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* SPDX-FileCopyrightText: Copyright (c) 1993-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*
* 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 TRT_SAMPLE_INFERENCE_H
#define TRT_SAMPLE_INFERENCE_H
#include "debugTensorWriter.h"
#include "sampleDevice.h"
#include "sampleEngines.h"
#include "sampleReporting.h"
#include "sampleUtils.h"
#include <functional>
#include <iostream>
#include <list>
#include <memory>
#include <string>
#include <vector>
#if ENABLE_UNIFIED_BUILDER
#include "safeCudaAllocator.h"
#endif
namespace sample
{
using LibraryPtr = std::unique_ptr<samplesCommon::DynamicLibrary>;
std::string const TRT_NVINFER_NAME = "nvinfer";
std::string const TRT_ONNXPARSER_NAME = "nvonnxparser";
std::string const TRT_LIB_SUFFIX = "";
#if !TRT_STATIC
#if defined(_WIN32)
std::string const kNVINFER_PLUGIN_LIBNAME
= std::string{"nvinfer_plugin_"} + std::to_string(NV_TENSORRT_MAJOR) + std::string{".dll"};
std::string const kNVINFER_LIBNAME = std::string(TRT_NVINFER_NAME) + std::string{"_"}
+ std::to_string(NV_TENSORRT_MAJOR) + TRT_LIB_SUFFIX + std::string{".dll"};
std::string const kNVINFER_SAFE_LIBNAME
= std::string{"nvinfer_safe_"} + std::to_string(NV_TENSORRT_MAJOR) + std::string{".dll"};
std::string const kNVONNXPARSER_LIBNAME = std::string(TRT_ONNXPARSER_NAME) + std::string{"_"}
+ std::to_string(NV_TENSORRT_MAJOR) + TRT_LIB_SUFFIX + std::string{".dll"};
std::string const kNVINFER_LEAN_LIBNAME
= std::string{"nvinfer_lean_"} + std::to_string(NV_TENSORRT_MAJOR) + std::string{".dll"};
std::string const kNVINFER_DISPATCH_LIBNAME
= std::string{"nvinfer_dispatch_"} + std::to_string(NV_TENSORRT_MAJOR) + std::string{".dll"};
#else
std::string const kNVINFER_PLUGIN_LIBNAME = std::string{"libnvinfer_plugin.so."} + std::to_string(NV_TENSORRT_MAJOR);
std::string const kNVINFER_LIBNAME
= std::string{"lib"} + std::string(TRT_NVINFER_NAME) + std::string{".so."} + std::to_string(NV_TENSORRT_MAJOR);
std::string const kNVINFER_SAFE_LIBNAME = std::string{"libnvinfer_safe.so."} + std::to_string(NV_TENSORRT_MAJOR);
std::string const kNVONNXPARSER_LIBNAME
= std::string{"lib"} + std::string(TRT_ONNXPARSER_NAME) + std::string{".so."} + std::to_string(NV_TENSORRT_MAJOR);
std::string const kNVINFER_LEAN_LIBNAME = std::string{"libnvinfer_lean.so."} + std::to_string(NV_TENSORRT_MAJOR);
std::string const kNVINFER_DISPATCH_LIBNAME
= std::string{"libnvinfer_dispatch.so."} + std::to_string(NV_TENSORRT_MAJOR);
#endif
std::string const& getRuntimeLibraryName(RuntimeMode const mode);
template <typename FetchPtrs>
bool initLibrary(LibraryPtr& libPtr, std::string const& libName, FetchPtrs fetchFunc)
{
if (libPtr != nullptr)
{
return true;
}
try
{
libPtr.reset(new samplesCommon::DynamicLibrary{libName});
fetchFunc(libPtr.get());
}
catch (std::exception const& e)
{
libPtr.reset();
sample::gLogError << "Could not load library " << libName << ": " << e.what() << std::endl;
return false;
}
catch (...)
{
libPtr.reset();
sample::gLogError << "Could not load library " << libName << std::endl;
return false;
}
return true;
}
#endif // !TRT_STATIC
#if ENABLE_UNIFIED_BUILDER
namespace safe
{
//!
//! \brief Initialize the NVIDIA Inference Safe Runtime library
//!
