILED; } std::string fail_reason; @@ -1705,11 +1716,11 @@ Status ModelManager::LaunchKernelCheckAicpuOp(std::vector &aicpu_op } fail_reason += "not support."; GELOGE(FAILED, "Check aicpu op_type failed. details: %s", fail_reason.c_str()); - GE_MAKE_GUARD(release, callback); + GE_CHK_RT(rtStreamDestroy(stream)); return FAILED; } - GE_MAKE_GUARD(release, callback); + GE_CHK_RT(rtStreamDestroy(stream)); GELOGI("Cpu kernel launch check optype task success."); return SUCCESS; } diff --git a/ge/graph/load/new_model_manager/model_manager.h b/ge/graph/load/new_model_manager/model_manager.h index dc685519..3310a5a7 100644 --- a/ge/graph/load/new_model_manager/model_manager.h +++ b/ge/graph/load/new_model_manager/model_manager.h @@ -273,7 +273,8 @@ class FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY ModelManager { std::shared_ptr GetHybridModel(uint32_t id); - ge::Status KernelLaunchEx(aicpu::FWKAdapter::FWKOperateType op_type, uint64_t session_id, uint32_t model_id); + ge::Status KernelLaunchEx(aicpu::FWKAdapter::FWKOperateType op_type, uint64_t session_id, uint32_t model_id, + uint32_t sub_model_id); ge::Status CreateAicpuSession(uint64_t session_id); @@ -281,9 +282,9 @@ class FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY ModelManager { void DestroyAicpuSession(uint64_t session_id); - ge::Status DestroyAicpuKernel(uint64_t session_id, uint32_t model_id); + ge::Status DestroyAicpuKernel(uint64_t session_id, uint32_t model_id, uint32_t sub_model_id); - ge::Status CreateAicpuKernel(uint64_t session_id, uint32_t model_id, uint64_t kernel_id); + ge::Status CreateAicpuKernel(uint64_t session_id, uint32_t model_id, uint32_t sub_model_id, uint64_t kernel_id); ge::Status DestroyAicpuSessionForInfer(uint32_t model_id); diff --git a/ge/graph/load/new_model_manager/task_info/kernel_ex_task_info.cc b/ge/graph/load/new_model_manager/task_info/kernel_ex_task_info.cc index e5574e47..5dba0e5d 100644 --- a/ge/graph/load/new_model_manager/task_info/kernel_ex_task_info.cc +++ b/ge/graph/load/new_model_manager/task_info/kernel_ex_task_info.cc @@ -97,14 +97,16 @@ Status KernelExTaskInfo::Init(const domi::TaskDef &task_def, DavinciModel *davin // 2.2 Collect aicpu kernel uint64_t kernel_id = fwk_op_kernel.fwkKernelBase.fwk_kernel.kernelID; - GE_IF_BOOL_EXEC(ModelManager::GetInstance()->CreateAicpuKernel(session_id, davinci_model->Id(), kernel_id) != SUCCESS, + GE_IF_BOOL_EXEC(ModelManager::GetInstance()->CreateAicpuKernel(session_id, davinci_model->Id(), + davinci_model->SubModelId(), kernel_id) != SUCCESS, GELOGE(FAILED, "CreateAicpuKernel error."); return FAILED;) // 2.3 Create session GE_CHECK_NOTNULL(ModelManager::GetInstance()); - GE_IF_BOOL_EXEC(ModelManager::GetInstance()->CreateAicpuSession(session_id) != SUCCESS, - GELOGE(FAILED, "CreateAicpuSession error. session id: %lu", session_id); - return FAILED;) + ret = ModelManager::GetInstance()->CreateAicpuSession(session_id); + GE_IF_BOOL_EXEC(ret != SUCCESS, + GELOGE(ret, "CreateAicpuSession error. session id: %lu", session_id); + return ret;) kernel_buf_size_ = sizeof(STR_FWK_OP_KERNEL); if (davinci_model_->IsKnownNode()) { @@ -132,6 +134,7 @@ Status KernelExTaskInfo::Init(const domi::TaskDef &task_def, DavinciModel *davin GE_IF_BOOL_EXEC(rt_ret != RT_ERROR_NONE, GELOGE(RT_FAILED, "rtMemcpy error, ret: Ox%X", rt_ret); return RT_ERROR_TO_GE_STATUS(rt_ret);) + InitDumpTask(input_output_addr, op_desc); GELOGI("KernelExTaskInfo knonw node Init Success."); return SUCCESS; } @@ -166,11 +169,7 @@ Status KernelExTaskInfo::Init(const domi::TaskDef &task_def, DavinciModel *davin GE_IF_BOOL_EXEC(rt_ret != RT_ERROR_NONE, GELOGE(RT_FAILED, "rtMemcpy to input_output_addr_ error: 0x%X", rt_ret); return RT_ERROR_TO_GE_STATUS(rt_ret);) - if (davinci_model_->GetDumpProperties().IsLayerNeedDump(davinci_model_->Name(), davinci_model_->OmName(), - op_desc->GetName())) { - dump_flag_ = RT_KERNEL_DUMPFLAG; - dump_args_ = input_output_addr_; - } + InitDumpTask(input_output_addr_, op_desc); if (davinci_model_->GetOpDugReg()) { GELOGI("Op debug is open in kernel ex task info"); dump_args_ = input_output_addr_; @@ -200,6 +199,14 @@ Status KernelExTaskInfo::Init(const domi::TaskDef &task_def, DavinciModel *davin return SUCCESS; } +void KernelExTaskInfo::InitDumpTask(void *addr, const OpDescPtr &op_desc) { + if (davinci_model_->GetDumpProperties().IsLayerNeedDump(davinci_model_->Name(), davinci_model_->OmName(), + op_desc->GetName())) { + dump_flag_ = RT_KERNEL_DUMPFLAG; + dump_args_ = input_output_addr_; + } +} + Status KernelExTaskInfo::CalculateArgs(const domi::TaskDef &task_def, DavinciModel *davinci_model) { auto kernel_ex_def = task_def.kernel_ex(); uint32_t op_index = kernel_ex_def.op_index(); diff --git a/ge/graph/load/new_model_manager/task_info/kernel_ex_task_info.h b/ge/graph/load/new_model_manager/task_info/kernel_ex_task_info.h index e4d3e6fd..1c7d7772 100644 --- a/ge/graph/load/new_model_manager/task_info/kernel_ex_task_info.h +++ b/ge/graph/load/new_model_manager/task_info/kernel_ex_task_info.h @@ -60,6 +60,8 @@ class KernelExTaskInfo : public TaskInfo { private: Status CopyTaskInfo(const domi::KernelExDef &kernel_def, const RuntimeParam &rts_param, const OpDescPtr &op_desc); + void InitDumpTask(void *addr, const OpDescPtr &op_desc); + uint32_t task_id_; uint32_t stream_id_; uint32_t dump_flag_; diff --git a/ge/graph/load/new_model_manager/task_info/kernel_task_info.cc b/ge/graph/load/new_model_manager/task_info/kernel_task_info.cc index 74faeb24..01d21e85 100644 --- a/ge/graph/load/new_model_manager/task_info/kernel_task_info.cc +++ b/ge/graph/load/new_model_manager/task_info/kernel_task_info.cc @@ -571,6 +571,8 @@ Status KernelTaskInfo::InitTVMTask(uint16_t offset, const domi::KernelDef &kerne OpDescPtr op_desc = davinci_model_->GetOpByIndex(ctx_.opIndex); GE_CHECK_NOTNULL(op_desc); if (davinci_model_->IsKnownNode()) { + args_ = davinci_model_->GetCurrentArgsAddr(args_offset_); + InitDumpTask(offset); return SUCCESS; } @@ -635,15 +637,7 @@ Status KernelTaskInfo::InitTVMTask(uint16_t offset, const domi::KernelDef &kerne return FAILED; } skt_dump_args_ = static_cast(args_) + offset; - if (davinci_model_->GetDumpProperties().IsLayerNeedDump(davinci_model_->Name(), davinci_model_->OmName(), - op_desc->GetName())) { - if (IsL1FusionOp(op_desc)) { - dump_flag_ = RT_FUSION_KERNEL_DUMPFLAG; - } else { - dump_flag_ = RT_KERNEL_DUMPFLAG; - } - dump_args_ = static_cast(args_) + offset; - } + InitDumpTask(offset); GE_CHK_BOOL_TRUE_EXEC_INFO(davinci_model_->GetOpDugReg(), dump_args_ = static_cast(args_) + offset, "Op debug is open in TVM task info"); @@ -941,16 +935,7 @@ Status KernelTaskInfo::InitAicpuTask(uint32_t op_index, const domi::KernelDef &k GELOGE(RT_FAILED, "Call rt api(rtMemcpy) failed, ret: 0x%X", rt_ret); return RT_ERROR_TO_GE_STATUS(rt_ret); } - - if (davinci_model_->GetDumpProperties().IsLayerNeedDump(davinci_model_->Name(), davinci_model_->OmName(), - op_desc->GetName())) { - if (IsL1FusionOp(op_desc)) { - dump_flag_ = RT_FUSION_KERNEL_DUMPFLAG; - } else { - dump_flag_ = RT_KERNEL_DUMPFLAG; - } - dump_args_ = static_cast(args_) + sizeof(aicpu::AicpuParamHead); - } + InitDumpTask(sizeof(aicpu::AicpuParamHead)); if (davinci_model_->GetOpDugReg()) { GELOGI("Op debug is open in aicpu task info"); dump_args_ = static_cast(args_) + sizeof(aicpu::AicpuParamHead); @@ -964,6 +949,18 @@ Status KernelTaskInfo::InitAicpuTask(uint32_t op_index, const domi::KernelDef &k return SUCCESS; } +void KernelTaskInfo::InitDumpTask(uint32_t offset) { + if (davinci_model_->GetDumpProperties().IsLayerNeedDump(davinci_model_->Name(), davinci_model_->OmName(), + op_desc_->GetName())) { + if (IsL1FusionOp(op_desc_)) { + dump_flag_ = RT_FUSION_KERNEL_DUMPFLAG; + } else { + dump_flag_ = RT_KERNEL_DUMPFLAG; + } + dump_args_ = static_cast(args_) + offset; + } +} + Status KernelTaskInfo::InitAicpuTaskExtInfo(const std::string &ext_info) { if (ext_info.empty()) { return SUCCESS; diff --git a/ge/graph/load/new_model_manager/task_info/kernel_task_info.h b/ge/graph/load/new_model_manager/task_info/kernel_task_info.h index 1f90ede1..2cf95ecc 100644 --- a/ge/graph/load/new_model_manager/task_info/kernel_task_info.h +++ b/ge/graph/load/new_model_manager/task_info/kernel_task_info.h @@ -129,7 +129,9 @@ class KernelTaskInfo : public TaskInfo { Status SuperKernelDistribute(); bool IsL1FusionOp(const OpDescPtr &op_desc); - // For super kernel + void InitDumpTask(uint32_t offset); + + // For super kernel Status SaveSKTDumpInfo(); void UpdateTaskId(); void UpdateSKTTaskId(); diff --git a/ge/graph/manager/graph_manager.cc b/ge/graph/manager/graph_manager.cc index 3beea57f..4b6616e1 100644 --- a/ge/graph/manager/graph_manager.cc +++ b/ge/graph/manager/graph_manager.cc @@ -536,7 +536,7 @@ Status GraphManager::CopySubGraphAndMarkFusion(const ComputeGraphPtr &compute_gr return SUCCESS; } -Status GraphManager::OptimizeSubGraphWithMultiThreads(ComputeGraphPtr compute_graph, +Status GraphManager::OptimizeSubGraphWithMultiThreads(ComputeGraphPtr compute_graph, Graph2SubGraphInfoList &sub_graph_map, uint64_t session_id) { GE_CHECK_NOTNULL(compute_graph); // use default 16 multi thread @@ -737,6 +737,9 @@ Status GraphManager::PreRunAfterOptimizeSubGraph(const GraphNodePtr &graph_node, GeRootModelPtr &ge_root_model, uint64_t session_id) { GE_CHECK_NOTNULL(graph_node); GE_CHECK_NOTNULL(compute_graph); + + CompilerStages &stages = GetCompilerStages(graph_node->GetGraphId()); + GM_RUN_AND_DUMP_PERF("OptimizeWholeGraph", stages.optimizer.OptimizeWholeGraph, compute_graph); GM_RUN_AND_DUMP_PERF("Optimize2", OptimizeStage2, compute_graph); GM_RUN_AND_DUMP_PERF("OptimizeGraphBeforeBuildForRts", GetCompilerStages(graph_node->GetGraphId()).optimizer.OptimizeGraphBeforeBuildForRts, @@ -2439,6 +2442,13 @@ Status GraphManager::CheckAndReleaseMemory(const GeModelPtr &ge_model, const Gra continue; } auto model_id = model->GetModelId(); + // unknown model not release + bool is_unknown_shape = false; + GE_CHK_STATUS_RET(model->CheckIsUnknownShape(is_unknown_shape)); + if (is_unknown_shape) { + GELOGD("model_id[%u] graph_id[%u] is unknown model, not release memory", model_id, graph_id); + continue; + } // not loaded,no need unload if (!it.second->GetLoadFlag()) { GELOGI("CheckAndReleaseMemory graph[%u] has not been loaded.", graph_id); @@ -2456,7 +2466,7 @@ Status GraphManager::CheckAndReleaseMemory(const GeModelPtr &ge_model, const Gra GELOGE(RT_FAILED, "[GraphManager:] rtSetDevice failed, modelId=%u, graphId=%u.", model_id, graph_id); continue; } - result = GraphLoader::DestroyAicpuKernel(session_id, model_id); + result = GraphLoader::DestroyAicpuKernel(session_id, model_id, 0); if (result != SUCCESS) { GELOGW("[GraphManager:] destroy aicpu kernel failed when dynamic memory, modelId=%u, graphId=%u.", model_id, graph_id); diff --git a/ge/graph/optimize/graph_optimize.cc b/ge/graph/optimize/graph_optimize.cc index c94408de..cd80a956 100644 --- a/ge/graph/optimize/graph_optimize.cc +++ b/ge/graph/optimize/graph_optimize.cc @@ -336,4 +336,37 @@ Status GraphOptimize::IdentifyReference(ComputeGraphPtr &compute_graph) { } return SUCCESS; } +Status GraphOptimize::OptimizeWholeGraph(ComputeGraphPtr &compute_graph) { + if (compute_graph == nullptr) { + GELOGE(GE_GRAPH_OPTIMIZE_COMPUTE_GRAPH_NULL, "[OptimizeWholeGraph]: compute_graph is nullptr."); + return GE_GRAPH_OPTIMIZE_COMPUTE_GRAPH_NULL; + } + + std::shared_ptr instance_ptr = ge::GELib::GetInstance(); + if (instance_ptr == nullptr || !instance_ptr->InitFlag()) { + GELOGE(GE_CLI_GE_NOT_INITIALIZED, "OptimizeWholeGraph failed."); + return GE_CLI_GE_NOT_INITIALIZED; + } + + auto graph_optimizer = instance_ptr->OpsKernelManagerObj().GetAllGraphOptimizerObjsByPriority(); + GELOGI("optimize by opskernel in OptimizeWholeGraph. num of graph_optimizer is %zu.", graph_optimizer.size()); + Status ret = SUCCESS; + string exclude_core_type = (core_type_ == kVectorCore) ? kAicoreEngine : kVectorEngine; + GELOGD("[OptimizeWholeGraph]: engine type will exclude: %s", exclude_core_type.c_str()); + if (!graph_optimizer.empty()) { + for (auto &iter : graph_optimizer) { + if (iter.first == exclude_core_type || iter.second == nullptr) { + continue; + } + GELOGI("Begin to optimize whole graph by engine %s", iter.first.c_str()); + ret = iter.second->OptimizeWholeGraph(*compute_graph); + GE_DUMP(compute_graph, "OptimizeWholeGraph" + iter.first); + if (ret != SUCCESS) { + GELOGE(ret, "[OptimizeWholeGraph]: graph optimize failed, ret:%u", ret); + return ret; + } + } + } + return ret; +} } // namespace ge diff --git a/ge/graph/optimize/graph_optimize.h b/ge/graph/optimize/graph_optimize.h index 78d580b7..3a1960f7 100644 --- a/ge/graph/optimize/graph_optimize.h +++ b/ge/graph/optimize/graph_optimize.h @@ -52,6 +52,9 @@ class GraphOptimize { // for fe prepare optimize in quantize scene Status OptimizeOriginalGraphForQuantize(ComputeGraphPtr &compute_graph); + // for engine to optimize merged whole graph before ge Optimize2 + Status OptimizeWholeGraph(ComputeGraphPtr &compute_graph); + // for rts optimize before build to add attr and insert memcpy op Status OptimizeGraphBeforeBuildForRts(ComputeGraphPtr &compute_graph); diff --git a/ge/graph/passes/multi_batch_clone_pass.cc b/ge/graph/passes/multi_batch_clone_pass.cc index 86ea043e..f8451ace 100644 --- a/ge/graph/passes/multi_batch_clone_pass.cc +++ b/ge/graph/passes/multi_batch_clone_pass.cc @@ -22,6 +22,8 @@ #include "graph/preprocess/multi_batch_options.h" #include "graph/utils/node_utils.h" #include "graph/utils/op_desc_utils.h" +#include "graph/utils/tensor_utils.h" +#include "graph/utils/type_utils.h" #include "register/op_registry.h" namespace ge { @@ -478,8 +480,28 @@ Status MultiBatchClonePass::SetMaxShapeToData(const NodePtr &data) { if (std::all_of(dims.begin(), dims.end(), [](int64_t val) { return val >= 0; })) { return SUCCESS; } - (void)AttrUtils::SetListInt(data->GetOpDesc(), ATTR_MBATCH_ORIGIN_INPUT_DIMS, data_shape.GetDims()); + + GeTensorDesc tensor(NodeUtils::GetOutputDesc(*data, kDataOutIndex)); + std::vector input_dims_str; + for (size_t i = 0; i < batch_shapes_.size(); ++i) { + auto shape = data_shape; + auto ret = multibatch::CalcShape(data_to_dynamic_info_.at(data_name).at(i), shape); + if (ret != SUCCESS) { + GELOGE(ret, "Failed to