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225 lines
9.3 KiB
225 lines
9.3 KiB
/**
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* Copyright 2019-2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "hybrid_model_executor.h"
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#include "graph/ge_context.h"
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#include "graph/runtime_inference_context.h"
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#include "graph/utils/tensor_utils.h"
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#include "common/dump/dump_manager.h"
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#include "common/profiling/profiling_manager.h"
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namespace ge {
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namespace hybrid {
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namespace {
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const int kIntBase = 10;
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const char *const kEnvProfilingLevel = "HYBRID_PROFILING_LEVEL";
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} // namespace
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HybridModelExecutor::HybridModelExecutor(HybridModel *model, uint32_t device_id, rtStream_t stream)
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: model_(model), device_id_(device_id), stream_(stream) {
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}
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HybridModelExecutor::~HybridModelExecutor() {
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if (context_.rt_gen_context != nullptr) {
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(void) rtCtxDestroy(context_.rt_gen_context);
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}
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}
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Status HybridModelExecutor::Init() {
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GELOGD("Start to init HybridGraphEngine.");
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GE_CHK_STATUS_RET_NOLOG(InitExecutionContext());
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GELOGD("HybridGraphEngine initialized successfully.");
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return SUCCESS;
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}
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Status HybridModelExecutor::Execute(HybridModelExecutor::ExecuteArgs &args) {
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GELOGD("Start to execute model.");
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auto root_graph_item = model_->GetRootGraphItem();
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GE_CHECK_NOTNULL(root_graph_item);
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if (root_graph_item->IsDynamic()) {
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GE_CHK_STATUS_RET(CheckInputShapeByShapeRange(root_graph_item, args),
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"[%s] check input node shape by shape range failed.",
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root_graph_item->GetName().c_str());
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}
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if (context_.global_step != nullptr) {
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GE_CHK_RT_RET(rtMemcpyAsync(context_.global_step, sizeof(uint64_t), &context_.iteration,
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sizeof(uint64_t), RT_MEMCPY_HOST_TO_DEVICE_EX, context_.stream));
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}
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SubgraphExecutor executor(model_->GetRootGraphItem(), &context_);
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auto ret = ExecuteGraphInternal(executor, args);
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Cleanup();
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RECORD_MODEL_EXECUTION_EVENT(&context_, "[Cleanup] End");
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GELOGD("Model executed successfully.");
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if (context_.profiler != nullptr) {
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context_.profiler->Dump(std::cout);
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context_.profiler->Reset();
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}
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context_.iteration += 1;
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if (ret == END_OF_SEQUENCE) {
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args.is_eos = true;
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} else {
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GE_CHK_STATUS_RET(ret, "[Invoke][ExecuteGraphInternal] Failed, ret:%d.", ret);
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}
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return SUCCESS;
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}
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Status HybridModelExecutor::ExecuteGraphInternal(SubgraphExecutor &executor,
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HybridModelExecutor::ExecuteArgs &args) {
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RECORD_MODEL_EXECUTION_EVENT(&context_, "[InitContext] Start");
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GE_CHK_STATUS_RET_NOLOG(ResetExecutionContext(context_));
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RECORD_MODEL_EXECUTION_EVENT(&context_, "[InitContext] End");
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uint64_t index_id = context_.iteration + 1;
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uint64_t model_id = static_cast<uint64_t>(model_->GetModelId());
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int32_t device_id = static_cast<int32_t>(device_id_);
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auto &prof_mgr = ProfilingManager::Instance();
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// tag_id 0 means step begin, 1 meas step end.
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if (!model_->IsSingleOp() && prof_mgr.ProfilingModelLoadOn()) {
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GE_CHK_STATUS_RET_NOLOG(prof_mgr.ProfileStepInfo(index_id, model_id, 0, stream_, device_id));
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}
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HYBRID_CHK_STATUS_RET(executor.ExecuteAsync(args.inputs, args.input_desc, args.outputs),
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"Failed to execute partitioned call.");
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RECORD_MODEL_EXECUTION_EVENT(&context_, "[ExecuteAsync] End");
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if (!model_->IsSingleOp() && prof_mgr.ProfilingModelLoadOn()) {
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GE_CHK_STATUS_RET_NOLOG(prof_mgr.ProfileStepInfo(index_id, model_id, 1, stream_, device_id));
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}
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if (!model_->IsSingleOp()) {
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HYBRID_CHK_STATUS_RET(executor.Synchronize(), "Failed to sync root graph.");
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RECORD_MODEL_EXECUTION_EVENT(&context_, "[Synchronize] End");
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}
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args.outputs.clear();
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HYBRID_CHK_STATUS_RET(executor.GetOutputs(args.outputs, args.output_desc), "Failed to get outputs");
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RECORD_MODEL_EXECUTION_EVENT(&context_, "[GetOutput] End");
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return SUCCESS;
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}
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Status HybridModelExecutor::Cleanup() {
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GELOGD("Start to cleanup.");
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context_.callback_manager->Destroy();
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RuntimeInferenceContext::DestroyContext(std::to_string(context_.context_id));
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GELOGD("Cleanup successfully.");
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return SUCCESS;
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}
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Status HybridModelExecutor::InitExecutionContext() {
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GE_CHK_RT_RET(rtCtxGetCurrent(&context_.rt_context));
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GE_CHK_RT_RET(rtCtxCreate(&context_.rt_gen_context, RT_CTX_GEN_MODE, 0));
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GE_CHK_RT_RET(rtCtxSetCurrent(context_.rt_context));