//! This function dynamically loads the Safe TensorRT runtime library and initializes
//! function pointers for safe TensorRT operations. It is used to set up the safe runtime
//! environment for inference with safety-certified TensorRT engines.
//!
//! \return true if the safe runtime library was successfully loaded and initialized,
//! false otherwise (e.g., in static builds or if library loading fails)
//!
bool initNvinferSafe();
//!
//! \brief Create a safe TRT graph from serialized engine data
//!
//! This function creates a safe TRT graph from serialized engine data. It is used to create
//! a safe TRT graph for inference with safety-certified TensorRT engines.
//!
//! \param graph: Pointer to the safe TRT graph to be created
//! \param blob: Pointer to the serialized engine data
//! \param size: Size of the serialized engine data
//! \param recorder: Reference to the safe recorder
//! \param useManaged: Flag indicating whether to use managed memory
//! \param allocator: Pointer to the safe memory allocator
//! \return Error code indicating the success or failure of the operation
//!
nvinfer1::ErrorCode createSafeTRTGraph(nvinfer2::safe::ITRTGraph*& graph, void const* blob, int64_t size,
ISafeRecorder& recorder, bool useManaged, ISafeMemAllocator* allocator);
//!
//! \brief Destroy a safe TRT graph and release resources
//!
//! This function destroys a safe TRT graph and releases the associated resources. It is used to clean up
//! the safe TRT graph after inference with safety-certified TensorRT engines.
//!
//! \param graph: Pointer to the safe TRT graph to be destroyed
//! \return Error code indicating the success or failure of the operation
//!
nvinfer1::ErrorCode destroySafeTRTGraph(nvinfer2::safe::ITRTGraph*& graph);
//!
//! \brief Get the safe plugin registry for loading plugins
//!
//! This function retrieves the safe plugin registry for loading plugins. It is used to get the safe plugin registry
//! for loading plugins with safety-certified TensorRT engines.
//!
//! \param recorder: Reference to the safe recorder
//! \return Pointer to the safe plugin registry
//!
nvinfer2::safe::ISafePluginRegistry* getSafePluginRegistry(ISafeRecorder& recorder);
} // namespace safe
#endif
struct InferenceEnvironmentBase
{
InferenceEnvironmentBase() = delete;
virtual ~InferenceEnvironmentBase() = default;
InferenceEnvironmentBase(InferenceEnvironmentBase const& other) = delete;
InferenceEnvironmentBase(InferenceEnvironmentBase&& other) = delete;
InferenceEnvironmentBase(BuildEnvironment& bEnv)
: engine(std::move(bEnv.engine))
, safe(bEnv.engine.isSafe())
, cmdline(bEnv.cmdline)
{
}
LazilyDeserializedEngine engine;
std::unique_ptr<Profiler> profiler;
std::vector<TrtDeviceBuffer>
deviceMemory; //< Device memory used for inference when the allocation strategy is not static.
std::unique_ptr<DebugTensorWriter> listener;
bool error{false};
bool safe{false};
std::string cmdline;
};
struct InferenceEnvironmentStd : public InferenceEnvironmentBase
{
InferenceEnvironmentStd() = delete;
InferenceEnvironmentStd(InferenceEnvironmentStd const& other) = delete;
InferenceEnvironmentStd(InferenceEnvironmentStd&& other) = delete;
InferenceEnvironmentStd(BuildEnvironment& bEnv)
: InferenceEnvironmentBase(bEnv)
{
}
std::vector<std::unique_ptr<nvinfer1::IExecutionContext>> contexts;
std::vector<std::unique_ptr<BindingsStd>> bindings;
inline nvinfer1::IExecutionContext* getContext(int32_t streamIdx);
//! Storage for input shape tensors.
//!
//! It's important that the addresses of the data do not change between the calls to
//! setTensorAddress/setInputShape (which tells TensorRT where the input shape tensor is)
//! and enqueueV3 (when TensorRT might use the input shape tensor).
//!
