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narendasannarendasan
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Merge branch 'snake_case_apis_cpp' into 'main'
refactor!: Changing the C++ api to be snake case See merge request nvidia/trtorch/Torch-TensorRT-Preview!3
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‎.gitignore

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@@ -56,4 +56,5 @@ examples/int8/ptq/ptq
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examples/int8/qat/qat
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examples/int8/training/vgg16/data/*
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examples/int8/datasets/data/*
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env/**/*
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env/**/*
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bazel-Torch-TensorRT-Preview

‎README.md

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@@ -14,7 +14,7 @@ More Information / System Architecture:
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## Building a docker container for Torch-TensorRT Preview
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We provide a `Dockerfile` in `docker/` directory. We build `Torch-TensorRT` on top of a `Pytorch NGC container` which provide basic dependencies (like CUDA, CUDNN, CUBLAS, TensorRT, Pytorch and others) The dependency libraries in the container can be found in the <a href="https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/index.html">release notes</a>.
17+
We provide a `Dockerfile` in `docker/` directory. We build `Torch-TensorRT` on top of a `Pytorch NGC container` which provide basic dependencies (like CUDA, CUDNN, CUBLAS, TensorRT, Pytorch and others) The dependency libraries in the container can be found in the <a href="https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/index.html">release notes</a>.
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Please follow this instruction to build a Docker container.
2020

@@ -41,7 +41,7 @@ auto compile_settings = torch_tensorrt::ts::CompileSpec({input});
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// FP16 execution
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compile_settings.enabled_precisions = {torch::kHalf};
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// Compile module
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auto trt_mod = torch_tensorrt::ts::CompileModule(ts_mod, compile_settings);
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auto trt_mod = torch_tensorrt::ts::compile(ts_mod, compile_settings);
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// Run like normal
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auto results = trt_mod.forward({in_tensor});
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// Save module for later

‎core/partitioning/README.md

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@@ -62,6 +62,6 @@ torchtrt::ts::CompileSpec cfg(input_sizes);
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cfg.torch_fallback = torchtrt::CompileSpec::TorchFallback(true);
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cfg.torch_fallback.min_block_size = 2;
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cfg.torch_fallback.forced_fallback_ops.push_back("aten::relu");
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auto trt_mod = torchtrt::ts::CompileModule(mod, cfg);
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auto trt_mod = torchtrt::ts::compile(mod, cfg);
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auto out = trt_mod.forward({in});
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```

‎cpp/bin/torchtrtc/main.cpp

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@@ -600,7 +600,7 @@ int main(int argc, char** argv) {
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// Instead of compiling, just embed engine in a PyTorch module
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if (embed_engine) {
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std::string serialized_engine = read_buf(real_input_path);
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auto trt_mod = torchtrt::ts::EmbedEngineInNewModule(serialized_engine, compile_settings.device);
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auto trt_mod = torchtrt::ts::embed_engine_in_new_module(serialized_engine, compile_settings.device);
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trt_mod.save(real_output_path);
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return 0;
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}
@@ -615,19 +615,19 @@ int main(int argc, char** argv) {
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}
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if (require_full_compilation) {
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if (!torchtrt::ts::CheckMethodOperatorSupport(mod, "forward")) {
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if (!torchtrt::ts::check_method_operator_support(mod, "forward")) {
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torchtrt::logging::log(torchtrt::logging::Level::kERROR, "Module is not currently supported by Torch-TensorRT");
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return 1;
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}
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}
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if (save_engine) {
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auto engine = torchtrt::ts::ConvertMethodToTRTEngine(mod, "forward", compile_settings);
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auto engine = torchtrt::ts::convert_method_to_trt_engine(mod, "forward", compile_settings);
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std::ofstream out(real_output_path);
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out << engine;
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out.close();
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} else {
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auto trt_mod = torchtrt::ts::CompileModule(mod, compile_settings);
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auto trt_mod = torchtrt::ts::compile(mod, compile_settings);
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if (!no_threshold_check &&
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(compile_settings.enabled_precisions.size() == 1 &&