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context_.global_step = model_->GetGlobalStep();
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context_.stream = stream_;
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context_.model = model_;
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context_.is_eos_ = false;
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context_.session_id = ::ge::GetContext().SessionId();
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context_.ge_context = &GetThreadLocalContext();
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GELOGD("session id from model = %lu, from context = %lu", model_->GetSessionId(), context_.session_id);
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context_.allocator = NpuMemoryAllocator::GetAllocator(device_id_);
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GE_CHECK_NOTNULL(context_.allocator);
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context_.callback_manager = std::unique_ptr<CallbackManager>(new(std::nothrow)CallbackManager());
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GE_CHECK_NOTNULL(context_.callback_manager);
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context_.dump_properties = DumpManager::GetInstance().GetDumpProperties(context_.session_id);
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const char *profiling_level = std::getenv(kEnvProfilingLevel);
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if (profiling_level != nullptr) {
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context_.profiling_level = std::strtol(profiling_level, nullptr, kIntBase);
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GELOGD("Got profiling level = %ld", context_.profiling_level);
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if (context_.profiling_level > 0) {
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context_.profiler.reset(new(std::nothrow)HybridProfiler());
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GE_CHECK_NOTNULL(context_.profiler);
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}
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}
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if (IsLogEnable(GE_MODULE_NAME, DLOG_DEBUG)) {
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context_.trace_enabled = true;
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}
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return SUCCESS;
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}
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Status HybridModelExecutor::ResetExecutionContext(GraphExecutionContext &context) {
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GE_CHK_STATUS_RET_NOLOG(context.callback_manager->Init());
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string ctx_id = std::to_string(context.context_id);
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RuntimeInferenceContext::DestroyContext(ctx_id);
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GE_CHK_GRAPH_STATUS_RET(RuntimeInferenceContext::CreateContext(ctx_id), "Failed to Destroy RuntimeInferenceContext");
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RuntimeInferenceContext *ctx = nullptr;
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GE_CHK_GRAPH_STATUS_RET(RuntimeInferenceContext::GetContext(ctx_id, &ctx), "Failed to get context");
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for (auto &host_tensor : context.model->GetHostTensors()) {
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auto node_id = host_tensor.first;
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for (const auto &output_idx_and_tensor : host_tensor.second) {
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auto output_idx = output_idx_and_tensor.first;
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GELOGD("Preload const host tensor, node_id = %ld, output id = %d", node_id, output_idx);
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ctx->SetTensor(node_id, output_idx, output_idx_and_tensor.second.Clone());
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}
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}
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return SUCCESS;
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}
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Status HybridModelExecutor::CheckInputShapeByShapeRange(const GraphItem *graph_item,
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HybridModelExecutor::ExecuteArgs &args) {
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GE_CHECK_NOTNULL(graph_item);
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auto input_nodes = graph_item->GetInputNodes();
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if (args.input_desc.size() < input_nodes.size()) {
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REPORT_INNER_ERROR("E19999", "[%s] Number of inputs [%zu] is not sufficient for graph which needs [%zu] inputs.",
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graph_item->GetName().c_str(), args.input_desc.size(), input_nodes.size());
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GELOGE(INTERNAL_ERROR, "[%s] Number of inputs [%zu] is not sufficient for graph which needs [%zu] inputs.",
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graph_item->GetName().c_str(), args.input_desc.size(), input_nodes.size());
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return INTERNAL_ERROR;
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}
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for (size_t i = 0; i < input_nodes.size(); ++i) {
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auto &input_node = input_nodes[i];
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if (input_node == nullptr) {
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GELOGD("[%s] Input[%zu] is not needed by graph, skip it.", graph_item->GetName().c_str(), i);
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continue;
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}
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GeTensorDescPtr model_input_desc = input_node->MutableInputDesc(0);
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GE_CHECK_NOTNULL(model_input_desc);
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std::vector<std::pair<int64_t, int64_t>> shape_range;
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if (model_input_desc->GetShapeRange(shape_range) != SUCCESS) {
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REPORT_INNER_ERROR("E19999", "[%s] Input[%zu] get shape range failed", graph_item->GetName().c_str(), i);
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GELOGE(INTERNAL_ERROR, "[%s] Input[%zu] get shape range failed", graph_item->GetName().c_str(), i);
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return INTERNAL_ERROR;
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}
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if (shape_range.empty()) {
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GELOGD("[%s] Input[%zu] shape is not needed to check by shape range, skip it.", graph_item->GetName().c_str(), i);
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continue;
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}
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ConstGeTensorDescPtr args_tensor_desc = args.input_desc[i];
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GE_CHECK_NOTNULL(args_tensor_desc);
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GeShape shape = args_tensor_desc->GetShape();
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if (shape.IsUnknownShape()) {
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REPORT_INNER_ERROR("E19999", "[%s] Input desc shape [%zu] designed by user must be static.",
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graph_item->GetName().c_str(), i);
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GELOGE(INTERNAL_ERROR, "[%s] Input desc shape [%zu] designed by user must be static.",
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graph_item->GetName().c_str(), i);
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return INTERNAL_ERROR;
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}
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if (TensorUtils::CheckShapeByShapeRange(shape, shape_range) != SUCCESS) {
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GELOGE(PARAM_INVALID, "[Check][InputShape] [%s] check input [%zu] shape failed by shape range.",
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graph_item->GetName().c_str(), i);
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return PARAM_INVALID;
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}
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}
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return SUCCESS;
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}
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} // namespace hybrid
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} // namespace ge
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