calculate the shape for data node %s, the shape may not match", data->GetName().c_str()); + return ret; + } + tensor.SetShape(shape); + int64_t tensor_size = 0; + (void)TensorUtils::GetTensorSizeInBytes(tensor, tensor_size); + string input_str = TypeUtils::FormatToSerialString(tensor.GetFormat()) + ":" + + TypeUtils::DataTypeToSerialString(tensor.GetDataType()) + ":" + data->GetName() + ":" + + std::to_string(tensor_size) + ":" + std::to_string(tensor.GetShape().GetDimNum()) + ":" + + formats::JoinToString(tensor.GetShape().GetDims()); + input_dims_str.emplace_back(input_str); + } + (void)AttrUtils::SetListStr(data->GetOpDesc(), "_all_origin_gears_inputs", input_dims_str); + size_t max_shape_index = 0; int64_t max_size = 0; for (size_t i = 0; i < batch_shapes_.size(); ++i) { diff --git a/ge/graph/passes/subgraph_const_migration_pass.cc b/ge/graph/passes/subgraph_const_migration_pass.cc index 579b2424..f131942c 100644 --- a/ge/graph/passes/subgraph_const_migration_pass.cc +++ b/ge/graph/passes/subgraph_const_migration_pass.cc @@ -20,11 +20,12 @@ #include "graph/passes/folding_pass.h" namespace ge { -constexpr uint32_t kDataOutIndex = 0; +constexpr uint32_t kZeroIndex = 0; constexpr uint32_t kCaseInputBase = 1; constexpr uint32_t kInvalidParent = 0x7fffffffU; +const string kMbatchNodeNameMark = "_ascend_mbatch_batch_"; -bool IsSameOpNode(const NodePtr &src_node, const NodePtr &dst_node) { +bool IsSameConstNode(const NodePtr &src_node, const NodePtr &dst_node) { if ((src_node == nullptr) && (dst_node == nullptr)) { return true; } @@ -37,35 +38,9 @@ bool IsSameOpNode(const NodePtr &src_node, const NodePtr &dst_node) { return false; } - if ((src_node->GetInControlNodes().size() != dst_node->GetInControlNodes().size()) || - (src_node->GetOutDataNodesSize() != dst_node->GetOutDataNodesSize())) { - return false; - } - - set related_parent; - const auto in_nodes = src_node->GetInControlNodes(); - for (uint32_t i = 0; i < in_nodes.size(); ++i) { - const auto owner_node = in_nodes.at(i); - uint32_t parent_index = 0; - if (!AttrUtils::GetInt(owner_node->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, parent_index)) { - return false; - } - - related_parent.insert(parent_index); - } - - for (const auto &in_node : dst_node->GetInControlNodes()) { - uint32_t parent_index = 0; - if (!AttrUtils::GetInt(in_node->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, parent_index)) { - return false; - } - - if (related_parent.count(parent_index) == 0) { - return false; - } - } - - return true; + const GeTensorDesc &src_desc = src_node->GetOpDesc()->GetOutputDesc(kZeroIndex); + const GeTensorDesc &dst_desc = dst_node->GetOpDesc()->GetOutputDesc(kZeroIndex); + return (src_desc == dst_desc); } /*********************************************************************************************************************** @@ -89,12 +64,12 @@ bool IsSameOpNode(const NodePtr &src_node, const NodePtr &dst_node) { +-----------+ +-----------+ +-----------+ +-----------+ +-----------+ +-----------+ +-----------+ | Data | | Data | | Data | | Data | | Data | | Data | | Conv2D | +-----------+ +-----------+ +-----------+ +-----------+ +-----------+ +-----------+ +-----------+ - \ \ | / / | | - \ \ | / / | | - \ \ | / / | | - \ \ | / / | | - \ +-----------+ / | +-----------+ - +---------------| Const |----------------+ | | Pooling | + \ \ | / / | | +-----------+ + \ \ | / / | | | Const | + \ \ | / / | | +-----------+ + \ \ | / / | | / + \ +-----------+ / | +-----------+ / + +---------------| Const |----------------+ | | Pooling |-----+ +-----------+ | +-----------+ \ | / \ | / @@ -126,28 +101,26 @@ Status SubgraphConstMigrationPass::Run(ComputeGraphPtr graph) { continue; } - do { - migration_append_ = false; - map> graph_datas; - if (ClassifyDataNodes(graph, func_desc, graph_datas) != SUCCESS) { - return FAILED; - } + map> all_const_nodes; + map> all_data_nodes; + if (ClassifyGraphNodes(graph, func_desc, all_const_nodes, all_data_nodes) != SUCCESS) { + return FAILED; + } - if (graph_datas.empty()) { - GELOGW("Graph: %s subgraph is empty", graph->GetName().c_str()); - break; - } + if (all_const_nodes.empty()) { + GELOGW("Graph: %s subgraph is empty", graph->GetName().c_str()); + break; + } - // {subgraph0, {{1, Data}, {2, Data}, {3, Data}, {4, Data}, ..., {n, Data}}} - // {subgraph1, {{1, Data}, {2, Data}, {3, Data}, {4, Data}, ..., {n, Data}}} - // {subgraph2, {{1, Data}, {2, Data}, {3, Data}, {4, Data}, ..., {n, Data}}} - const auto base_nodes = graph_datas.begin()->second; // Need copy. - for (const auto &node_item : base_nodes) { - if (GraphNodeMigration(graph, node, graph_datas, node_item.second, node_item.first) != SUCCESS) { - return FAILED; - } + // {subgraph0, {{key1, Const}, {key2, Const}, {key3, Const}, {key4, Const}, ..., {keyn, Const}}} + // {subgraph1, {{key1, Const}, {key2, Const}, {key3, Const}, {key4, Const}, ..., {keyn, Const}}} + // {subgraph2, {{key1, Const}, {key2, Const}, {key3, Const}, {key4, Const}, ..., {keyn, Const}}} + const auto &const_nodes = all_const_nodes.begin()->second; + for (const auto &item : const_nodes) { + if (GraphNodeMigration(graph, node, all_const_nodes, all_data_nodes, item.second, item.first) != SUCCESS) { + return FAILED; } - } while (migration_append_); + } } return SUCCESS; @@ -155,14 +128,16 @@ Status SubgraphConstMigrationPass::Run(ComputeGraphPtr graph) { /// /// @ingroup ge -/// @brief Get all Data nodes for all subgraph. +/// @brief Get all Const/Data nodes for all subgraph. /// @param [in] graph: Root compute graph. /// @param [in] func_desc: functional OpDesc of Case. -/// @param [out] graph_datas: Data groups of subgraph. +/// @param [out] all_const_nodes: Const groups of subgraph. +/// @param [out] all_data_nodes: Data groups of subgraph. /// @return 0: SUCCESS / others: FAILED /// -Status SubgraphConstMigrationPass::ClassifyDataNodes(const ComputeGraphPtr &graph, const OpDescPtr &func_desc, - map> &graph_datas) { +Status SubgraphConstMigrationPass::ClassifyGraphNodes(const ComputeGraphPtr &graph, const OpDescPtr &func_desc, + map> &all_const_nodes, + map> &all_data_nodes) { for (const auto &name : func_desc->GetSubgraphInstanceNames()) { const auto &subgraph = graph->GetSubgraph(name); if (subgraph == nullptr) { @@ -170,32 +145,47 @@ Status SubgraphConstMigrationPass::ClassifyDataNodes(const ComputeGraphPtr &grap return GE_GRAPH_EMPTY_SUBGRAPH; } - auto &data_nodes = graph_datas[subgraph]; - for (auto &data : subgraph->GetDirectNode()) { - if (data->GetType() != DATA) { - continue; - } + auto &data_nodes = all_data_nodes[subgraph]; + auto &const_nodes = all_const_nodes[subgraph]; + for (auto &node : subgraph->GetDirectNode()) { + if (node->GetType() == DATA) { + uint32_t parent_index = kInvalidParent; + if (!AttrUtils::GetInt(node->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, parent_index)) { + return FAILED; + } - uint32_t parent_index = 0; - if (!AttrUtils::GetInt(data->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, parent_index)) { - GELOGE(FAILED, "Parent index not found, name: %s", data->GetName().c_str()); - return FAILED; - } + data_nodes[parent_index] = node; + GELOGD("%s, index: %u, Data: %s", subgraph->GetName().c_str(), parent_index, node->GetName().c_str()); + } else if ((node->GetType() == CONSTANT) && (node->GetOutDataAnchor(kZeroIndex) != nullptr)) { + set peer_name_list; + const auto &out_anchor = node->GetOutDataAnchor(kZeroIndex); + for (const auto &in_anchor : out_anchor->GetPeerInDataAnchors()) { + const auto &peer_node = in_anchor->GetOwnerNode(); + // Trim subgraph node name prefix. + string node_full_name = peer_node->GetName(); + size_t pos = node_full_name.find(kMbatchNodeNameMark); + if (pos == string::npos) { + GELOGE(FAILED, "find: %s of multi-batch in node: %s", kMbatchNodeNameMark.c_str(), node_full_name.c_str()); + return FAILED; + } + + string fixed_name = node_full_name.substr(0, pos); + pos = node_full_name.find("_", pos + kMbatchNodeNameMark.length()); + if (pos != string::npos) { + fixed_name += node_full_name.substr(pos); + } + + peer_name_list.insert(fixed_name + ":" + std::to_string(in_anchor->GetIdx())); + } - data_nodes[parent_index] = data; - GELOGD("%s, Parent index: %u, Data: %s", subgraph->GetName().c_str(), parent_index, data->GetName().c_str()); - } - } + string key_of_const; + for (const string &name : peer_name_list) { + key_of_const += (key_of_const.empty() ? name : "_" + name); + } - auto iter = graph_datas.begin(); - if (iter == graph_datas.end()) { - return SUCCESS; - } - for (const auto &data_nodes : graph_datas) { - if (data_nodes.second.size() != iter->second.size()) { - GELOGE(FAILED, "Subgraph %s has invalid Data nodes[%zu != %zu]", - data_nodes.first->GetName().c_str(), data_nodes.second.size(), iter->second.size()); - return FAILED; + const_nodes[key_of_const] = node; + GELOGD("%s, Key: %s, Const: %s", subgraph->GetName().c_str(), key_of_const.c_str(), node->GetName().c_str()); + } } } @@ -204,36 +194,27 @@ Status SubgraphConstMigrationPass::ClassifyDataNodes(const ComputeGraphPtr &grap /// /// @ingroup ge -/// @brief Get all Data nodes for all subgraph. -/// @param [in] node: Const node of subgraph. -/// @param [out] inputs: parent index to Const. -/// @param [out] outputs: Data groups of subgraph. +/// @brief Get parent_index for Const node migration. +/// @param [in] all_data_nodes: Data groups of subgraph. +/// @param [in] const_node: Const node will process. +/// @param [out] parent_index: parent index for replace Data. /// @return true: SUCCESS / false: FAILED /// -bool SubgraphConstMigrationPass::GetAssociatedNodes(const NodePtr &node, map &inputs, - map &outputs) { - for (uint32_t i = 0; i < node->GetAllOutDataAnchorsSize(); ++i) { - outputs[i] = kInvalidParent; - } - - uint32_t out_index = 0; - const auto in_nodes = node->GetInAllNodes(); - for (size_t i = 0; i < in_nodes.size(); ++i) { - const auto owner_node = in_nodes.at(i); - if (owner_node->GetType() != DATA) { +bool SubgraphConstMigrationPass::GetAssociatedNodes(const map> &all_data_nodes, + const NodePtr &const_node, uint32_t &parent_index) { + for (const auto in_node : const_node->GetInAllNodes()) { + if (in_node->GetType() != DATA) { return false; } - uint32_t parent_index = 0; - if (!AttrUtils::GetInt(owner_node->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, parent_index)) { + uint32_t node_index = 0; + if (!AttrUtils::GetInt(in_node->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, node_index)) { return false; } // Input Data feed other Node, need add new Data. - inputs[i] = parent_index; - if ((out_index == outputs.size()) && owner_node->GetOutDataNodes().empty()) { - outputs[out_index] = parent_index; - ++out_index; + if ((parent_index == kInvalidParent) && in_node->GetOutDataNodes().empty()) { + parent_index = node_index; } } @@ -242,43 +223,26 @@ bool SubgraphConstMigrationPass::GetAssociatedNodes(const NodePtr &node, map> &graph_datas, - const NodePtr &const_node, uint32_t parent_index, size_t index) { - auto it = graph_datas.begin(); - for (++it; it != graph_datas.end(); ++it) { - const auto &data_nodes = it->second; - auto data_it = data_nodes.find(parent_index); - if (data_it == data_nodes.end()) { - GELOGE(FAILED, "Data: %s not fount, index: %u", const_node->GetName().c_str(), parent_index); - return false; - } - - const auto &work_data = data_it->second; - const auto &out_anchor = work_data->GetOutControlAnchor(); - const auto &in_anchors = out_anchor->GetPeerInControlAnchors(); - if (in_anchors.size() <= index || in_anchors.at(index) == nullptr) { - GELOGW("Node anchors not same, Data: %s -> %s anchor size: %zu, index: %zu", - work_data->GetName().c_str(), const_node->GetName().c_str(), in_anchors.size(), index); - return false; - } - - const auto &in_anchor = in_anchors.at(index); - const auto &work_node = in_anchor->GetOwnerNode(); - if (work_node == nullptr) { - GELOGE(FAILED, "Data: %s not found, parent: %u, index: %zu", const_node->GetName().c_str(), parent_index, index); +bool SubgraphConstMigrationPass::IsParallelNodeSame(const map> &all_const_nodes, + const NodePtr &const_node, const string &node_key) { + auto it = all_const_nodes.begin(); + for (++it; it != all_const_nodes.end(); ++it) { + const auto &const_nodes = it->second; + auto node_it = const_nodes.find(node_key); + if (node_it == const_nodes.end()) { + GELOGW("Const node: %s not fount, key: %s", const_node->GetName().c_str(), node_key.c_str()); return false; } - if (!IsSameOpNode(const_node, work_node)) { - GELOGI("OpDesc not same: %s %s, parent: %u, index: %zu", - const_node->GetName().c_str(), work_node->GetName().c_str(), parent_index, index); + const auto &work_node = node_it->second; + if (!IsSameConstNode(const_node, work_node)) { + GELOGI("Not same: %s %s, key: %s", const_node->GetName().c_str(), work_node->GetName().c_str(), node_key.c_str()); return false; } } @@ -291,51 +255,34 @@ bool SubgraphConstMigrationPass::IsParallelNodeSame(const map> &graph_datas, - const NodePtr &data_node, uint32_t parent_index) { - bool can_extrapolation = false; - do { - can_extrapolation = false; - const auto &out_anchor = data_node->GetOutControlAnchor(); - const auto &in_anchors = out_anchor->GetPeerInControlAnchors(); - for (size_t i = in_anchors.size(); i > 0; --i) { - const auto &in_anchor = in_anchors.at(i - 1); - const auto &work_node = in_anchor->GetOwnerNode(); - GELOGD("Data: %s, node: %s, parent: %u, index: %zu", - data_node->GetName().c_str(), work_node->GetName().c_str(), parent_index, i); - if (work_node->GetType() != CONSTANT) { - continue; - } - - // Get associated Data, if Data feed other nodes, need append new Data. - map inputs; - map outputs; - if (!GetAssociatedNodes(work_node, inputs, outputs)) { - continue; - } + const map> &all_const_nodes, + map> &all_data_nodes, + const NodePtr &const_node, const string &node_key) { + if (!IsParallelNodeSame(all_const_nodes, const_node, node_key)) { + return SUCCESS; + } - if (!IsParallelNodeSame(graph_datas, work_node, parent_index, i - 1)) { - continue; - } + // Get associated Data, if Data feed other nodes, need append new Data. + uint32_t parent_index = kInvalidParent; + if (!GetAssociatedNodes(all_data_nodes, const_node, parent_index)) { + return SUCCESS; + } - GELOGI("Move