‎cpp/include/torch_tensorrt/torch_tensorrt.h

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@@ -701,7 +701,7 @@ struct TORCHTRT_API CompileSpec {
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*
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* @returns bool: Method is supported by Torch-TensorRT.TorchScript
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*/
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TORCHTRT_API bool CheckMethodOperatorSupport(const torch::jit::Module& module, std::string method_name);
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TORCHTRT_API bool check_method_operator_support(const torch::jit::Module& module, std::string method_name);
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/**
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* @brief Compile a TorchScript module for NVIDIA GPUs using TensorRT
@@ -717,7 +717,7 @@ TORCHTRT_API bool CheckMethodOperatorSupport(const torch::jit::Module& module, s
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*
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* @return: A new module trageting a TensorRT engine
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*/
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TORCHTRT_API torch::jit::Module CompileModule(const torch::jit::Module& module, CompileSpec info);
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TORCHTRT_API torch::jit::Module compile(const torch::jit::Module& module, CompileSpec info);
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/**
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* @brief Compile a TorchScript method for NVIDIA GPUs using TensorRT
@@ -733,7 +733,7 @@ TORCHTRT_API torch::jit::Module CompileModule(const torch::jit::Module& module,
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* @return: std::string: Serialized TensorRT engine equivilant to the method
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* graph
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*/
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TORCHTRT_API std::string ConvertMethodToTRTEngine(
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TORCHTRT_API std::string convert_method_to_trt_engine(
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const torch::jit::Module& module,
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std::string method_name,
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CompileSpec info);
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*
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* @return: A new module trageting a TensorRT engine
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*/
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TORCHTRT_API torch::jit::Module EmbedEngineInNewModule(const std::string& engine, Device device);
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TORCHTRT_API torch::jit::Module embed_engine_in_new_module(const std::string& engine, Device device);
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} // namespace torchscript
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} // namespace torch_tensorrt

‎cpp/src/torch_tensorrt.cpp

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@@ -12,11 +12,11 @@ namespace torchscript {
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// Defined in compile_spec.cpp
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torch_tensorrt::core::CompileSpec to_internal_compile_spec(CompileSpec external);
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bool CheckMethodOperatorSupport(const torch::jit::script::Module& module, std::string method_name) {
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bool check_method_operator_support(const torch::jit::script::Module& module, std::string method_name) {
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return torch_tensorrt::core::CheckMethodOperatorSupport(module, method_name);
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}
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std::string ConvertMethodToTRTEngine(
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std::string convert_method_to_trt_engine(
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const torch::jit::script::Module& module,
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std::string method_name,
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CompileSpec info) {
@@ -26,14 +26,14 @@ std::string ConvertMethodToTRTEngine(
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return torch_tensorrt::core::ConvertGraphToTRTEngine(module, method_name, to_internal_compile_spec(info));
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}
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torch::jit::script::Module CompileModule(const torch::jit::script::Module& module, CompileSpec info) {
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torch::jit::script::Module compile(const torch::jit::script::Module& module, CompileSpec info) {
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LOG_DEBUG(get_build_info());
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// Want to export a much simpler (non TRT header dependent) API so doing the
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// type conversion here
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return torch_tensorrt::core::CompileGraph(module, to_internal_compile_spec(info));
3434
}
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torch::jit::Module EmbedEngineInNewModule(const std::string& engine, Device device) {
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torch::jit::Module embed_engine_in_new_module(const std::string& engine, Device device) {
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return torch_tensorrt::core::EmbedEngineInNewModule(engine, to_internal_cuda_device(device));
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}
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‎docs/_cpp_api/class_view_hierarchy.html

