mirror of
https://github.com/saymrwulf/onnxruntime.git
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311 lines
12 KiB
C++
311 lines
12 KiB
C++
// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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#include "core/framework/session_state.h"
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#include <sstream>
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#include "core/common/logging/logging.h"
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#include "core/framework/node_index_info.h"
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#include "core/framework/op_kernel.h"
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#include "core/framework/utils.h"
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using namespace ::onnxruntime::common;
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namespace onnxruntime {
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const GraphViewer* SessionState::GetGraphViewer() const { return graph_viewer_.get(); }
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Status SessionState::SetGraph(const Graph& graph) {
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graph_viewer_ = onnxruntime::make_unique<onnxruntime::GraphViewer>(graph);
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auto& logger = Logger();
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// use graph_viewer_ to initialize ort_value_name_idx_map_
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LOGS(logger, INFO) << "SaveMLValueNameIndexMapping";
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int idx = 0;
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// we keep all graph inputs (including initializers), even if they are unused, so make sure they all have an entry
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for (const auto* input_def : graph_viewer_->GetInputsIncludingInitializers()) {
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idx = ort_value_name_idx_map_.Add(input_def->Name());
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VLOGS(logger, 1) << "Added graph_viewer_ input with name: " << input_def->Name()
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<< " to OrtValueIndex with index: " << idx;
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}
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for (auto& node : graph_viewer_->Nodes()) {
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// build the OrtValue->index map
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for (const auto* input_def : node.InputDefs()) {
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if (input_def->Exists()) {
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idx = ort_value_name_idx_map_.Add(input_def->Name());
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VLOGS(logger, 1) << "Added input argument with name: " << input_def->Name()
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<< " to OrtValueIndex with index: " << idx;
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}
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}
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for (const auto* input_def : node.ImplicitInputDefs()) {
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if (input_def->Exists()) {
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idx = ort_value_name_idx_map_.Add(input_def->Name());
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VLOGS(logger, 1) << "Added implicit input argument with name: " << input_def->Name()
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<< " to OrtValueIndex with index: " << idx;
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}
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}
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for (const auto* output_def : node.OutputDefs()) {
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if (output_def->Exists()) {
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ort_value_name_idx_map_.Add(output_def->Name());
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VLOGS(logger, 1) << "Added output argument with name: " << output_def->Name()
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<< " to OrtValueIndex with index: " << idx;
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}
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}
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}
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// allocate OrtValue for graph outputs when coming from initializers
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for (const auto& output : graph_viewer_->GetOutputs()) {
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if (output->Exists()) {
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idx = ort_value_name_idx_map_.Add(output->Name());
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VLOGS(logger, 1) << "Added graph output with name: " << output->Name() << " to OrtValueIndex with index: " << idx;
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}
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}
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LOGS(logger, INFO) << "Done saving OrtValue mappings.";
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return Status::OK();
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}
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Status SessionState::CreateKernels(const KernelRegistryManager& custom_registry_manager) {
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const GraphNodes& nodes = graph_viewer_->Nodes();
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if (!nodes.empty()) {
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size_t max_nodeid = 0;
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for (auto& node : graph_viewer_->Nodes()) {
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max_nodeid = std::max(max_nodeid, node.Index());
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}
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session_kernels_.clear();
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session_kernels_.resize(max_nodeid + 1, nullptr);
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for (auto& node : graph_viewer_->Nodes()) {
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// construct and save the kernels
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std::unique_ptr<OpKernel> op_kernel;
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onnxruntime::ProviderType exec_provider_name = node.GetExecutionProviderType();
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const IExecutionProvider* exec_provider = nullptr;
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if (exec_provider_name.empty() || (exec_provider = execution_providers_.get().Get(exec_provider_name)) == nullptr) {
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return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "Could not create kernel for node: ", node.Name(),
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" as there's no execution provider allocated.");
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}
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common::Status status = custom_registry_manager.CreateKernel(node, *exec_provider, *this, op_kernel);
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if (!status.IsOK()) {
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return common::Status(
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status.Category(), status.Code(),
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MakeString("Kernel creation failed for node: ", node.Name(), " with error: ", status.ErrorMessage()));
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}
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assert(session_kernels_[node.Index()] == nullptr);
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// assumes vector is already resize()'ed to the number of nodes in the graph
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session_kernels_[node.Index()] = op_kernel.release();
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}
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}