//! The input shape tensors could alternatively be handled via member bindings,
//! but it simplifies control-flow to store the data here since it's shared across
//! the bindings.
std::list<std::vector<int64_t>> inputShapeTensorValues;
};
#if ENABLE_UNIFIED_BUILDER
// Forward declaration of BindingsSafe
class BindingsSafe;
struct InferenceEnvironmentSafe : public InferenceEnvironmentBase
{
InferenceEnvironmentSafe() = delete;
InferenceEnvironmentSafe(InferenceEnvironmentSafe const& other) = delete;
InferenceEnvironmentSafe(InferenceEnvironmentSafe&& other) = delete;
InferenceEnvironmentSafe(BuildEnvironment& bEnv)
: InferenceEnvironmentBase(bEnv)
{
}
std::vector<std::unique_ptr<BindingsSafe>> bindings;
inline void* getClonedGraph(int32_t streamIdx);
std::vector<std::unique_ptr<nvinfer2::safe::ITRTGraph>> mClonedGraphs;
};
#endif
inline nvinfer1::IExecutionContext* InferenceEnvironmentStd::getContext(int32_t streamIdx)
{
return contexts[streamIdx].get();
}
//!
//! \brief Set up contexts/graphs and bindings for inference
//!
bool setUpInference(InferenceEnvironmentBase& iEnv, InferenceOptions const& inference, SystemOptions const& system);
#if ENABLE_UNIFIED_BUILDER
//!
//! \brief Set up graphs and bindings for safe inference
//!
bool setUpSafeInference(InferenceEnvironmentSafe& iEnv, InferenceOptions const& inference, SystemOptions const& system);
#endif
//!
//! \brief Set up contexts and bindings for standard inference
//!
bool setUpStdInference(InferenceEnvironmentStd& iEnv, InferenceOptions const& inference, SystemOptions const& system);
//!
//! \brief Deserialize the engine and time how long it takes.
//!
bool timeDeserialize(InferenceEnvironmentBase& iEnv, SystemOptions const& sys);
//!
//! \brief Run inference and collect timing, return false if any error hit during inference
//!
bool runInference(InferenceOptions const& inference, InferenceEnvironmentBase& iEnv, int32_t device,
std::vector<InferenceTrace>& trace, ReportingOptions const& reporting);
//!
//! \brief Get layer information of the engine.
//!
std::string getLayerInformation(
nvinfer1::ICudaEngine* engine, nvinfer1::IExecutionContext* context, nvinfer1::LayerInformationFormat format);
struct Binding
{
bool isInput{false};
std::unique_ptr<IMirroredBuffer> buffer;
std::unique_ptr<OutputAllocator> outputAllocator;
int64_t volume{0};
nvinfer1::DataType dataType{nvinfer1::DataType::kFLOAT};
void fill(std::string const& fileName);
void fill();
void dump(std::ostream& os, nvinfer1::Dims dims, nvinfer1::Dims strides, int32_t vectorDim, int32_t spv,
std::string const separator = " ") const;
};
struct TensorInfo
{
int32_t bindingIndex{-1};
char const* name{nullptr};
nvinfer1::Dims dims{};
bool isDynamic{};
int32_t comps{-1};
nvinfer1::Dims strides{};
int32_t vectorDimIndex{-1};
bool isInput{};
nvinfer1::DataType dataType{};
int64_t vol{-1};
void updateVolume(int32_t batch)
{
vol = volume(dims, strides, vectorDimIndex, comps, batch);
}
};
class BindingsBase
{
public:
BindingsBase() = delete;
explicit BindingsBase(bool useManaged)
: mUseManaged(useManaged)
{
}
void addBinding(TensorInfo const& tensorInfo, std::string const& fileName = "");
void** getDeviceBuffers();
void transferInputToDevice(TrtCudaStream& stream);
void transferOutputToHost(TrtCudaStream& stream);
void fill(int binding, std::string const& fileName)
{
mBindings[binding].fill(fileName);
}
void fill(int binding)
{
mBindings[binding].fill();
}
std::unordered_map<std::string, int> getInputBindings() const
{
auto isInput = [](Binding const& b) { return b.isInput; };
return getBindings(isInput);
}
std::unordered_map<std::string, int> getOutputBindings() const
{
auto isOutput = [](Binding const& b) { return !b.isInput; };
return getBindings(isOutput);
}
std::unordered_map<std::string, int> getBindings() const
{
auto all = [](Binding const& b) { return true; };
return getBindings(all);