node: %s, parent: %u, index: %zu", work_node->GetName().c_str(), parent_index, i); - if (AppendParallelNode(graph_datas, func_node, outputs) != SUCCESS) { - return FAILED; - } + GELOGI("Move node: %s, parent index: %u", const_node->GetName().c_str(), parent_index); + if (AppendParallelNode(func_node, parent_index, all_data_nodes) != SUCCESS) { + return FAILED; + } - if (MoveNodeToParent(graph, func_node, graph_datas, parent_index, i - 1, inputs, outputs) != SUCCESS) { - return FAILED; - } - can_extrapolation = true; - break; - } - } while (can_extrapolation); + if (MoveNodeToParent(graph, func_node, all_const_nodes, all_data_nodes, node_key, parent_index) != SUCCESS) { + return FAILED; + } return SUCCESS; } @@ -343,114 +290,100 @@ Status SubgraphConstMigrationPass::GraphNodeMigration(const ComputeGraphPtr &gra /// /// @ingroup ge /// @brief Append Input Tensor for functional node. -/// @param [in] graph_nodes: Data groups of subgraph. /// @param [in] func_node: functional Node of Case. -/// @param [in] outputs: Parent index of Node output. +/// @param [in/out] parent_index: Parent index for migration. +/// @param [in/out] all_data_nodes: Data groups of subgraph. /// @return 0: SUCCESS / others: FAILED /// -Status SubgraphConstMigrationPass::AppendParallelNode(map> &graph_datas, - const NodePtr &func_node, map &outputs) { +Status SubgraphConstMigrationPass::AppendParallelNode(const NodePtr &func_node, uint32_t &parent_index, + map> &all_data_nodes) { // If outputs index invalid, add Data and Input Tensor. - for (auto &item : outputs) { - if (item.second != kInvalidParent) { - continue; - } - - // Add Data to subgraph. - map append_num; - for (auto &groups : graph_datas) { - const auto &subgraph = groups.first; - auto &data_nodes = groups.second; - - item.second = func_node->GetAllInDataAnchorsSize() + append_num[subgraph]; // Update to valid parent index. - const auto data_name = subgraph->GetName() + "_data_" + std::to_string(item.second); - - OpDescBuilder op_builder(data_name, DATA); - const OpDescPtr op_desc = op_builder.AddInput("x").AddOutput("y").Build(); - if (op_desc == nullptr) { - GELOGE(OUT_OF_MEMORY, "Create multi-batch subgraph data desc failed"); - return OUT_OF_MEMORY; - } + if (parent_index != kInvalidParent) { + return SUCCESS; + } - uint32_t data_index = item.second - kCaseInputBase; - if (!AttrUtils::SetInt(op_desc, ATTR_NAME_INDEX, data_index)) { - GELOGE(FAILED, "Parent index not found, name: %s", op_desc->GetName().c_str()); - return FAILED; - } + // Add Data to subgraph. + parent_index = func_node->GetAllInDataAnchorsSize(); // Update to valid parent index. + for (auto &item : all_data_nodes) { + const auto &subgraph = item.first; + const auto data_name = subgraph->GetName() + "_data_" + std::to_string(parent_index); + OpDescBuilder op_builder(data_name, DATA); + const auto op_desc = op_builder.AddInput("x").AddOutput("y").Build(); + if (op_desc == nullptr) { + GELOGE(OUT_OF_MEMORY, "Create multi-batch subgraph data desc failed"); + return OUT_OF_MEMORY; + } - if (!AttrUtils::SetInt(op_desc, ATTR_NAME_PARENT_NODE_INDEX, item.second)) { - GELOGE(FAILED, "Parent index not found, name: %s", op_desc->GetName().c_str()); - return FAILED; - } + uint32_t data_index = parent_index - kCaseInputBase; + if (!AttrUtils::SetInt(op_desc, ATTR_NAME_INDEX, data_index)) { + GELOGE(FAILED, "Parent index not found, name: %s", op_desc->GetName().c_str()); + return FAILED; + } - append_num[subgraph]++; - data_nodes[item.second] = subgraph->AddNode(op_desc); - GELOGI("Add Node: %s, parent index: %u", op_desc->GetName().c_str(), item.second); + if (!AttrUtils::SetInt(op_desc, ATTR_NAME_PARENT_NODE_INDEX, parent_index)) { + GELOGE(FAILED, "Parent index not found, name: %s", op_desc->GetName().c_str()); + return FAILED; } - // Add InputTensor to functional Node. - NodeUtils::AppendInputAnchor(func_node, item.second + 1); + item.second[parent_index] = subgraph->AddNode(op_desc); + GELOGI("Add Node: %s, parent index: %u", op_desc->GetName().c_str(), parent_index); } + // Add InputTensor to functional Node. + NodeUtils::AppendInputAnchor(func_node, parent_index + 1); return SUCCESS; } /// /// @ingroup ge -/// @brief Delete Node from all subgraph. -/// @param [in] graph_nodes: Data groups of subgraph. -/// @param [in] detach: Node will move to parent. -/// @param [in] outputs: Parent index of Node output. +/// @brief Delete Node from subgraph. +/// @param [in] graph: subgraph for process. +/// @param [in] const_node: Node will move to parent. +/// @param [in] data_node: Place holder for Const. /// @return 0: SUCCESS / others: FAILED /// -Status SubgraphConstMigrationPass::DetachParallelNode(const map &graph_datas, const NodePtr &detach, - const map &outputs) { +Status SubgraphConstMigrationPass::DetachParallelNode(const ComputeGraphPtr &graph, const NodePtr &const_node, + const NodePtr &data_node) { // Break Data and Move node. - const auto &in_anchor = detach->GetInControlAnchor(); - const auto &out_anchors = in_anchor->GetPeerOutControlAnchors(); - for (size_t i = out_anchors.size(); i > 0; --i) { - const auto &out_anchor = out_anchors.at(i - 1); + const auto &in_anchor = const_node->GetInControlAnchor(); + const auto out_anchors = in_anchor->GetPeerOutControlAnchors(); + for (const auto out_anchor : out_anchors) { GE_CHK_GRAPH_STATUS_RET(GraphUtils::RemoveEdge(out_anchor, in_anchor), "Remove edge failed"); - const auto &owner_node = out_anchor->GetOwnerNode(); - GELOGI("Remove Edge: %s %s", owner_node->GetName().c_str(), detach->GetName().c_str()); - } - - // Break Move and follow, Link Data and follow. - for (uint32_t i = 0; i < detach->GetAllOutDataAnchorsSize(); ++i) { - auto it_idx = outputs.find(i); - if (it_idx == outputs.end()) { - GELOGE(FAILED, "Node: %s parent index %u not found", detach->GetName().c_str(), i); - return FAILED; - } - - auto it_data = graph_datas.find(it_idx->second); - if (it_data == graph_datas.end()) { - GELOGE(FAILED, "Node: %s parent index %u not found", detach->GetName().c_str(), i); - return FAILED; + const auto owner_node = out_anchor->GetOwnerNode(); + GELOGI("Remove Edge: %s %s", owner_node->GetName().c_str(), const_node->GetName().c_str()); + if (owner_node->GetInAllNodes().empty() && owner_node->GetOutAllNodes().empty() && owner_node != data_node) { + graph->RemoveNode(owner_node); } + } - const auto &data_node = it_data->second; - const auto &out_anchor = detach->GetOutDataAnchor(i); + const auto &ctrl_anchor = const_node->GetOutControlAnchor(); + const auto ctrl_anchors = ctrl_anchor->GetPeerInControlAnchors(); + for (const auto in_anchor : ctrl_anchors) { + GE_CHK_GRAPH_STATUS_RET(GraphUtils::RemoveEdge(ctrl_anchor, in_anchor), "Remove edge failed"); + GELOGI("Remove Edge: %s %s", const_node->GetName().c_str(), in_anchor->GetOwnerNode()->GetName().c_str()); - const auto &out_desc = detach->GetOpDesc()->GetOutputDesc(i); - const auto &data_desc = data_node->GetOpDesc(); - (void)data_desc->UpdateInputDesc(kDataOutIndex, out_desc); // Set Data Input to new connect Node. - (void)data_desc->UpdateOutputDesc(kDataOutIndex, out_desc); // Set Data Output to new connect Node. + GE_CHK_GRAPH_STATUS_RET(GraphUtils::AddEdge(data_node->GetOutControlAnchor(), in_anchor), "Add edge failed"); + GELOGI("Add Edge: %s %s", data_node->GetName().c_str(), in_anchor->GetOwnerNode()->GetName().c_str()); + } - for (const auto &in_anchor : out_anchor->GetPeerInDataAnchors()) { - if (in_anchor == nullptr) { - continue; - } - GE_CHK_GRAPH_STATUS_RET(GraphUtils::RemoveEdge(out_anchor, in_anchor), "Remove edge failed"); - const auto &owner_node = in_anchor->GetOwnerNode(); - GELOGI("Remove Edge: %s %s", detach->GetName().c_str(), owner_node->GetName().c_str()); + // Break Move and follow, Link Data and follow. + const auto &out_anchor = const_node->GetOutDataAnchor(kZeroIndex); + const auto in_anchors =out_anchor->GetPeerInDataAnchors(); + for (const auto in_anchor : in_anchors) { + GE_CHK_GRAPH_STATUS_RET(GraphUtils::RemoveEdge(out_anchor, in_anchor), "Remove edge failed"); + GELOGI("Remove Edge: %s %s", const_node->GetName().c_str(), in_anchor->GetOwnerNode()->GetName().c_str()); - const auto &data_out_anchor = data_node->GetOutDataAnchor(kDataOutIndex); - GE_CHK_GRAPH_STATUS_RET(GraphUtils::AddEdge(data_out_anchor, in_anchor), "Add edge failed"); - GELOGI("Add Edge: %s %s", data_node->GetName().c_str(), owner_node->GetName().c_str()); - } + GE_CHK_GRAPH_STATUS_RET(GraphUtils::AddEdge(data_node->GetOutDataAnchor(kZeroIndex), in_anchor), "Add edge failed"); + GELOGI("Add Edge: %s %s", data_node->GetName().c_str(), in_anchor->GetOwnerNode()->GetName().c_str()); } + // Update Data op DataType. + const auto &const_desc = const_node->GetOpDesc(); + const auto &tensor_desc = const_desc->GetOutputDesc(kZeroIndex); + const auto &data_desc = data_node->GetOpDesc(); + (void)data_desc->UpdateInputDesc(kZeroIndex, tensor_desc); // Set Data Input to new connect Node. + (void)data_desc->UpdateOutputDesc(kZeroIndex, tensor_desc); // Set Data Output to new connect Node. + return SUCCESS; } @@ -459,47 +392,37 @@ Status SubgraphConstMigrationPass::DetachParallelNode(const map &inputs, - const map &outputs) { - GE_CHECK_NOTNULL(attach); - for (const auto item : inputs) { - if (item.second == kInvalidParent) { // Not connect, Skip. - continue; - } - - const auto &in_anchor = func_node->GetInDataAnchor(item.second); - const auto &out_anchor = in_anchor->GetPeerOutAnchor(); - const auto &owner_node = out_anchor->GetOwnerNode(); - const auto &in_control = attach->GetInControlAnchor(); - GE_CHK_GRAPH_STATUS_RET(GraphUtils::AddEdge(owner_node->GetOutControlAnchor(), in_control), "Add edge failed"); - GELOGI("Add Edge: %s %s", owner_node->GetName().c_str(), attach->GetName().c_str()); + const NodePtr &const_node, uint32_t parent_index) { + GE_CHECK_NOTNULL(const_node); + if (parent_index == kInvalidParent) { + return INTERNAL_ERROR; } - for (const auto &item : outputs) { - const auto &func_desc = func_node->GetOpDesc(); - const auto &out_desc = attach->GetOpDesc()->GetOutputDesc(item.second); - (void)func_desc->UpdateInputDesc(item.second, out_desc); // Set Data Input to new connect Node. - - const auto &in_anchor = func_node->GetInDataAnchor(item.second); - const auto &out_anchor = in_anchor->GetPeerOutAnchor(); - if (out_anchor != nullptr) { - GE_CHK_GRAPH_STATUS_RET(GraphUtils::RemoveEdge(out_anchor, in_anchor), "Remove edge failed"); - const auto &owner_node = out_anchor->GetOwnerNode(); - GELOGI("Remove Edge: %s %s", owner_node->GetName().c_str(), func_node->GetName().c_str()); + const auto &func_desc = func_node->GetOpDesc(); + const auto &tensor_desc = const_node->GetOpDesc()->GetOutputDesc(kZeroIndex); + (void)func_desc->UpdateInputDesc(parent_index, tensor_desc); // Set Data Input to new connect Node. + + const auto &in_anchor = func_node->GetInDataAnchor(parent_index); + const auto &out_anchor = in_anchor->GetPeerOutAnchor(); + if (out_anchor != nullptr) { // Break useless old link. + GE_CHK_GRAPH_STATUS_RET(GraphUtils::RemoveEdge(out_anchor, in_anchor), "Remove edge failed"); + const auto owner_node = out_anchor->GetOwnerNode(); + GELOGI("Remove Edge: %s %s", owner_node->GetName().c_str(), func_node->GetName().c_str()); + if (owner_node->GetInAllNodes().empty() && owner_node->GetOutAllNodes().empty()) { + graph->RemoveNode(owner_node); } - GE_CHK_GRAPH_STATUS_RET(GraphUtils::AddEdge(attach->GetOutDataAnchor(item.first), in_anchor), "Add edge failed"); - GELOGI("Add Edge: %s %s", attach->GetName().c_str(), func_node->GetName().c_str()); } + GE_CHK_GRAPH_STATUS_RET(GraphUtils::AddEdge(const_node->GetOutDataAnchor(kZeroIndex), in_anchor), "Add edge failed"); + GELOGI("Add Edge: %s %s, index: %u", const_node->GetName().c_str(), func_node->GetName().c_str(), parent_index); - (void)graph->AddNode(attach); - (void)attach->SetOwnerComputeGraph(graph); - GELOGI("Add Node: %s %s", graph->GetName().c_str(), attach->GetName().c_str()); + (void)graph->AddNode(const_node); + (void)const_node->SetOwnerComputeGraph(graph); + GELOGI("Add Node: %s %s", graph->GetName().c_str(), const_node->GetName().c_str()); return SUCCESS; } @@ -515,43 +438,37 @@ Status SubgraphConstMigrationPass::AttachParallelNode(const ComputeGraphPtr &gra /// @return 0: SUCCESS / others: FAILED /// Status SubgraphConstMigrationPass::MoveNodeToParent(const ComputeGraphPtr &graph, const NodePtr &func_node, - const map> &graph_datas, - uint32_t parent_index, uint32_t index, - const map &inputs, - const map &outputs) { - if (inputs.empty()) { + const map> &all_const_nodes, + const map> &all_data_nodes, + const string &node_key, uint32_t parent_index) { + if (node_key.empty() || parent_index == kInvalidParent) { GELOGE(FAILED, "Graph: %s, inputs is empty", graph->GetName().c_str()); return FAILED; } NodePtr move_node; - for (auto &groups : graph_datas) { - const auto &subgraph = groups.first; - const auto &data_nodes = groups.second; - auto it = data_nodes.find(parent_index); - if (it == data_nodes.end()) { - GELOGE(FAILED, "Graph: %s, Data: %u node not found", subgraph->GetName().c_str(), parent_index); + for (auto &item : all_const_nodes) { + const auto &subgraph = item.first; + const auto it_const = item.second.find(node_key); + if (it_const == item.second.end()) { + GELOGE(FAILED, "Graph: %s, Const: %s node not found", subgraph->GetName().c_str(), node_key.c_str()); return FAILED; } + move_node = it_const->second; - const auto &base_data = it->second; - const auto &out_anchor = base_data->GetOutControlAnchor(); - const auto &in_anchors = out_anchor->GetPeerInControlAnchors(); - if (in_anchors.size() <= index || in_anchors.at(index) == nullptr) { - GELOGE(FAILED, "Data: %s, anchor size: %zu, index: %u not found", - base_data->GetName().c_str(), in_anchors.size(), index); + const auto it_nodes = all_data_nodes.find(subgraph); + if (it_nodes == all_data_nodes.end()) { + GELOGE(FAILED, "Graph: %s, Const: %s node not found", subgraph->GetName().c_str(), node_key.c_str()); return FAILED; } - - const auto &in_anchor = in_anchors.at(index); - move_node = in_anchor->GetOwnerNode(); - if (move_node == nullptr) { - GELOGE(FAILED, "Data: %s not found, index: %u", base_data->GetName().c_str(), parent_index); + const auto it_data = it_nodes->second.find(parent_index); + if (it_data == it_nodes->second.end()) { + GELOGE(FAILED, "Graph: %s, Const: %s node not found", subgraph->GetName().c_str(), node_key.c_str()); return FAILED; } - if (DetachParallelNode(data_nodes, move_node, outputs) != SUCCESS) { - GELOGE(FAILED, "Data: %s not found, index: %u", base_data->GetName().c_str(), parent_index); + if (DetachParallelNode(subgraph, move_node, it_data->second) != SUCCESS) { + GELOGE(FAILED, "Data: %s not found, index: %u", move_node->GetName().c_str(), parent_index); return FAILED; } @@ -559,11 +476,10 @@ Status SubgraphConstMigrationPass::MoveNodeToParent(const ComputeGraphPtr &graph GELOGI("Remove Node: %s %s", subgraph->GetName().c_str(), move_node->GetName().c_str()); } - if (AttachParallelNode(graph, func_node, move_node, inputs, outputs) != SUCCESS) { + if (AttachParallelNode(graph, func_node, move_node, parent_index) != SUCCESS) { return FAILED; } - migration_append_ = true; return SUCCESS; } } // namespace ge diff --git a/ge/graph/passes/subgraph_const_migration_pass.h b/ge/graph/passes/subgraph_const_migration_pass.h index 3c087852..d93da839 100644 --- a/ge/graph/passes/subgraph_const_migration_pass.h +++ b/ge/graph/passes/subgraph_const_migration_pass.h @@ -36,50 +36,54 @@ class SubgraphConstMigrationPass : public GraphPass { private: /// /// @ingroup ge - /// @brief Get all Data nodes for all subgraph. + /// @brief Get all Const/Data nodes for all subgraph. /// @param [in] graph: Root compute graph. /// @param [in] func_desc: functional OpDesc of Case. - /// @param [out] graph_datas: Data groups of subgraph. + /// @param [out] all_const_nodes: Const groups of subgraph. + /// @param [out] all_data_nodes: Data groups of subgraph. /// @return 0: SUCCESS / others: FAILED /// - Status ClassifyDataNodes(const ComputeGraphPtr &graph, const OpDescPtr &func_desc, - map> &graph_datas); + Status ClassifyGraphNodes(const ComputeGraphPtr &graph, const OpDescPtr &func_desc, + map> &all_const_nodes, + map> &all_data_nodes); /// /// @ingroup ge - /// @brief Get all Data nodes for all subgraph. - /// @param [in] node: Const node of subgraph. - /// @param [in] func_desc: functional OpDesc of Case. - /// @param [out] graph_nodes: Data groups of subgraph. + /// @brief Get parent_index for Const node migration. + /// @param [in] all_data_nodes: Data groups of subgraph. + /// @param [in] const_node: Const node will process. + /// @param [out] parent_index: parent index for replace Data. /// @return true: SUCCESS / false: FAILED /// - bool GetAssociatedNodes(const NodePtr &node, map &inputs, map &outputs); + bool GetAssociatedNodes(const map> &all_data_nodes, + const NodePtr &const_node, uint32_t &parent_index); /// /// @ingroup ge - /// @brief Get all Data nodes for all subgraph. - /// @param [in] graph_nodes: Data groups of subgraph. - /// @param [in] data_base: Data Node for migration. - /// @param [in] data_idx: Data groups of subgraph. - /// @param [in] data_idx: Data groups of subgraph. + /// @brief Check parallel node is same for all subgraph. + /// @param [in] all_const_nodes: Const groups of subgraph. + /// @param [in] const_node: Const Node for migration. + /// @param [in] node_key: Key of Const node. /// @return true: Same / false: not same /// - bool IsParallelNodeSame(const map> &graph_nodes, - const NodePtr &const_node, uint32_t parent_index, size_t index); + bool IsParallelNodeSame(const map> &all_const_nodes, + const NodePtr &const_node, const string &node_key); /// /// @ingroup ge /// @brief Migration subgraph Node to Root /// @param [in] graph: Root compute graph. /// @param [in] func_node: functional Node of Case. - /// @param [in] graph_nodes: Data groups of subgraph. - /// @param [in] data_base: Data Node for migration. - /// @param [in] data_idx: Data groups of subgraph. + /// @param [in] all_const_nodes: Const groups of subgraph. + /// @param [in] all_data_nodes: Data groups of subgraph. + /// @param [in] const_node: Const Node for migration. + /// @param [in] node_key: Key of Const node for migration. /// @return 0: SUCCESS / others: FAILED /// Status GraphNodeMigration(const ComputeGraphPtr &graph, const NodePtr &func_node, - map> &graph_nodes, - const NodePtr &data_base, uint32_t data_idx); + const map> &all_const_nodes, + map> &all_data_nodes, + const NodePtr &const_node, const string &node_key); /// /// @ingroup ge @@ -93,46 +97,42 @@ class SubgraphConstMigrationPass : public GraphPass { /// @return 0: SUCCESS / others: FAILED /// Status MoveNodeToParent(const ComputeGraphPtr &graph, const NodePtr &func_node, - const map> &graph_nodes, - uint32_t parent_index, uint32_t anchor_idx, - const map &inputs, const map &outputs); + const map> &all_const_nodes, + const map> &all_data_nodes, + const string &node_key, uint32_t parent_index); /// /// @ingroup ge /// @brief Append Input Tensor for functional node. - /// @param [in] graph_nodes: Data groups of subgraph. - /// @param [in] func_node: functional Node of Case. - /// @param [in] outputs: Parent index of Node output. + /// @param [in] graph_nodes: Const groups of subgraph. + /// @param [in/out] parent_index: Parent index for migration. + /// @param [in/out] all_data_nodes: Data groups of subgraph. /// @return 0: SUCCESS / others: FAILED /// - Status AppendParallelNode(map> &graph_nodes, - const NodePtr &func_node, map &outputs); + Status AppendParallelNode(const NodePtr &func_node, uint32_t &parent_index, + map> &all_data_nodes); /// /// @ingroup ge - /// @brief Delete Node from all subgraph. - /// @param [in] graph_nodes: Data groups of subgraph. - /// @param [in] detach: Node will move to parent. - /// @param [in] outputs: Parent index of Node output. + /// @brief Delete Node from subgraph. + /// @param [in] graph: subgraph for process. + /// @param [in] const_node: Node will move to parent. + /// @param [in] data_node: Place holder for Const. /// @return 0: SUCCESS / others: FAILED /// - Status DetachParallelNode(const map &graph_datas, const NodePtr &detach, - const map &outputs); + Status DetachParallelNode(const ComputeGraphPtr &graph, const NodePtr &const_node, const NodePtr &data_node); /// /// @ingroup ge /// @brief Move Node to Parent Graph. /// @param [in] graph: Parent compute graph. /// @param [in] func_node: functional Node of Case. - /// @param [in] attach: Node will move to parent. - /// @param [in] inputs: Parent index of Node input. - /// @param [in] outputs: Parent index of Node output. + /// @param [in] const_node: Node will move to parent. + /// @param [in] parent_index: Parent index of Node input. /// @return 0: SUCCESS / others: FAILED /// - Status AttachParallelNode(const ComputeGraphPtr &graph, const NodePtr &func_node, const NodePtr &attach, - const map &inputs, const map &outputs); - - bool migration_append_{false}; + Status AttachParallelNode(const ComputeGraphPtr &graph, const NodePtr &func_node, + const NodePtr &const_node, uint32_t parent_index); }; } // namespace ge #endif // GE_COMMON_SUBGRAPH_CONST_MIGRATION_H_ \ No newline at end of file diff --git a/ge/graph/preprocess/graph_preprocess.cc b/ge/graph/preprocess/graph_preprocess.cc index 2ee5e330..27c54f03 100644 --- a/ge/graph/preprocess/graph_preprocess.cc +++ b/ge/graph/preprocess/graph_preprocess.cc @@ -1646,6 +1646,10 @@ Status GraphPrepare::InferShapeForPreprocess() { if (!options_.train_graph_flag) { names_to_passes.emplace_back("AssertPass", &assert_pass); } + SwitchDeadBranchElimination switch_dead_branch_elimination; + names_to_passes.emplace_back("SwitchDeadBranchElimination", &switch_dead_branch_elimination); + MergePass merge_pass; + names_to_passes.emplace_back("MergePass", &merge_pass); InferShapePass infer_shape_pass; names_to_passes.emplace_back("InferShapePass", &infer_shape_pass); ReplaceWithEmptyConstPass replace_with_empty_const_pass; diff --git a/ge/hybrid/node_executor/compiledsubgraph/known_node_executor.cc b/ge/hybrid/node_executor/compiledsubgraph/known_node_executor.cc index f985a3d0..7f2c6288 100644 --- a/ge/hybrid/node_executor/compiledsubgraph/known_node_executor.cc +++ b/ge/hybrid/node_executor/compiledsubgraph/known_node_executor.cc @@ -123,11 +123,22 @@ Status KnownNodeTask::Init(TaskContext &context) { davinci_model_->GetRuntimeParam().mem_base, davinci_model_->GetRuntimeParam().mem_size); } if (!load_flag_) { + auto dump_properties = context.GetDumpProperties(); + if (dump_properties.IsDumpOpen()) { + davinci_model_->SetDumpProperties(dump_properties); + } + int32_t device_id = 0; + rtError_t rt_ret = rtGetDevice(&device_id); + if (rt_ret != RT_ERROR_NONE || device_id < 0) { + GELOGE(rt_ret, "Call rtGetDevice failed, ret = 0x%X, device_id = %d.", rt_ret, device_id); + return RT_ERROR_TO_GE_STATUS(rt_ret); + } + davinci_model_->SetDeviceId(device_id); GE_CHK_STATUS_RET(davinci_model_->Init(), "KnownNodeExecutor::InitDavinciModel failed."); load_flag_ = true; } else { GE_CHK_STATUS_RET(ModelManager::GetInstance()->DestroyAicpuKernel(davinci_model_->GetSessionId(), - davinci_model_->Id()), "KnownNodeTask::Init destroy aicpu kernel failed."); + davinci_model_->Id(), davinci_model_->SubModelId()), "KnownNodeTask::Init destroy aicpu kernel failed."); } GELOGI("[%s] KnownNodeExecutor::Init success.", context.GetNodeName()); return SUCCESS; @@ -161,8 +172,9 @@ Status KnownNodeExecutor::LoadTask(const HybridModel &model, const NodePtr &node // set known node flag as true davinci_model->SetKnownNode(true); + davinci_model->SetId(model.GetModelId()); // set model id as root node's node id - davinci_model->SetId(node->GetOpDesc()->GetId()); + davinci_model->SetSubModelId(node->GetOpDesc()->GetId()); GELOGD("KnownNodeExecutor::LoadTask node id %ld.", node->GetOpDesc()->GetId()); GE_CHK_STATUS_RET(davinci_model->Assign(ge_model), "KnownNodeExecutor::LoadTask davincimodel assign failed."); diff --git a/ge/ir_build/ge_ir_build.cc b/ge/ir_build/ge_ir_build.cc index c7ef6c1a..92647d1a 100644 --- a/ge/ir_build/ge_ir_build.cc +++ b/ge/ir_build/ge_ir_build.cc @@ -581,42 +581,6 @@ graphStatus aclgrphGetIRVersion(int *major_version, int *minor_version, int *pat return GRAPH_SUCCESS; } -graphStatus aclgrphInferShapeAndType(ge::Graph &graph) { - auto compute_graph = GraphUtils::GetComputeGraph(graph); - GE_CHECK_NOTNULL(compute_graph); - - auto root_graph = compute_graph->GetParentGraph(); - if (root_graph != nullptr) { - GELOGE(GRAPH_PARAM_INVALID, "Input param should not be subgraph"); - return GRAPH_PARAM_INVALID; - } - - auto ret = compute_graph->TopologicalSorting(); - if (ret != GRAPH_SUCCESS) { - GELOGE(ret, "Acl topo logical sort failed."); - return ret; - } - - ret = compute_graph->InferOriginFormat(); - if (ret != GRAPH_SUCCESS) { - GELOGE(ret, "Acl InferOriginFormat failed."); - return ret; - } - - for (auto &node: compute_graph->GetAllNodes()) { - graphStatus ret = ShapeRefiner::InferShapeAndType(node); - if (ret == GRAPH_PARAM_INVALID) { - GELOGW("Can not find infershape func."); - continue; - } else if (ret != GRAPH_SUCCESS) { - GELOGE(ret, "Acl infershape failed."); - return ret; - } - } - - return GRAPH_SUCCESS; -} - graphStatus aclgrphDumpGraph(const ge::Graph &graph, const char *file, const size_t len) { GE_CHECK_NOTNULL(file); diff --git a/ge/omm/csa_interact.cc b/ge/omm/csa_interact.cc index 1b33ddbd..f1d59f41 100644 --- a/ge/omm/csa_interact.cc +++ b/ge/omm/csa_interact.cc @@ -78,8 +78,8 @@ void CsaInteract::Init(int32_t dev_index, int64_t job_id) { Status CsaInteract::WriteJobState(JobState job_state, JobSubState job_sub_state, uint32_t module_ret_errcode, ErrorModule error_module) { if (!is_init_) { - GELOGE(INTERNAL_ERROR, "CsaInteract has not init, can't WriteJobState"); - return INTERNAL_ERROR; + GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "CsaInteract has not init, can't WriteJobState"); + return ACL_ERROR_GE_INTERNAL_ERROR; } if ((curr_state_ == JOBSTATE_FAILED) || (curr_state_ == JOBSTATE_KILLED)) { return SUCCESS; diff --git a/inc/external/acl/acl_prof.h b/inc/external/acl/acl_prof.h index 97a81b53..990c70cf 100644 --- a/inc/external/acl/acl_prof.h +++ b/inc/external/acl/acl_prof.h @@ -26,7 +26,7 @@ extern "C" { #define ACL_PROF_ACL_API 0x0001 #define ACL_PROF_TASK_TIME 0x0002 #define ACL_PROF_AICORE_METRICS 0x0004 -#define ACL_PROF_AICPU_TRACE 0x0008 +#define ACL_PROF_AICPU 0x0008 #define ACL_PROF_MAX_OP_NAME_LEN 257 #define ACL_PROF_MAX_OP_TYPE_LEN 65 @@ -289,34 +289,8 @@ ACL_FUNC_VISIBILITY uint64_t aclprofGetOpDuration(const void *opInfo, size_t opI */ ACL_FUNC_VISIBILITY size_t aclprofGetModelId(const void *opInfo, size_t opInfoLen, uint32_t index); -/** - * @ingroup AscendCL - * @brief get cube ops from subscription data - * - * @param opInfo [IN] pointer to subscription data - * @param opInfoLen [IN] memory size of subscription data - * @param index [IN] index of op array in opInfo - * - * @retval cube ops of subscription data - * @retval 0 for failed - */ -ACL_FUNC_VISIBILITY uint64_t aclprofGetOpCubeOps(const void *opInfo, size_t opInfoLen, uint32_t index); - -/** - * @ingroup AscendCL - * @brief get vector ops from subscription data - * - * @param opInfo [IN] pointer to subscription data - * @param opInfoLen [IN] memory size of subscription data - * @param index [IN] index of op array in opInfo - * - * @retval vector ops of subscription data - * @retval 0 for failed - */ -ACL_FUNC_VISIBILITY uint64_t aclprofGetOpVectorOps(const void *opInfo, size_t opInfoLen, uint32_t index); - #ifdef __cplusplus } #endif -#endif // INC_EXTERNAL_ACL_PROF_H_ \ No newline at end of file +#endif // INC_EXTERNAL_ACL_PROF_H_ diff --git a/inc/external/acl/ops/acl_fv.h b/inc/external/acl/ops/acl_fv.h index 4dc518c5..27dc367a 100644 --- a/inc/external/acl/ops/acl_fv.h +++ b/inc/external/acl/ops/acl_fv.h @@ -13,6 +13,7 @@ * See the License for the specific language governing permissions and * limitations under the License. */ + #ifndef INC_EXTERNAL_ACL_OPS_ACL_RETR_H_ #define INC_EXTERNAL_ACL_OPS_ACL_RETR_H_ diff --git a/inc/external/ge/ge_api_types.h b/inc/external/ge/ge_api_types.h index f2d083ae..e89d70c4 100644 --- a/inc/external/ge/ge_api_types.h +++ b/inc/external/ge/ge_api_types.h @@ -394,7 +394,7 @@ const std::set ir_builder_suppported_options = {INPUT_FORMAT, // for interface: aclgrphParse const std::set ir_parser_suppported_options = { INPUT_FP16_NODES, IS_INPUT_ADJUST_HW_LAYOUT, IS_OUTPUT_ADJUST_HW_LAYOUT, OUTPUT, - OUT_NODES, COMPRESS_WEIGHT_CONF, ENABLE_SCOPE_FUSION_PASSES}; + OUT_NODES, ENABLE_SCOPE_FUSION_PASSES}; // for interface: aclgrphBuildInitialize const std::set global_options = {CORE_TYPE, diff --git a/inc/external/ge/ge_ir_build.h b/inc/external/ge/ge_ir_build.h index 182c0444..afaf42ac 100644 --- a/inc/external/ge/ge_ir_build.h +++ b/inc/external/ge/ge_ir_build.h @@ -102,16 +102,6 @@ graphStatus aclgrphGetIRVersion(int *major_version, int *minor_version, int *pat /** * @ingroup AscendCL - * @brief infer shape and data type - * - * @param graph[IN] the graph ready to build - * @retval GRAPH_SUCCESS The function is successfully executed. - * @retval OtherValues Failure - */ -graphStatus aclgrphInferShapeAndType(ge::Graph &graph); - -/** - * @ingroup AscendCL * @brief dump graph * * @param graph[IN] the graph ready to build diff --git a/inc/external/runtime/rt_error_codes.h b/inc/external/runtime/rt_error_codes.h index 34202314..d2373525 100644 --- a/inc/external/runtime/rt_error_codes.h +++ b/inc/external/runtime/rt_error_codes.h @@ -1,11 +1,17 @@ /** - * @file rt_error_codes.h + * Copyright 2019-2020 Huawei Technologies Co., Ltd * - * Copyright (C) Huawei Technologies Co., Ltd. 2019-2020. All Rights Reserved. + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. */ #ifndef __INC_EXTERNEL_RT_ERROR_CODES_H__ diff --git a/inc/framework/common/debug/log.h b/inc/framework/common/debug/log.h index 249271a6..95de2bc2 100644 --- a/inc/framework/common/debug/log.h +++ b/inc/framework/common/debug/log.h @@ -28,7 +28,7 @@ #include "ge/ge_api_error_codes.h" #if !defined(__ANDROID__) && !defined(ANDROID) -#define DOMI_LOGE(...) GE_LOG_ERROR(GE_MODULE_NAME, ge::FAILED, __VA_ARGS__) +#define DOMI_LOGE(fmt, ...) GE_LOG_ERROR(GE_MODULE_NAME, ge::FAILED, fmt, ##__VA_ARGS__) #else #include #if defined(BUILD_VERSION_PERF) diff --git a/metadef/graph/debug/ge_log.h b/metadef/graph/debug/ge_log.h index 03f0e3ac..de1cdb86 100644 --- a/metadef/graph/debug/ge_log.h +++ b/metadef/graph/debug/ge_log.h @@ -20,7 +20,7 @@ #include "graph/ge_error_codes.h" #include "framework/common/debug/ge_log.h" -#define GE_LOGE(...) GE_LOG_ERROR(GE_MODULE_NAME, ge::FAILED, __VA_ARGS__) +#define GE_LOGE(fmt, ...) GE_LOG_ERROR(GE_MODULE_NAME, ge::FAILED, fmt, ##__VA_ARGS__) #define GE_LOGI_IF(condition, ...) \ if ((condition)) { \ diff --git a/metadef/graph/proto/dump_task.proto b/metadef/graph/proto/dump_task.proto index b1e346cd..e7bd8dfb 100644 --- a/metadef/graph/proto/dump_task.proto +++ b/metadef/graph/proto/dump_task.proto @@ -108,4 +108,5 @@ message DumpData{ repeated OpOutput output = 3; repeated OpInput input = 4; repeated OpBuffer buffer = 5; + string op_name = 6; } diff --git a/metadef/graph/shape_refiner.cc b/metadef/graph/shape_refiner.cc index 99eda1a5..d467c02f 100644 --- a/metadef/graph/shape_refiner.cc +++ b/metadef/graph/shape_refiner.cc @@ -766,6 +766,7 @@ graphStatus ShapeRefiner::InferShapeAndType(const NodePtr &node, bool before_sub TypeUtils::FormatToSerialString(output_tensor->GetOriginFormat()).c_str(), TypeUtils::DataTypeToSerialString(output_tensor->GetOriginDataType()).c_str()); } + GE_CHK_STATUS_RET_NOLOG(NodeUtils::UpdatePeerNodeInputDesc(node)); } else { GELOGE(GRAPH_FAILED, "%s call infer function failed.", node->GetName().c_str()); return GRAPH_FAILED; diff --git a/metadef/graph/utils/node_utils.cc b/metadef/graph/utils/node_utils.cc index d3ea1215..13859cbd 100644 --- a/metadef/graph/utils/node_utils.cc +++ b/metadef/graph/utils/node_utils.cc @@ -318,10 +318,17 @@ GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY graphStatus NodeUtils::UpdatePeer TypeUtils::DataTypeToSerialString(output_tensor->GetOriginDataType()).c_str()); for (const auto &peer_anchor : out_anchor->GetPeerInDataAnchors()) { - if (peer_anchor->GetOwnerNode()->GetOpDesc() == nullptr) { + auto peer_anchor_opdesc = peer_anchor->GetOwnerNode()->GetOpDesc(); + if (peer_anchor_opdesc == nullptr) { GELOGE(GRAPH_FAILED, "peer_anchor opdesc is null"); continue; } + if (op_desc->GetId() < peer_anchor_opdesc->GetId() || + peer_anchor_opdesc->GetType() == CONSTANT || + peer_anchor_opdesc->GetType() == CONSTANTOP) { + GELOGD("no need to UpdatePeerNodeInputDesc"); + continue; + } auto peer_input_desc = peer_anchor->GetOwnerNode()->GetOpDesc()->MutableInputDesc(peer_anchor->GetIdx()); if (peer_input_desc == nullptr) { GELOGE(GRAPH_FAILED, "peer_input_desc is nullptr"); @@ -337,22 +344,11 @@ GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY graphStatus NodeUtils::UpdatePeer peer_anchor->GetOwnerNode()->GetName().c_str(), peer_anchor->GetIdx(), TypeUtils::DataTypeToSerialString(peer_input_dtype).c_str()); } else if ((!peer_input_dims.empty()) && (out_dims != peer_input_dims)) { - string out_shape_str, peer_in_shape_str; - out_shape_str += "["; - for (int64_t dim : out_dims) { - out_shape_str += std::to_string(dim) + " "; - } - out_shape_str += "]"; - peer_in_shape_str += "["; - for (int64_t dim : peer_input_dims) { - peer_in_shape_str += std::to_string(dim) + " "; - } - peer_in_shape_str += "]"; - GELOGW("current node [%s] [%d]\'th out_shape is [%s].peer input node [%s] [%d]\'th " "input_shape is [%s].The two shape should be same! Please check graph and fix it", - node_ptr->GetName().c_str(), out_anchor->GetIdx(), out_shape_str.c_str(), - peer_anchor->GetOwnerNode()->GetName().c_str(), peer_anchor->GetIdx(), peer_in_shape_str.c_str()); + node_ptr->GetName().c_str(), out_anchor->GetIdx(), output_tensor->GetShape().ToString().c_str(), + peer_anchor->GetOwnerNode()->GetName().c_str(), peer_anchor->GetIdx(), + peer_input_desc->GetShape().ToString().c_str()); } GELOGI("Peer input opdesc name is %s, need to flush: shape size is %zu, datatype is %d, original datatype is %d", peer_anchor->GetOwnerNode()->GetOpDesc()->GetName().c_str(), diff --git a/metadef/inc/common/proto/dump_task.proto b/metadef/inc/common/proto/dump_task.proto index b1e346cd..e7bd8dfb 100644 --- a/metadef/inc/common/proto/dump_task.proto +++ b/metadef/inc/common/proto/dump_task.proto @@ -108,4 +108,5 @@ message DumpData{ repeated OpOutput output = 3; repeated OpInput input = 4; repeated OpBuffer buffer = 5; + string op_name = 6; } diff --git a/metadef/inc/register/proto/dump_task.proto b/metadef/inc/register/proto/dump_task.proto index b1e346cd..a75ba866 100644 --- a/metadef/inc/register/proto/dump_task.proto +++ b/metadef/inc/register/proto/dump_task.proto @@ -108,4 +108,5 @@ message DumpData{ repeated OpOutput output = 3; repeated OpInput input = 4; repeated OpBuffer buffer = 5; + string op_name; } diff --git a/metadef/proto/dump_task.proto b/metadef/proto/dump_task.proto index b1e346cd..e7bd8dfb 100644 --- a/metadef/proto/dump_task.proto +++ b/metadef/proto/dump_task.proto @@ -108,4 +108,5 @@ message DumpData{ repeated OpOutput output = 3; repeated OpInput input = 4; repeated OpBuffer buffer = 5; + string op_name = 6; } diff --git a/third_party/fwkacllib/inc/cce/aicpu_engine.h b/third_party/fwkacllib/inc/cce/aicpu_engine.h index b83731a8..8bf0bdb6 100644 --- a/third_party/fwkacllib/inc/cce/aicpu_engine.h +++ b/third_party/fwkacllib/inc/cce/aicpu_engine.h @@ -13,6 +13,7 @@ * See the License for the specific language governing permissions and * limitations under the License. */ + #ifndef AICPU_ENGINE_H__ #define AICPU_ENGINE_H__ diff --git a/third_party/fwkacllib/inc/ops/aipp.h b/third_party/fwkacllib/inc/ops/aipp.h index 86805f72..6db4d783 100644 --- a/third_party/fwkacllib/inc/ops/aipp.h +++ b/third_party/fwkacllib/inc/ops/aipp.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/all_ops.h b/third_party/fwkacllib/inc/ops/all_ops.h index 614b06e2..1ac83783 100644 --- a/third_party/fwkacllib/inc/ops/all_ops.h +++ b/third_party/fwkacllib/inc/ops/all_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/array_ops.h b/third_party/fwkacllib/inc/ops/array_ops.h index 19147d64..d66d6f99 100644 --- a/third_party/fwkacllib/inc/ops/array_ops.h +++ b/third_party/fwkacllib/inc/ops/array_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/audio_ops.h b/third_party/fwkacllib/inc/ops/audio_ops.h index f05135d1..d9883253 100644 --- a/third_party/fwkacllib/inc/ops/audio_ops.h +++ b/third_party/fwkacllib/inc/ops/audio_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/batch_ops.h b/third_party/fwkacllib/inc/ops/batch_ops.h index a4786cd3..8a1c5a7b 100644 --- a/third_party/fwkacllib/inc/ops/batch_ops.h +++ b/third_party/fwkacllib/inc/ops/batch_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/bitwise_ops.h b/third_party/fwkacllib/inc/ops/bitwise_ops.h index 39a28cf3..5c83e161 100644 --- a/third_party/fwkacllib/inc/ops/bitwise_ops.h +++ b/third_party/fwkacllib/inc/ops/bitwise_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/boosted_trees_ops.h b/third_party/fwkacllib/inc/ops/boosted_trees_ops.h index 08e54824..550e8b7d 100644 --- a/third_party/fwkacllib/inc/ops/boosted_trees_ops.h +++ b/third_party/fwkacllib/inc/ops/boosted_trees_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/candidate_sampling_ops.h b/third_party/fwkacllib/inc/ops/candidate_sampling_ops.h index 890c52ae..e20607bf 100644 --- a/third_party/fwkacllib/inc/ops/candidate_sampling_ops.h +++ b/third_party/fwkacllib/inc/ops/candidate_sampling_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/condtake_ops.h b/third_party/fwkacllib/inc/ops/condtake_ops.h index 029cffbf..5e91eb07 100644 --- a/third_party/fwkacllib/inc/ops/condtake_ops.h +++ b/third_party/fwkacllib/inc/ops/condtake_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/control_flow_ops.h b/third_party/fwkacllib/inc/ops/control_flow_ops.h index c0b6ad72..7196b14f 100644 --- a/third_party/fwkacllib/inc/ops/control_flow_ops.h +++ b/third_party/fwkacllib/inc/ops/control_flow_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/ctc_ops.h b/third_party/fwkacllib/inc/ops/ctc_ops.h index c6a265cc..2c75fd09 100644 --- a/third_party/fwkacllib/inc/ops/ctc_ops.h +++ b/third_party/fwkacllib/inc/ops/ctc_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/data_flow_ops.h b/third_party/fwkacllib/inc/ops/data_flow_ops.h index 18a79289..bb937a75 100644 --- a/third_party/fwkacllib/inc/ops/data_flow_ops.h +++ b/third_party/fwkacllib/inc/ops/data_flow_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/elewise_calculation_ops.h b/third_party/fwkacllib/inc/ops/elewise_calculation_ops.h index 81d2743d..51b7eeb4 100644 --- a/third_party/fwkacllib/inc/ops/elewise_calculation_ops.h +++ b/third_party/fwkacllib/inc/ops/elewise_calculation_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/functional_ops.h b/third_party/fwkacllib/inc/ops/functional_ops.h index b09ac058..598d3ad3 100644 --- a/third_party/fwkacllib/inc/ops/functional_ops.h +++ b/third_party/fwkacllib/inc/ops/functional_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/get_data_ops.h b/third_party/fwkacllib/inc/ops/get_data_ops.h index e5518ef8..33dc4f14 100644 --- a/third_party/fwkacllib/inc/ops/get_data_ops.h +++ b/third_party/fwkacllib/inc/ops/get_data_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/hcom_ops.h b/third_party/fwkacllib/inc/ops/hcom_ops.h index cb9fbe22..13ed4f26 100644 --- a/third_party/fwkacllib/inc/ops/hcom_ops.h +++ b/third_party/fwkacllib/inc/ops/hcom_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/hvd_ops.h b/third_party/fwkacllib/inc/ops/hvd_ops.h index 00299ef7..a49ec5ed 100644 --- a/third_party/fwkacllib/inc/ops/hvd_ops.h +++ b/third_party/fwkacllib/inc/ops/hvd_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/image_ops.h b/third_party/fwkacllib/inc/ops/image_ops.h index 726cd0e5..77306c97 100644 --- a/third_party/fwkacllib/inc/ops/image_ops.h +++ b/third_party/fwkacllib/inc/ops/image_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/internal_ops.h b/third_party/fwkacllib/inc/ops/internal_ops.h index bcc3f1c3..9dde14a5 100644 --- a/third_party/fwkacllib/inc/ops/internal_ops.h +++ b/third_party/fwkacllib/inc/ops/internal_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/linalg_ops.h b/third_party/fwkacllib/inc/ops/linalg_ops.h index d8f45c5d..7a6fbc59 100644 --- a/third_party/fwkacllib/inc/ops/linalg_ops.h +++ b/third_party/fwkacllib/inc/ops/linalg_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/logging_ops.h b/third_party/fwkacllib/inc/ops/logging_ops.h index 03be7757..bc8ae2b8 100644 --- a/third_party/fwkacllib/inc/ops/logging_ops.h +++ b/third_party/fwkacllib/inc/ops/logging_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/lookup_ops.h b/third_party/fwkacllib/inc/ops/lookup_ops.h index 5d928e5a..b37ab048 100644 --- a/third_party/fwkacllib/inc/ops/lookup_ops.h +++ b/third_party/fwkacllib/inc/ops/lookup_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/math_ops.h b/third_party/fwkacllib/inc/ops/math_ops.h index e8dbd812..fb000aa8 100644 --- a/third_party/fwkacllib/inc/ops/math_ops.h +++ b/third_party/fwkacllib/inc/ops/math_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/matrix_calculation_ops.h b/third_party/fwkacllib/inc/ops/matrix_calculation_ops.h index 33b596d8..1dc9fec9 100644 --- a/third_party/fwkacllib/inc/ops/matrix_calculation_ops.h +++ b/third_party/fwkacllib/inc/ops/matrix_calculation_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/nn_batch_norm_ops.h b/third_party/fwkacllib/inc/ops/nn_batch_norm_ops.h index a35cee03..0c6a5dff 100644 --- a/third_party/fwkacllib/inc/ops/nn_batch_norm_ops.h +++ b/third_party/fwkacllib/inc/ops/nn_batch_norm_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/nn_calculation_ops.h b/third_party/fwkacllib/inc/ops/nn_calculation_ops.h index 5ec9d252..99af5c5d 100644 --- a/third_party/fwkacllib/inc/ops/nn_calculation_ops.h +++ b/third_party/fwkacllib/inc/ops/nn_calculation_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -365,6 +365,25 @@ REG_OP(BiasAddGrad) * 4-D with shape [batch, out_height, out_width, out_channels] * or [batch, out_channels, out_height, out_width]. * Gradients with respect to the output of the convolution. + *\n + *\n + * The following are the supported data types and data formats: +*@verbatim + | Tensor | out_bckprop | filter | y + ------------|-------------|---------|-------- + | Data Type | float16 | float16 | float16 + | |-------------|---------|-------- + | | float32 | float32 | float32 + | |-------------|---------|-------- + | | float64 | float64 | float64 + ------------|-------------|---------|-------- + | Format | NCHW | NCHW | NCHW + | | NHWC | HWCN | NHWC +@endverbatim + * For float32 and float64 type, the actual calculation on the chip is based on + * float16. + *\n + * *@par Attributes: * Five attributes: * @li strides: A tuple/list of 4 integers. The stride of the sliding window @@ -377,8 +396,52 @@ REG_OP(BiasAddGrad) * channels. * @li data_format: An optional string from: "NHWC", "NCHW". Defaults to * "NHWC". Specify the data format of the input and output data. + *\n + *\n + * The following value range restrictions must be met: +*@verbatim + | Name | Field | Scope + -------------------|----------|-------------- + | input_size | H | [1, 4096] + | | W | [1, 4096] + -------------------|----------|-------------- + | Filter | H | [1, 255] + | | W | [1, 255] + -------------------|----------|-------------- + | out_backprop | H | [1, 4096] + | | W | [1, 4096] + -------------------|----------|-------------- + | y(fmap) | H | [1, 4096] + | | W | [1, 4096] + -------------------|----------|-------------- + | Stride | H | [1, 63] + | | W | [1, 63] + -------------------|----------|-------------- + | Padding | Top | [0, 255] + | | Bottom | [0, 255] + | | Left | [0, 255] + | | Right | [0, 255] + -------------------|----------|-------------- + | Dilation | H | [1, 255] + | | W | [1, 255] + +@endverbatim + * In Ascend910, fmap or out_backprop's H and W not support 1 when + * fmap_h + pad_top + pad_bottom != (filter_height - 1) * dilation_h + 1 + *\n + * *@par Outputs: * y: A Tensor. Has the same type as filter,and has same format as input_size. + *\n + * out_backprop_height = (fmap_height + pad_top + pad_bottom - + * (dilation_h * (filter_height - 1) + 1)) + * / stride_h + 1 + *\n + * out_backprop_width = (fmap_width + pad_left + pad_right - + * (dilation_w * (filter_width - 1) + 1)) + * / stride_w + 1 + *\n + * *@par Third-party framework compatibility * Compatible with Tensorflow's conv2d_backprop_input */ @@ -454,6 +517,21 @@ REG_OP(Conv2DBackpropInputD) * @li bias: An optional tensor. Must have the same type as "y". * @li offset_w: An optional 1D tensor for quantized deconvolution. * Type is int8. Reserved.\n + *\n + *\n + * The following are the supported data types and data formats: +*@verbatim + | Tensor | x | filter | bias | y + ------------|---------|---------|---------|-------- + | Data Type | float16 | float16 | float16 | float16 + | |---------|---------|---------|-------- + | | int8 | int8 | int32 | int32 + ------------|---------|---------|---------|-------- + | Format | NCHW | NCHW | ND | NCHW +@endverbatim + * For int8, a dequant or requant operator must be followed. + *\n + * *@par Attributes: * Six attributes: * @li strides: A tuple or list of 2 integers. The stride of the sliding window @@ -468,8 +546,51 @@ REG_OP(Conv2DBackpropInputD) Specify the data format of the input and output data. * @li offset_x: An optional integer for quantized deconvolution. * Defaults to "0". + *\n + *\n + * The following value range restrictions must be met: +*@verbatim + | Name | Field | Scope + -------------------|----------|-------------- + | x (out_backprop) | H | [1, 4096] + | | W | [1, 4096] + -------------------|----------|-------------- + | Filter | H | [1, 255] + | | W | [1, 255] + -------------------|----------|-------------- + | y (fmap) | H | [1, 4096] + | | W | [1, 4096] + -------------------|----------|-------------- + | Stride | H | [1, 63] + | | W | [1, 63] + -------------------|----------|-------------- + | Padding | Top | [0, 255] + | | Bottom | [0, 255] + | | Left | [0, 255] + | | Right | [0, 255] + -------------------|----------|-------------- + | Dilation | H | [1, 255] + | | W | [1, 255] + -------------------|----------|-------------- + | Offset_x | | [-128, 127] + +@endverbatim + * In Ascend910, fmap or out_backprop's H and W not support 1 when + * fmap_h + pad_top + pad_bottom != (filter_height - 1) * dilation_h + 1 + *\n + * *@par Outputs: * y: A Tensor. 4D tensor with shape [batch, channels, height, width]. + *\n + * out_backprop_height = (fmap_height + pad_top + pad_bottom - + * (dilation_h * (filter_height - 1) + 1)) + * / stride_h + 1 + *\n + * out_backprop_width = (fmap_width + pad_left + pad_right - + * (dilation_w * (filter_width - 1) + 1)) + * / stride_w + 1 + *\n + * * When type of x is float16, the type of y must be float16. * When type of x is int8, the type of y must be int32. */ @@ -502,6 +623,25 @@ REG_OP(Deconvolution) * [batch, out_height, out_width, out_channels] or [batch, out_channels, * out_height, out_width]. Gradients with respect to the output of the * convolution. + *\n + *\n + * The following are the supported data types and data formats: +*@verbatim + | Tensor | x | out_backprop | y + ------------|---------|--------------|--------- + | Data Type | float16 | float16 | float16 + | |---------|--------------|--------- + | | float32 | float32 | float32 + | |---------|--------------|--------- + | | float64 | float64 | float64 + |-----------|---------|--------------|--------- + | Format | NCHW | NCHW | NCHW + | | NHWC | NHWC | HWCN +@endverbatim + * For float32 and float64 type of x and outbackprop, the actual calculation on the chip + * is based on float16. + *\n + * *@par Attributes: * Five attributes: * @li strides: A tuple/list of 4 integers. The stride of the sliding window @@ -514,8 +654,52 @@ REG_OP(Deconvolution) * channels. * @li data_format: An optional string from: "NHWC", "NCHW". Defaults to * "NHWC". Specify the data format of the input and output data. + *\n +*\n +* The following value range restrictions must be met: +*@verbatim + | Name | Field | Scope + -------------------|----------|-------------- + | x(fmap) | H | [1, 4096] + | | W | [1, 4096] + -------------------|----------|-------------- + | Filter Size | H | [1, 255] + | | W | [1, 255] + -------------------|----------|-------------- + | out_backprop | H | [1, 4096] + | | W | [1, 4096] + -------------------|----------|-------------- + | y | H | [1, 4096] + | | W | [1, 4096] + -------------------|----------|-------------- + | Stride | H | [1, 63] + | | W | [1, 63] + -------------------|----------|-------------- + | Padding | Top | [0, 255] + | | Bottom | [0, 255] + | | Left | [0, 255] + | | Right | [0, 255] + -------------------|----------|-------------- + | Dilation | H | [1, 255] + | | W | [1, 255] + +@endverbatim + * In Ascend910, out_backprop's H and W not support 1 when + * fmap_h + pad_top + pad_bottom != (filter_height - 1) * dilation_h + 1 + *\n + * *@par Outputs: * y: A Tensor. Has the same type as x, has the same format as filter_size. + *\n + * out_backprop_height = (in_height + pad_top + pad_bottom - + * (dilation_h * (filter_height - 1) + 1)) + * / stride_h + 1 + *\n + * out_backprop_width = (in_width + pad_left + pad_right - + * (dilation_w * (filter_width - 1) + 1)) + * / stride_w + 1 + *\n + * *@par Third-party framework compatibility * Compatible with Tensorflow's conv2d_backprop_filter */ @@ -1031,9 +1215,7 @@ REG_OP(Conv3DBackpropInputD) * @li c_t: A optinal Tensor dtype of float16, float32. The cell state at time t . \n *@par Third-party framework compatibility: -* Compatible with the Pytorch operator adds. -*@par Restrictions: -*Warning: THIS FUNCTION IS EXPERIMENTAL. Please do not use. +* Compatible with the Caffe operator LSTM. */ REG_OP(LSTM) .INPUT(x, TensorType({DT_FLOAT16})) @@ -1275,6 +1457,22 @@ REG_OP(Conv3DTransposeD) * or [out_channels, in_channel, filter_height, filter_width]. * @li bias: An optional 1D tensor of type float16 or int32. Format is "ND". * @li offset_w: An optional 1D tensor for quantized inference. Reserved. + *\n + *\n + * The following are the supported data types and data formats: +*@verbatim + | Tensor | x | filter | bias | y + ------------|---------|---------|---------|-------- + | Data Type | float16 | float16 | float16 | float16 + | |---------|---------|---------|-------- + | | int8 | int8 | int32 | int32 + ------------|---------|---------|---------|-------- + | Format | NCHW | NCHW | ND | NCHW + | | NHWC | HWCN | | NHWC +@endverbatim + * For int8, a dequant or requant operator must be followed. + *\n + * *@par Required Attributes: * @li strides: A required tuple/list of 4 integers. The stride of the sliding * window for H/W dimension. The index of H/W is same as data_format. @@ -1293,9 +1491,55 @@ REG_OP(Conv3DTransposeD) * to [0, 0, 0, 0]. * @li offset_x: An optional int. Input offset, used for quantized inference. * Defaults to "0". + *\n + *\n + * The following value range restrictions must be met: +*@verbatim + | Name | Field | Scope + -------------------|----------|-------------- + | input_size | H | [1, 4096] + | | W | [1, 4096] + -------------------|----------|-------------- + | x (out_backprop) | H | [1, 4096] + | | W | [1, 4096] + -------------------|----------|-------------- + | filter | H | [1, 255] + | | W | [1, 255] + -------------------|----------|-------------- + | y (fmap) | H | [1, 4096] + | | W | [1, 4096] + -------------------|----------|-------------- + | Stride | H | [1, 63] + | | W | [1, 63] + -------------------|----------|-------------- + | Padding | Top | [0, 255] + | | Bottom | [0, 255] + | | Left | [0, 255] + | | Right | [0, 255] + -------------------|----------|-------------- + | Dilation | H | [1, 255] + | | W | [1, 255] + -------------------|----------|-------------- + | Offset_x | | [-128, 127] + +@endverbatim + * In Ascend910, fmap or out_backprop's H and W not support 1 when + * fmap_h + pad_top + pad_bottom != (filter_height - 1) * dilation_h + 1 + *\n + * *@par Outputs: * y: A Tensor. A Tensor of type float16 or int32, and has same format as * input_size. + *\n + * out_backprop_height = (fmap_height + pad_top + pad_bottom - + * (dilation_h * (filter_height - 1) + 1)) + * / stride_h + 1 + *\n + * out_backprop_width = (fmap_width + pad_left + pad_right - + * (dilation_w * (filter_width - 1) + 1)) + * / stride_w + 1 + *\n + * */ REG_OP(Conv2DTranspose) .INPUT(input_size, TensorType({DT_INT32, DT_INT64})) diff --git a/third_party/fwkacllib/inc/ops/nn_detect_ops.h b/third_party/fwkacllib/inc/ops/nn_detect_ops.h index 20fdb90d..7c7586a1 100644 --- a/third_party/fwkacllib/inc/ops/nn_detect_ops.h +++ b/third_party/fwkacllib/inc/ops/nn_detect_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -1487,6 +1487,9 @@ REG_OP(DecodeBboxV2) *@par Outputs: * @li y1: A Tensor. Must have the same type as x. * @li y2: A Tensor. Indices of y1 in x.Dtype must be int32. +* +*@attention Constraints: +* The upper limit of data on the direction axis is 7040. */ REG_OP(Sort) .INPUT(x, TensorType({ DT_FLOAT16 })) diff --git a/third_party/fwkacllib/inc/ops/nn_norm_ops.h b/third_party/fwkacllib/inc/ops/nn_norm_ops.h index 482bca40..2d519485 100644 --- a/third_party/fwkacllib/inc/ops/nn_norm_ops.h +++ b/third_party/fwkacllib/inc/ops/nn_norm_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/nn_ops.h b/third_party/fwkacllib/inc/ops/nn_ops.h index 16552eee..9edc469a 100644 --- a/third_party/fwkacllib/inc/ops/nn_ops.h +++ b/third_party/fwkacllib/inc/ops/nn_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/nn_pooling_ops.h b/third_party/fwkacllib/inc/ops/nn_pooling_ops.h index f16a59df..ba9383ed 100644 --- a/third_party/fwkacllib/inc/ops/nn_pooling_ops.h +++ b/third_party/fwkacllib/inc/ops/nn_pooling_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -223,6 +223,83 @@ REG_OP(AvgPool3DD) .ATTR(data_format, String, "NDHWC") .OP_END_FACTORY_REG(AvgPool3DD) +/** +* @brief Computes AvgPool3DGrad function. + +* @par Inputs: +* @li orig_input_shape: An NDHWC tensor of type float16, float32, or double. +* @li grads: An NDHWC tensor of type int32. + +* @par Attributes: +* @li ksize: List of ints that has length 1, 3 or 5. The size of the window for each dimension of the input tensor. +* @li strides:List of ints that has length 1, 3 or 5. The stride of the sliding window for each dimension of the input tensor. +* @li pads: List of ints, implicit zero paddings on both sides of the input. +* @li ceil_mode: When true, will use ceil instead of floor in the formula to compute the output shape. +* @li count_include_pad: When true, will include the zero-padding in the averaging calculation. +* @li divisor_override: if specified, it will be used as divisor, otherwise size of the pooling region will be used. +* @li data_format: A string, format of input data. + +* @par Outputs: +* @output: A mutable tensor with the same shape and type as "orig_input". + +* @par Third-party framework compatibility +* @li Compatible with the TensorFlow operator AvgPoolGrad. +*/ + +REG_OP(AvgPool3DGrad) + .INPUT(orig_input_shape, TensorType({DT_FLOAT16, DT_FLOAT32, DT_DOUBLE})) + .INPUT(grads, TensorType({DT_INT32})) + .OUTPUT(output, TensorType({DT_FLOAT16, DT_FLOAT32, DT_DOUBLE})) + .REQUIRED_ATTR(ksize, ListInt) + .REQUIRED_ATTR(strides, ListInt) + .REQUIRED_ATTR(pads, ListInt) + .ATTR(ceil_mode, Bool, false) + .ATTR(count_include_pad, Bool, true) + .ATTR(divisor_override, Int, 0) + .ATTR(data_format, String, "NDHWC") + .OP_END_FACTORY_REG(AvgPool3DGrad) + +/** +* @brief Performs average pooling on the input. + +* @par Inputs: +* @li grads: An NDHWC tensor of type float16. +* @li filter: An optional tensor of type float16, fractal_z_3d layout. +* @li multiplier: An optional tensor of float16. + +* @par Attributes: +* @li orig_input_shape: List of ints that has length 5. The size of the window for each dimension of the input tensor. +* @li ksize: List of ints that has length 3. The size of the window for each dimension of the input tensor. +* @li strides:List of ints that has length 3. The stride of the sliding window for each dimension of the input tensor. +* @li pads: List of ints, implicit zero paddings on both sides of the input. +* @li ceil_mode: When true, will use ceil instead of floor in the formula to compute the output shape. +* @li count_include_pad: When true, will include the zero-padding in the averaging calculation. +* @li divisor_override: if specified, it will be used as divisor, otherwise size of the pooling region will be used. +* @li data_format: A string, format of input data . \n + +* @par Outputs: +* @output: The average pooled output tensor . \n + +* @attention Constraints: +* @li "ksize" is in the range [1, 255]. "strides" is in the range [1, 63] + +* @par Third-party framework compatibility +* Compatible with the TensorFlow operator AvgPool3DGradD. +*/ +REG_OP(AvgPool3DGradD) + .INPUT(grads, TensorType({DT_FLOAT16})) + .OPTIONAL_INPUT(filter, TensorType({DT_FLOAT16})) + .OPTIONAL_INPUT(multiplier, TensorType({DT_FLOAT16})) + .OUTPUT(output, TensorType({DT_FLOAT16, DT_FLOAT32, DT_DOUBLE})) + .REQUIRED_ATTR(orig_input_shape, ListInt) + .REQUIRED_ATTR(ksize, ListInt) + .REQUIRED_ATTR(strides, ListInt) + .REQUIRED_ATTR(pads, ListInt) + .ATTR(ceil_mode, Bool, false) + .ATTR(count_include_pad, Bool, true) + .ATTR(divisor_override, Int, 0) + .ATTR(data_format, String, "NDHWC") + .OP_END_FACTORY_REG(AvgPool3DGradD) /** *@brief Performs max_pool_ext2 on the input . \n @@ -350,6 +427,31 @@ REG_OP(MaxPool3D) .ATTR(data_format, String, "NDHWC") .OP_END_FACTORY_REG(MaxPool3D) +/** +*@brief Applies a 2D adaptive max pooling over an input signal conposed of several input planes. \n +* The output is of size H x W, for any input size. + +* @par Inputs: +* One input, including: +* @li x: A Tensor. Must be one of the following data types: +* float16, float32, float64. \n + +* @par Attributes: +* @li output_size: A required list of 2 ints +* specifying the size (H,W) of the output tensor. \n + +* @par Outputs: +* @li y: A Tensor. Has the same data type as "x" \n + +* @par Third-party framework compatibility +* Compatible with the Pytorch operator AdaptiveMaxPool2d. +*/ +REG_OP(AdaptiveMaxPool2d) + .