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node_index_info_ = onnxruntime::make_unique<NodeIndexInfo>(*graph_viewer_, ort_value_name_idx_map_);
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return Status::OK();
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}
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void SessionState::SetExecutionPlan(std::unique_ptr<SequentialExecutionPlan> p_seq_exec_plan) {
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p_seq_exec_plan_ = std::move(p_seq_exec_plan);
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}
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const SequentialExecutionPlan* SessionState::GetExecutionPlan() const { return p_seq_exec_plan_.get(); }
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Status SessionState::AddInitializedTensor(int ort_value_index, const OrtValue& ort_value, const OrtCallback* d,
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bool constant) {
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auto p = initialized_tensors_.insert({ort_value_index, ort_value});
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if (!p.second)
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return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "duplicated ort_value index:", ort_value_index,
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". Do you have duplicated calls to SessionState::AddInitializedTensor function?");
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if (d != nullptr && d->f != nullptr) {
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deleter_for_initialized_tensors_[ort_value_index] = *d;
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}
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if (constant) {
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constant_initialized_tensors_.insert({ort_value_index, ort_value});
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}
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return Status::OK();
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}
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const std::unordered_map<int, OrtValue>& SessionState::GetInitializedTensors() const { return initialized_tensors_; }
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const std::unordered_map<int, OrtValue>& SessionState::GetConstantInitializedTensors() const {
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return constant_initialized_tensors_;
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}
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SessionState& SessionState::SetLogger(const logging::Logger& logger) {
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logger_ = &logger;
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return *this;
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}
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const logging::Logger& SessionState::Logger() const {
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// DefaultLogger either throws or returns a valid logger.
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const logging::Logger* logger = logger_ != nullptr ? logger_ : &logging::LoggingManager::DefaultLogger();
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return *logger;
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}
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void SessionState::SetProfiler(profiling::Profiler& profiler) { profiler_ = &profiler; }
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::onnxruntime::profiling::Profiler& SessionState::Profiler() const { return *profiler_; }
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static int64_t CalculateMemoryPatternsKey(const std::vector<std::reference_wrapper<const TensorShape>>& shapes) {
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int64_t key = 0;
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for (auto shape : shapes) {
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for (auto dim : shape.get().GetDims()) key ^= dim;
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}
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return key;
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}
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const MemoryPatternGroup* SessionState::GetMemoryPatternGroup(
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const std::vector<std::reference_wrapper<const TensorShape>>& input_shapes) const {
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int64_t key = CalculateMemoryPatternsKey(input_shapes);
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std::lock_guard<OrtMutex> lock(mem_patterns_lock_);
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auto it = mem_patterns_.find(key);
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if (it == mem_patterns_.end()) return nullptr;
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return it->second.get();
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}
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Status SessionState::UpdateMemoryPatternGroupCache(
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const std::vector<std::reference_wrapper<const TensorShape>>& input_shapes,
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std::unique_ptr<MemoryPatternGroup> mem_patterns) const {
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int64_t key = CalculateMemoryPatternsKey(input_shapes);
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std::lock_guard<OrtMutex> lock(mem_patterns_lock_);
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auto it = mem_patterns_.find(key);
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if (it == mem_patterns_.end()) {
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mem_patterns_[key] = std::move(mem_patterns);
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}
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return Status::OK();
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}
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bool SessionState::GetEnableMemoryPattern() const { return enable_mem_pattern_; }
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common::Status SessionState::AddInputNameToNodeInfoMapping(const std::string& input_name, const NodeInfo& node_info) {
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// Graph partitioning should ensure an input is only consumed from one device. Copy nodes should have been inserted
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// to handle a scenario where an input is required on different devices by different nodes. Validate that.
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auto& entries = input_names_to_nodeinfo_mapping_[input_name];
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if (entries.empty()) {
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entries.push_back(node_info);
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} else {
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const auto& existing_entry = entries.front();
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// if index == max it's an entry for an implicit input to a subgraph or unused graph input.
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// we want to prefer the entry for explicit usage in this graph, as the implicit usage in a
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// subgraph will be handled by the subgraph's SessionState.
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if (node_info.index == std::numeric_limits<size_t>::max()) {
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// ignore and preserve existing value
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} else if (existing_entry.index == std::numeric_limits<size_t>::max()) {
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// replace existing entry that is for an implicit input with new entry for explicit usage in this graph
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entries[0] = node_info;
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} else {
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// if the devices match we can add the new entry for completeness (it will be ignored in
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// utils::CopyOneInputAcrossDevices though).