}
std::unordered_map<std::string, int> getBindings(std::function<bool(Binding const&)> predicate) const;
protected:
std::unordered_map<std::string, int32_t> mNames;
std::vector<Binding> mBindings;
std::vector<void*> mDevicePointers;
bool mUseManaged{false};
};
class BindingsStd : public BindingsBase
{
public:
BindingsStd() = delete;
explicit BindingsStd(bool useManaged)
: BindingsBase(useManaged)
{
}
void dumpInputs(nvinfer1::IExecutionContext const& context, std::ostream& os) const
{
auto isInput = [](Binding const& b) { return b.isInput; };
dumpBindings(context, isInput, os);
}
void dumpOutputs(nvinfer1::IExecutionContext const& context, std::ostream& os) const
{
auto isOutput = [](Binding const& b) { return !b.isInput; };
dumpBindings(context, isOutput, os);
}
void dumpBindings(nvinfer1::IExecutionContext const& context, std::ostream& os) const
{
auto all = [](Binding const& b) { return true; };
dumpBindings(context, all, os);
}
void dumpBindings(nvinfer1::IExecutionContext const& context, std::function<bool(Binding const&)> predicate,
std::ostream& os) const
{
for (auto const& n : mNames)
{
auto const name = n.first;
auto const binding = n.second;
if (predicate(mBindings[binding]))
{
os << n.first << ": (";
dumpBindingDimensions(name, context, os);
os << ")" << std::endl;
dumpBindingValues(context, binding, os);
os << std::endl;
}
}
}
void dumpBindingDimensions(
std::string const& name, nvinfer1::IExecutionContext const& context, std::ostream& os) const;
void dumpBindingValues(nvinfer1::IExecutionContext const& context, int32_t binding, std::ostream& os,
std::string const& separator = " ", int32_t batch = 1) const;
void dumpRawBindingToFiles(nvinfer1::IExecutionContext const& context, std::ostream& os) const;
bool setTensorAddresses(nvinfer1::IExecutionContext& context) const;
};
#if ENABLE_UNIFIED_BUILDER
class BindingsSafe : public BindingsBase
{
public:
BindingsSafe() = delete;
explicit BindingsSafe(bool useManaged)
: BindingsBase(useManaged)
{
}
void dumpInputs(ITRTGraph const& graph, std::ostream& os) const
{
auto isInput = [](Binding const& b) { return b.isInput; };
dumpBindings(graph, isInput, os);
}
void dumpOutputs(ITRTGraph const& graph, std::ostream& os) const
{
auto isOutput = [](Binding const& b) { return !b.isInput; };
dumpBindings(graph, isOutput, os);
}
void dumpBindings(ITRTGraph const& graph, std::ostream& os) const
{
auto all = [](Binding const& b) { return true; };
dumpBindings(graph, all, os);
}
void dumpBindings(ITRTGraph const& graph, std::function<bool(Binding const&)> predicate, std::ostream& os) const
{
for (auto const& n : mNames)
{
auto const name = n.first;
auto const binding = n.second;
if (predicate(mBindings[binding]))
{
os << n.first << ": (";
dumpBindingDimensions(name, graph, os);
os << ")" << std::endl;
dumpBindingValues(graph, binding, os);
os << std::endl;
}
}
}
void dumpBindingDimensions(std::string const& name, ITRTGraph const& graph, std::ostream& os) const;
void dumpBindingValues(ITRTGraph const& graph, int32_t binding, std::ostream& os,
std::string const& separator = " ", int32_t batch = 1) const;
void dumpRawBindingToFiles(ITRTGraph& graph, std::ostream& os) const;
bool setTensorAddresses(ITRTGraph& graph) const;
};
#endif
struct TaskInferenceEnvironment
{
TaskInferenceEnvironment(std::string engineFile, InferenceOptions const& inference,
ReportingOptions const& reporting, int32_t deviceId = 0,
int32_t DLACore = -1, int32_t bs = batchNotProvided);
InferenceOptions iOptions{};
ReportingOptions rOptions{};
int32_t device{defaultDevice};
int32_t batch{batchNotProvided};
std::unique_ptr<InferenceEnvironmentStd> iEnv;
std::vector<InferenceTrace> trace;
};
bool runMultiTasksInference(std::vector<std::unique_ptr<TaskInferenceEnvironment>>& tEnvList);
} // namespace sample
#endif // TRT_SAMPLE_INFERENCE_H
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