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT32, DT_DOUBLE})) + .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT32, DT_DOUBLE})) + .OUTPUT(argmax, TensorType::IndexNumberType()) + .REQUIRED_ATTR(output_size, ListInt) + .OP_END_FACTORY_REG(AdaptiveMaxPool2d) /** * @brief Computes second-order gradients of the maxpooling3d function . \n diff --git a/third_party/fwkacllib/inc/ops/nn_training_ops.h b/third_party/fwkacllib/inc/ops/nn_training_ops.h index 92074872..047fd6da 100644 --- a/third_party/fwkacllib/inc/ops/nn_training_ops.h +++ b/third_party/fwkacllib/inc/ops/nn_training_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/no_op.h b/third_party/fwkacllib/inc/ops/no_op.h index b27b1fa0..7834591c 100644 --- a/third_party/fwkacllib/inc/ops/no_op.h +++ b/third_party/fwkacllib/inc/ops/no_op.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/nonlinear_fuc_ops.h b/third_party/fwkacllib/inc/ops/nonlinear_fuc_ops.h index e0897280..3ba38668 100644 --- a/third_party/fwkacllib/inc/ops/nonlinear_fuc_ops.h +++ b/third_party/fwkacllib/inc/ops/nonlinear_fuc_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/npu_loss_scale_ops.h b/third_party/fwkacllib/inc/ops/npu_loss_scale_ops.h index f36d2935..8d7ef9f9 100644 --- a/third_party/fwkacllib/inc/ops/npu_loss_scale_ops.h +++ b/third_party/fwkacllib/inc/ops/npu_loss_scale_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/outfeed_ops.h b/third_party/fwkacllib/inc/ops/outfeed_ops.h index 53b9d701..e0b783bc 100644 --- a/third_party/fwkacllib/inc/ops/outfeed_ops.h +++ b/third_party/fwkacllib/inc/ops/outfeed_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/pad_ops.h b/third_party/fwkacllib/inc/ops/pad_ops.h index 8d71c5cd..91969e88 100644 --- a/third_party/fwkacllib/inc/ops/pad_ops.h +++ b/third_party/fwkacllib/inc/ops/pad_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/parsing_ops.h b/third_party/fwkacllib/inc/ops/parsing_ops.h index 9a5cf504..5c7adfd8 100644 --- a/third_party/fwkacllib/inc/ops/parsing_ops.h +++ b/third_party/fwkacllib/inc/ops/parsing_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/quantize_ops.h b/third_party/fwkacllib/inc/ops/quantize_ops.h index 806e28df..b53cfeb6 100644 --- a/third_party/fwkacllib/inc/ops/quantize_ops.h +++ b/third_party/fwkacllib/inc/ops/quantize_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/ragged_array_ops.h b/third_party/fwkacllib/inc/ops/ragged_array_ops.h index 20484623..9b31aa8e 100644 --- a/third_party/fwkacllib/inc/ops/ragged_array_ops.h +++ b/third_party/fwkacllib/inc/ops/ragged_array_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/ragged_conversion_ops.h b/third_party/fwkacllib/inc/ops/ragged_conversion_ops.h index 020e3da4..13488a25 100644 --- a/third_party/fwkacllib/inc/ops/ragged_conversion_ops.h +++ b/third_party/fwkacllib/inc/ops/ragged_conversion_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/ragged_math_ops.h b/third_party/fwkacllib/inc/ops/ragged_math_ops.h index 258b0ca1..8af4f867 100644 --- a/third_party/fwkacllib/inc/ops/ragged_math_ops.h +++ b/third_party/fwkacllib/inc/ops/ragged_math_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/random_ops.h b/third_party/fwkacllib/inc/ops/random_ops.h index e2b00ce3..ddf2fbf4 100644 --- a/third_party/fwkacllib/inc/ops/random_ops.h +++ b/third_party/fwkacllib/inc/ops/random_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/reduce_ops.h b/third_party/fwkacllib/inc/ops/reduce_ops.h index 0b114134..cf30ab6a 100644 --- a/third_party/fwkacllib/inc/ops/reduce_ops.h +++ b/third_party/fwkacllib/inc/ops/reduce_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/resource_variable_ops.h b/third_party/fwkacllib/inc/ops/resource_variable_ops.h index 74ac83f8..1b60d42a 100644 --- a/third_party/fwkacllib/inc/ops/resource_variable_ops.h +++ b/third_party/fwkacllib/inc/ops/resource_variable_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/rnn.h b/third_party/fwkacllib/inc/ops/rnn.h index cfd20479..f730c83d 100644 --- a/third_party/fwkacllib/inc/ops/rnn.h +++ b/third_party/fwkacllib/inc/ops/rnn.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -187,16 +187,16 @@ REG_OP(DynamicRNNGrad) *@brief: DynamicRNN calculation. *@par Inputs: *ten inputs: -*@li x:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. -*@li w:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. -*@li b:A 1D Tensor. Must be one of the following types: float16, float32. The format must be ND. -*@li seq_length:A 1D Tensor. Must be one of the following types: int32. The format must be ND. -*@li init_h:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. -*@li init_c:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. -*@li wci:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. -*@li wcf:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. -*@li wco:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. -*@li mask:A 1D Tensor. Must be one of the following types: uint8. The format must be ND . \n +*@li x:A required 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@li w:A required 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. +*@li b:A required 1D Tensor. Must be one of the following types: float16, float32. The format must be ND. +*@li seq_length:A optional 1D Tensor. Must be one of the following types: int32. The format must be ND. +*@li init_h:A optional 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@li init_c:A optional 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@li wci:A optional 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. +*@li wcf:A optional 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. +*@li wco:A optional 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. +*@li mask:A optional 1D Tensor. Must be one of the following types: uint8. The format must be ND . \n *@par Attributes: *@li cell_type:An string identifying the cell type in the op. Default to "LSTM". Only LSTM is currently supported. @@ -221,6 +221,8 @@ REG_OP(DynamicRNNGrad) *@li f:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. *@li o:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. *@li tanhct:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@par Third-party framework compatibility: +* Compatible with the TF operator LSTM. */ REG_OP(DynamicRNN) .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT})) @@ -258,17 +260,17 @@ REG_OP(DynamicRNN) *@brief: DynamicLSTMV2 calculation. *@par Inputs: *ten inputs: -*@li x:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. -*@li w:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. -*@li b:A 1D Tensor. Must be one of the following types: float16, float32. The format must be ND. -*@li cont:A 1D Tensor. Must be one of the following types: float16, float32. The format must be ND. -*@li w_xc_x_static:A 1D Tensor. Must be one of the following types: float16, float32. The format must be ND. -*@li h0:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. -*@li c0:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. -*@li wci:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. -*@li wcf:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. -*@li wco:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. -*@li mask:A 1D Tensor. Must be one of the following types: uint8. The format must be ND . \n +*@li x:A required 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@li w:A required 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. +*@li b:A required 1D Tensor. Must be one of the following types: float16, float32. The format must be ND. +*@li cont:A required 2D Tensor. Must be one of the following types: float16, float32. The format must be ND. +*@li w_xc_x_static:A optional 2D Tensor. Must be one of the following types: float16, float32. The format must be ND. +*@li h0:A optional 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@li c0:A optional 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@li wci:A optional 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. +*@li wcf:A optional 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. +*@li wco:A optional 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. +*@li mask:A optional 1D Tensor. Must be one of the following types: uint8. The format must be ND . *@par Attributes: *@li num_output:An integer identifying the num projection in the op. Default to 0. @@ -283,6 +285,10 @@ REG_OP(DynamicRNN) *@li output_c:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. *@li last_output_h:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. *@li last_output_c:A 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@par Third-party framework compatibility: +* Compatible with the Caffe operator LSTM. +*@par Restrictions: +* Warning: THIS FUNCTION IS EXPERIMENTAL. Please do not use. */ REG_OP(DynamicLSTMV2) .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT})) @@ -854,6 +860,56 @@ REG_OP(EmbeddingDenseGrad) .ATTR(padding_idx, Int, -1) .ATTR(scale_grad_by_freq, Bool, false) .OP_END_FACTORY_REG(EmbeddingDenseGrad) + +/** +*@brief CommonLSTM calculation. +*@par Inputs: +*eight inputs: \n +*@li x:Each time step is a 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@li w:Each direction is a 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. +*@li r:Each direction is a 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_ZN_LSTM. +*@li b:An optional input. Each direction is a 1D Tensor. Must be one of the following types: float16, float32. The format must be ND. +*@li sequence_lens:An optional input. A 1D Tensor.Must be one of the following types: int32. The format must be ND. +*@li initial_h:An optional input. Each direction is a 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@li initial_c:An optional input. Each direction is a 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@li p:An optional input. Each direction is a 1D Tensor.Must be one of the following types: float16, float32. The format must be ND. + +*@par Attributes: +*@li activation_alpha:Optional scaling values used by some activation functions. Empty is currently supported. +*@li activation_beta:Optional scaling values used by some activation functions. Empty is currently supported. +*@li activations:The list of activation functions. Empty is currently supported. +*@li clip:An float identifying the cell clip in the op. Default to -1. +*@li direction:Specify if the RNN is forward, reverse, or bidirectional. Must be one of forward(default), reverse, or bidirectional. +*@li hidden_size:Number of neurons in the hidden layer. Reserved. +*@li input_forget:Couple the input and forget gates if 1. Reserved. + +*@par Outputs: +*three outputs: \n +*@li y:First dimension is time step, second dimension is direction, others is a 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@li y_h:Each direction is a 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*@li y_c:Each direction is a 4D Tensor. Must be one of the following types: float16, float32. The format must be FRACTAL_NZ. +*/ + +REG_OP(CommonLSTM) + .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT})) + .INPUT(w, TensorType({DT_FLOAT16, DT_FLOAT})) + .INPUT(r, TensorType({DT_FLOAT16, DT_FLOAT})) + .OPTIONAL_INPUT(b, TensorType({DT_FLOAT16, DT_FLOAT})) + .OPTIONAL_INPUT(sequence_lens, TensorType({DT_INT32})) + .OPTIONAL_INPUT(initial_h, TensorType({DT_FLOAT16, DT_FLOAT})) + .OPTIONAL_INPUT(initial_c, TensorType({DT_FLOAT16, DT_FLOAT})) + .OPTIONAL_INPUT(p, TensorType({DT_FLOAT16, DT_FLOAT})) + .