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// if they don't, we are broken.
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const auto& current_device = entries[0].device;
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const auto& new_device = node_info.device;
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if (current_device == new_device) {
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entries.push_back(node_info);
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} else {
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return ORT_MAKE_STATUS(
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ONNXRUNTIME, NOT_IMPLEMENTED,
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"Using an input in multiple nodes on different devices is not supported currently. Input:", input_name,
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" is used by node ", existing_entry.p_node->Name(), " (", current_device->ToString(), ") and node ",
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node_info.p_node->Name(), " (", new_device->ToString(), ").");
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}
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}
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}
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return Status::OK();
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}
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common::Status SessionState::GetInputNodeInfo(const std::string& input_name,
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std::vector<NodeInfo>& node_info_vec) const {
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auto entry = input_names_to_nodeinfo_mapping_.find(input_name);
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if (entry == input_names_to_nodeinfo_mapping_.cend()) {
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return Status(ONNXRUNTIME, FAIL, "Failed to find input name in the mapping: " + input_name);
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}
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node_info_vec = entry->second;
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return Status::OK();
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}
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const SessionState::NameNodeInfoMapType& SessionState::GetInputNodeInfoMap() const {
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return input_names_to_nodeinfo_mapping_;
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}
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void SessionState::AddOutputNameToNodeInfoMapping(const std::string& output_name, const NodeInfo& node_info) {
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auto& output_names_to_nodeinfo = output_names_to_nodeinfo_mapping_[output_name];
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ORT_ENFORCE(output_names_to_nodeinfo.empty(), "Only one node should produce an output. Existing entry for ",
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output_name);
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output_names_to_nodeinfo.push_back(node_info);
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}
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common::Status SessionState::GetOutputNodeInfo(const std::string& output_name,
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std::vector<NodeInfo>& node_info_vec) const {
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auto entry = output_names_to_nodeinfo_mapping_.find(output_name);
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if (entry == output_names_to_nodeinfo_mapping_.cend()) {
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return Status(ONNXRUNTIME, FAIL, "Failed to find output name in the mapping: " + output_name);
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}
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node_info_vec = entry->second;
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return Status::OK();
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}
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const SessionState::NameNodeInfoMapType& SessionState::GetOutputNodeInfoMap() const {
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return output_names_to_nodeinfo_mapping_;
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}
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void SessionState::AddSubgraphSessionState(onnxruntime::NodeIndex index, const std::string& attribute_name,
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std::unique_ptr<SessionState> session_state) {
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auto entry = subgraph_session_states_.find(index);
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// make sure this is new. internal logic error if it is not so using ORT_ENFORCE.
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if (entry != subgraph_session_states_.cend()) {
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const auto& existing_entries = entry->second;
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ORT_ENFORCE(existing_entries.find(attribute_name) == existing_entries.cend(), "Entry exists in node ", index,
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" for attribute ", attribute_name);
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}
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#ifdef ONNXRUNTIME_ENABLE_INSTRUMENT
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session_state->parent_ = this;
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GenerateGraphId();
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#endif
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subgraph_session_states_[index].insert(std::make_pair(attribute_name, std::move(session_state)));
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}
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SessionState* SessionState::GetMutableSubgraphSessionState(onnxruntime::NodeIndex index,
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const std::string& attribute_name) {
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SessionState* session_state = nullptr;
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auto node_entry = subgraph_session_states_.find(index);
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if (node_entry != subgraph_session_states_.cend()) {
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const auto& attribute_state_map = node_entry->second;
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const auto& subgraph_entry = attribute_state_map.find(attribute_name);
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if (subgraph_entry != attribute_state_map.cend()) {
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session_state = subgraph_entry->second.get();
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}
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}
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return session_state;
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}
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const SessionState* SessionState::GetSubgraphSessionState(onnxruntime::NodeIndex index,
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const std::string& attribute_name) const {
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return const_cast<SessionState*>(this)->GetMutableSubgraphSessionState(index, attribute_name);
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}
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void SessionState::RemoveSubgraphSessionState(onnxruntime::NodeIndex index) {
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subgraph_session_states_.erase(index);
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}
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const NodeIndexInfo& SessionState::GetNodeIndexInfo() const {
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ORT_ENFORCE(node_index_info_, "SetGraphAndCreateKernels must be called prior to GetExecutionInfo.");
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return *node_index_info_;
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}
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} // namespace onnxruntime
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