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT})) + .OUTPUT(y_h, TensorType({DT_FLOAT16, DT_FLOAT})) + .OUTPUT(y_c, TensorType({DT_FLOAT16, DT_FLOAT})) + .ATTR(activation_alpha, ListFloat, {}) + .ATTR(activation_beta, ListFloat, {}) + .ATTR(activations, ListString, {}) + .ATTR(clip, Float, -1.0) + .ATTR(direction, String, "forward") + .REQUIRED_ATTR(hidden_size, Int) + .ATTR(input_forget, Int, 0) + .OP_END_FACTORY_REG(CommonLSTM) } // namespace ge #endif // OPS_BUILT_IN_OP_PROTO_INC_RNN_H_ diff --git a/third_party/fwkacllib/inc/ops/rpn_ops.h b/third_party/fwkacllib/inc/ops/rpn_ops.h index 089af326..b7649a44 100644 --- a/third_party/fwkacllib/inc/ops/rpn_ops.h +++ b/third_party/fwkacllib/inc/ops/rpn_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/save_ops.h b/third_party/fwkacllib/inc/ops/save_ops.h index 5ce6c2e0..0ce473b7 100644 --- a/third_party/fwkacllib/inc/ops/save_ops.h +++ b/third_party/fwkacllib/inc/ops/save_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/sdca_ops.h b/third_party/fwkacllib/inc/ops/sdca_ops.h index 34c6a268..cbd9839d 100644 --- a/third_party/fwkacllib/inc/ops/sdca_ops.h +++ b/third_party/fwkacllib/inc/ops/sdca_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/selection_ops.h b/third_party/fwkacllib/inc/ops/selection_ops.h index dee9e0f7..6d26600d 100644 --- a/third_party/fwkacllib/inc/ops/selection_ops.h +++ b/third_party/fwkacllib/inc/ops/selection_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/set_ops.h b/third_party/fwkacllib/inc/ops/set_ops.h index 04e04f1b..1d02fa15 100644 --- a/third_party/fwkacllib/inc/ops/set_ops.h +++ b/third_party/fwkacllib/inc/ops/set_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/sparse_ops.h b/third_party/fwkacllib/inc/ops/sparse_ops.h index 09d8ced9..d7512790 100644 --- a/third_party/fwkacllib/inc/ops/sparse_ops.h +++ b/third_party/fwkacllib/inc/ops/sparse_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/spectral_ops.h b/third_party/fwkacllib/inc/ops/spectral_ops.h index be3d7d00..64fa7814 100644 --- a/third_party/fwkacllib/inc/ops/spectral_ops.h +++ b/third_party/fwkacllib/inc/ops/spectral_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/split_combination_ops.h b/third_party/fwkacllib/inc/ops/split_combination_ops.h index f1a93fa6..efe4715d 100644 --- a/third_party/fwkacllib/inc/ops/split_combination_ops.h +++ b/third_party/fwkacllib/inc/ops/split_combination_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/state_ops.h b/third_party/fwkacllib/inc/ops/state_ops.h index 3c8e32b6..db1f5353 100644 --- a/third_party/fwkacllib/inc/ops/state_ops.h +++ b/third_party/fwkacllib/inc/ops/state_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/stateful_random_ops.h b/third_party/fwkacllib/inc/ops/stateful_random_ops.h index c2f65c6a..366112d6 100644 --- a/third_party/fwkacllib/inc/ops/stateful_random_ops.h +++ b/third_party/fwkacllib/inc/ops/stateful_random_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/stateless_random_ops.h b/third_party/fwkacllib/inc/ops/stateless_random_ops.h index ff9daaa3..dad3c379 100644 --- a/third_party/fwkacllib/inc/ops/stateless_random_ops.h +++ b/third_party/fwkacllib/inc/ops/stateless_random_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/string_ops.h b/third_party/fwkacllib/inc/ops/string_ops.h index ec84cc83..4a88bc79 100644 --- a/third_party/fwkacllib/inc/ops/string_ops.h +++ b/third_party/fwkacllib/inc/ops/string_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/swap_co_ops.h b/third_party/fwkacllib/inc/ops/swap_co_ops.h index 6e8eaac3..a1bf4f8b 100644 --- a/third_party/fwkacllib/inc/ops/swap_co_ops.h +++ b/third_party/fwkacllib/inc/ops/swap_co_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/target_crop_and_resize.h b/third_party/fwkacllib/inc/ops/target_crop_and_resize.h index 9bef1d7b..9c61f2c9 100644 --- a/third_party/fwkacllib/inc/ops/target_crop_and_resize.h +++ b/third_party/fwkacllib/inc/ops/target_crop_and_resize.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/ops/transformation_ops.h b/third_party/fwkacllib/inc/ops/transformation_ops.h index d24c0512..c7477cd2 100644 --- a/third_party/fwkacllib/inc/ops/transformation_ops.h +++ b/third_party/fwkacllib/inc/ops/transformation_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -519,7 +519,8 @@ REG_OP(Unpack) * @par Inputs: * x: A 4D Tensor with shape [batch, in_rows, in_cols, depth], Must be one of the * following types:float32, double, int32, uint8, int16, int8, int64, uint16, -* float16, uint32, uint64 +* float16, uint32, uint64. The inputs must have data_format with one of follows: +* NHWC, NCHW. * @par Attributes: * @li ksizes: A required list or tuple. The size of the sliding window for each @@ -534,7 +535,6 @@ REG_OP(Unpack) * This is equivalent to rate in dilated (a.k.a. Atrous) convolutions. * @li padding: A required string. The type of padding algorithm to use, support "SAME" or "VALID". \n -* @li data_format: A required string. The format of input, only supported NHWC. \n * @par Outputs: * y: A 4D Tensor with shape [batch, out_rows, out_cols, ksize_rows * @@ -555,7 +555,6 @@ REG_OP(ExtractImagePatches) .REQUIRED_ATTR(strides, ListInt) .REQUIRED_ATTR(rates, ListInt) .REQUIRED_ATTR(padding, String) - .ATTR(data_format, String, "NHWC") .OP_END_FACTORY_REG(ExtractImagePatches) /** @@ -564,6 +563,7 @@ REG_OP(ExtractImagePatches) * @par Inputs: * x: A 5D Tensor with shape [batch, in_planes, in_rows, in_cols, depth] . \n +* The inputs must have data_format with one of follows: NDHWC, NCDHW. \n * @par Attributes: * @li ksizes: A required list or tuple. The size of the sliding window for each @@ -572,7 +572,6 @@ REG_OP(ExtractImagePatches) * patches are in "x". Must be: [1, stride_planes, stride_rows, stride_cols, 1]. * @li padding: A required string. The type of padding algorithm to use , * support "SAME" or "VALID" . \n -* @li data_format: An optional string. The format of input, only supported NDHWC. \n * @par Outputs: * Output: A 5D Tensor with shape [batch, out_planes, out_rows, out_cols, ksize_planes * @@ -591,7 +590,6 @@ REG_OP(ExtractVolumePatches) .REQUIRED_ATTR(ksizes, ListInt) .REQUIRED_ATTR(strides, ListInt) .REQUIRED_ATTR(padding, String) - .ATTR(data_format, String, "NDHWC") .OP_END_FACTORY_REG(ExtractVolumePatches) /** diff --git a/third_party/fwkacllib/inc/ops/warp_perspective_ops.h b/third_party/fwkacllib/inc/ops/warp_perspective_ops.h index 8ef69d8b..e19cbd7c 100644 --- a/third_party/fwkacllib/inc/ops/warp_perspective_ops.h +++ b/third_party/fwkacllib/inc/ops/warp_perspective_ops.h @@ -1,5 +1,5 @@ /** - * Copyright 2019 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/third_party/fwkacllib/inc/runtime/base.h b/third_party/fwkacllib/inc/runtime/base.h index d8e271aa..da10938a 100644 --- a/third_party/fwkacllib/inc/runtime/base.h +++ b/third_party/fwkacllib/inc/runtime/base.h @@ -1,18 +1,18 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd - + * Copyright 2019-2020 Huawei Technologies Co., Ltd + * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at - + * * http://www.apache.org/licenses/LICENSE-2.0 - + * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. -*/ + */ #ifndef __CCE_RUNTIME_BASE_H__ #define __CCE_RUNTIME_BASE_H__ @@ -81,11 +81,11 @@ typedef enum tagRtLimitType { } rtLimitType_t; typedef struct rtExceptionInfo { - uint32_t taskid; - uint32_t streamid; - uint32_t tid; - uint32_t deviceid; - uint32_t retcode; + uint32_t taskid; + uint32_t streamid; + uint32_t tid; + uint32_t deviceid; + uint32_t retcode; } rtExceptionInfo; typedef void (*rtErrorCallback)(rtExceptionType); diff --git a/third_party/fwkacllib/inc/runtime/config.h b/third_party/fwkacllib/inc/runtime/config.h index 12a407d7..c35a1278 100644 --- a/third_party/fwkacllib/inc/runtime/config.h +++ b/third_party/fwkacllib/inc/runtime/config.h @@ -1,18 +1,18 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd - + * Copyright 2019-2020 Huawei Technologies Co., Ltd + * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at - + * * http://www.apache.org/licenses/LICENSE-2.0 - + * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. -*/ + */ #ifndef __CCE_RUNTIME_CONFIG_H__ #define __CCE_RUNTIME_CONFIG_H__ diff --git a/third_party/fwkacllib/inc/runtime/context.h b/third_party/fwkacllib/inc/runtime/context.h index 4be49a8c..3346ff75 100644 --- a/third_party/fwkacllib/inc/runtime/context.h +++ b/third_party/fwkacllib/inc/runtime/context.h @@ -1,18 +1,18 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd - + * Copyright 2019-2020 Huawei Technologies Co., Ltd + * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at - + * * http://www.apache.org/licenses/LICENSE-2.0 - + * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. -*/ + */ #ifndef __CCE_RUNTIME_CONTEXT_H__ #define __CCE_RUNTIME_CONTEXT_H__ diff --git a/third_party/fwkacllib/inc/runtime/dev.h b/third_party/fwkacllib/inc/runtime/dev.h index d1a91a9b..c70a2372 100644 --- a/third_party/fwkacllib/inc/runtime/dev.h +++ b/third_party/fwkacllib/inc/runtime/dev.h @@ -1,18 +1,18 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd - + * Copyright 2019-2020 Huawei Technologies Co., Ltd + * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at - + * * http://www.apache.org/licenses/LICENSE-2.0 - + * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. -*/ + */ #ifndef __CCE_RUNTIME_DEVICE_H__ #define __CCE_RUNTIME_DEVICE_H__ diff --git a/third_party/fwkacllib/inc/runtime/dvfsprofile.h b/third_party/fwkacllib/inc/runtime/dvfsprofile.h index 6e451695..e27cd832 100644 --- a/third_party/fwkacllib/inc/runtime/dvfsprofile.h +++ b/third_party/fwkacllib/inc/runtime/dvfsprofile.h @@ -1,18 +1,18 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd - + * Copyright 2019-2020 Huawei Technologies Co., Ltd + * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at - + * * http://www.apache.org/licenses/LICENSE-2.0 - + * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. -*/ + */ #ifndef __CCE_RUNTIME_DVFSPROFILE_H__ #define __CCE_RUNTIME_DVFSPROFILE_H__ diff --git a/third_party/fwkacllib/inc/runtime/event.h b/third_party/fwkacllib/inc/runtime/event.h index 41e611ea..f9d2eae2 100644 --- a/third_party/fwkacllib/inc/runtime/event.h +++ b/third_party/fwkacllib/inc/runtime/event.h @@ -1,18 +1,18 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd - + * Copyright 2019-2020 Huawei Technologies Co., Ltd + * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at - + * * http://www.apache.org/licenses/LICENSE-2.0 - + * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. -*/ + */ #ifndef __CCE_RUNTIME_EVENT_H__ #define __CCE_RUNTIME_EVENT_H__ diff --git a/third_party/fwkacllib/inc/runtime/kernel.h b/third_party/fwkacllib/inc/runtime/kernel.h index 5f519442..98862ad4 100644 --- a/third_party/fwkacllib/inc/runtime/kernel.h +++ b/third_party/fwkacllib/inc/runtime/kernel.h @@ -1,18 +1,18 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd - + * Copyright 2019-2020 Huawei Technologies Co., Ltd + * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at - + * * http://www.apache.org/licenses/LICENSE-2.0 - + * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. -*/ + */ #ifndef __CCE_RUNTIME_KERNEL_H__ #define __CCE_RUNTIME_KERNEL_H__ diff --git a/third_party/fwkacllib/inc/runtime/mem.h b/third_party/fwkacllib/inc/runtime/mem.h index e65d8604..f175cd45 100644 --- a/third_party/fwkacllib/inc/runtime/mem.h +++ b/third_party/fwkacllib/inc/runtime/mem.h @@ -1,18 +1,18 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd - + * Copyright 2019-2020 Huawei Technologies Co., Ltd + * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at - + * * http://www.apache.org/licenses/LICENSE-2.0 - + * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. -*/ + */ #ifndef __CCE_RUNTIME_MEM_H__ #define __CCE_RUNTIME_MEM_H__ diff --git a/third_party/fwkacllib/inc/runtime/rt.h b/third_party/fwkacllib/inc/runtime/rt.h index 83cafa3c..0d39389b 100644 --- a/third_party/fwkacllib/inc/runtime/rt.h +++ b/third_party/fwkacllib/inc/runtime/rt.h @@ -1,18 +1,18 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd - + * Copyright 2019-2020 Huawei Technologies Co., Ltd + * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at - + * * http://www.apache.org/licenses/LICENSE-2.0 - + * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. -*/ + */ #ifndef __CCE_RUNTIME_RT_H__ #define __CCE_RUNTIME_RT_H__ diff --git a/third_party/fwkacllib/inc/runtime/rt_model.h b/third_party/fwkacllib/inc/runtime/rt_model.h index b72b142d..c96349a0 100644 --- a/third_party/fwkacllib/inc/runtime/rt_model.h +++ b/third_party/fwkacllib/inc/runtime/rt_model.h @@ -1,18 +1,18 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd - + * Copyright 2019-2020 Huawei Technologies Co., Ltd + * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at - + * * http://www.apache.org/licenses/LICENSE-2.0 - + * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. -*/ + */ #ifndef __CCE_RUNTIME_MODEL_H__ #define __CCE_RUNTIME_MODEL_H__ diff --git a/third_party/fwkacllib/inc/runtime/stream.h b/third_party/fwkacllib/inc/runtime/stream.h index 6b9f80ae..b726fbd5 100644 --- a/third_party/fwkacllib/inc/runtime/stream.h +++ b/third_party/fwkacllib/inc/runtime/stream.h @@ -1,18 +1,18 @@ /** - * Copyright 2020 Huawei Technologies Co., Ltd - + * Copyright 2019-2020 Huawei Technologies Co., Ltd + * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at - + * * http://www.apache.org/licenses/LICENSE-2.0 - + * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. -*/ + */ #ifndef __CCE_RUNTIME_STREAM_H__ #define __CCE_RUNTIME_STREAM_H__ diff --git a/third_party/fwkacllib/inc/tdt/index_transform.h b/third_party/fwkacllib/inc/tdt/index_transform.h index a5af2c83..a62e0185 100644 --- a/third_party/fwkacllib/inc/tdt/index_transform.h +++ b/third_party/fwkacllib/inc/tdt/index_transform.h @@ -1,10 +1,18 @@ /** -* @file index_transform.h -* -* Copyright (C) Huawei Technologies Co., Ltd. 2018-2019. All Rights Reserved. -* -* This program is used to get logical device id by phy device id. -*/ + * Copyright 2019-2020 Huawei Technologies Co., Ltd + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ #ifndef INC_TDT_INDEX_TRANSFORM_H #define INC_TDT_INDEX_TRANSFORM_H diff --git a/third_party/fwkacllib/inc/toolchain/prof_callback.h b/third_party/fwkacllib/inc/toolchain/prof_callback.h index 3fad74bc..1299ae59 100644 --- a/third_party/fwkacllib/inc/toolchain/prof_callback.h +++ b/third_party/fwkacllib/inc/toolchain/prof_callback.h @@ -1,5 +1,5 @@ /** - * Copyright 2020-2020 Huawei Technologies Co., Ltd + * Copyright 2019-2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -12,9 +12,6 @@ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. - * - * @file prof_callback.h - * @brief declaraion of profiling callbacks */ #ifndef MSPROFILER_PROF_CALLBACK_H_ diff --git a/third_party/fwkacllib/inc/toolchain/tuning_tool/tune_api.h b/third_party/fwkacllib/inc/toolchain/tuning_tool/tune_api.h index 12b6aa1e..87fdcbeb 100644 --- a/third_party/fwkacllib/inc/toolchain/tuning_tool/tune_api.h +++ b/third_party/fwkacllib/inc/toolchain/tuning_tool/tune_api.h @@ -1,13 +1,19 @@ /** - * @file tune_api.h + * Copyright 2019-2020 Huawei Technologies Co., Ltd * - * Copyright (c) Huawei Technologies Co., Ltd. 2020-2020. All rights reserved.\n + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.\n - * 描述：mstune调优接口头文件 + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. */ + /** @defgroup mstune mstune调优接口 */ #ifndef TUNE_API_H #define TUNE_API_H