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<head>
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<meta charset="utf-8"/>
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<meta content="width=device-width, initial-scale=1.0" name="viewport"/>
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<meta content="Docutils 0.17.1: http://docutils.sourceforge.net/" name="generator"/>
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<meta content="width=device-width,initial-scale=1" name="viewport"/>
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<meta content="ie=edge" http-equiv="x-ua-compatible"/>
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<meta content="Copy to clipboard" name="lang:clipboard.copy"/>
@@ -299,17 +300,17 @@
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</li>
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<li class="md-nav__item">
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<a class="md-nav__link" href="../_notebooks/lenet-getting-started.html">
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TRTorch Getting Started - LeNet
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Torch-TensorRT Getting Started - LeNet
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</a>
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</li>
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<li class="md-nav__item">
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<a class="md-nav__link" href="../_notebooks/ssd-object-detection-demo.html">
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Object Detection with TRTorch (SSD)
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Object Detection with Torch-TensorRT (SSD)
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</a>
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</li>
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<li class="md-nav__item">
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<a class="md-nav__link" href="../_notebooks/vgg-qat.html">
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Deploying Quantization Aware Trained models in INT8 using TRTorch
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Deploying Quantization Aware Trained models in INT8 using Torch-TensorRT
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</a>
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</li>
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<li class="md-nav__item">
@@ -392,114 +393,116 @@
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</div>
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<div class="md-content">
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<article class="md-content__inner md-typeset" role="main">
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<h1 id="cpp-api-class-view-hierarchy--page-root">
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Class Hierarchy
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<a class="headerlink" href="#cpp-api-class-view-hierarchy--page-root" title="Permalink to this headline">
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<ul class="treeView" id="class-treeView">
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Namespace
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<a href="namespace_torch_tensorrt.html#namespace-torch-tensorrt">
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torch_tensorrt
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<ul>
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<li>
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Namespace
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<a href="namespace_torch_tensorrt__logging.html#namespace-torch-tensorrt-logging">
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torch_tensorrt::logging
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</a>
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<ul>
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<li class="lastChild">
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Enum
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<a href="enum_logging_8h_1a130f65408ad8cbaee060f05e8db69558.html#exhale-enum-logging-8h-1a130f65408ad8cbaee060f05e8db69558">
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Level
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Namespace
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<a href="namespace_torch_tensorrt__ptq.html#namespace-torch-tensorrt-ptq">
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torch_tensorrt::ptq
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<ul>
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Template Class
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<a href="classtorch__tensorrt_1_1ptq_1_1Int8CacheCalibrator.html#exhale-class-classtorch-tensorrt-1-1ptq-1-1Int8CacheCalibrator">
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Int8CacheCalibrator
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Template Class
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Int8Calibrator
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torch_tensorrt::torchscript
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Struct
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<a href="structtorch__tensorrt_1_1torchscript_1_1CompileSpec.html#exhale-struct-structtorch-tensorrt-1-1torchscript-1-1CompileSpec">
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CompileSpec
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Device
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Class
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Device::DeviceType
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Input
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<a href="classtorch__tensorrt_1_1DataType.html#exhale-class-classtorch-tensorrt-1-1DataType">
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DataType
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</li>
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Class
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<a href="classtorch__tensorrt_1_1TensorFormat.html#exhale-class-classtorch-tensorrt-1-1TensorFormat">
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TensorFormat
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</a>
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</li>
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Enum
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<a href="enum_torch__tensorrt_8h_1a3fbe5d72e4fc624dbd038853079620eb.html#exhale-enum-torch-tensorrt-8h-1a3fbe5d72e4fc624dbd038853079620eb">
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EngineCapability
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<!-- only tree view element -->
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</ul>
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<!-- /treeView class-treeView -->
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<section id="class-hierarchy">
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<h1 id="cpp-api-class-view-hierarchy--page-root">
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Class Hierarchy
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<a class="headerlink" href="#cpp-api-class-view-hierarchy--page-root" title="Permalink to this headline">
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</a>
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</h1>
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<ul class="treeView" id="class-treeView">
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<li>
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<ul class="collapsibleList">
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<li class="lastChild">
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Namespace
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<a href="namespace_torch_tensorrt.html#namespace-torch-tensorrt">
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torch_tensorrt
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</a>
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<ul>
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<li>
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Namespace
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<a href="namespace_torch_tensorrt__logging.html#namespace-torch-tensorrt-logging">
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torch_tensorrt::logging
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</a>
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<ul>
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<li class="lastChild">
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Enum
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<a href="enum_logging_8h_1a130f65408ad8cbaee060f05e8db69558.html#exhale-enum-logging-8h-1a130f65408ad8cbaee060f05e8db69558">
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Level
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</a>
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</li>
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</ul>
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</li>
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<li>
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Namespace
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<a href="namespace_torch_tensorrt__ptq.html#namespace-torch-tensorrt-ptq">
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torch_tensorrt::ptq
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</a>
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<ul>
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<li>
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Template Class
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<a href="classtorch__tensorrt_1_1ptq_1_1Int8CacheCalibrator.html#exhale-class-classtorch-tensorrt-1-1ptq-1-1Int8CacheCalibrator">
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Int8CacheCalibrator
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</a>
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</li>
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<li class="lastChild">
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Template Class
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<a href="classtorch__tensorrt_1_1ptq_1_1Int8Calibrator.html#exhale-class-classtorch-tensorrt-1-1ptq-1-1Int8Calibrator">
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Int8Calibrator
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</a>
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</li>
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</ul>
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</li>
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<li>
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Namespace
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<a href="namespace_torch_tensorrt__torchscript.html#namespace-torch-tensorrt-torchscript">
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torch_tensorrt::torchscript
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</a>
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<ul>
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Struct
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<a href="structtorch__tensorrt_1_1torchscript_1_1CompileSpec.html#exhale-struct-structtorch-tensorrt-1-1torchscript-1-1CompileSpec">
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CompileSpec
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</a>
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</li>
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</ul>
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Struct
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<a href="structtorch__tensorrt_1_1Device.html#exhale-struct-structtorch-tensorrt-1-1Device">
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Device
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</a>
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<ul>
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<li class="lastChild">
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Class
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<a href="classtorch__tensorrt_1_1Device_1_1DeviceType.html#exhale-class-classtorch-tensorrt-1-1Device-1-1DeviceType">
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Device::DeviceType
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</a>
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</li>
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</ul>
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Struct
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<a href="structtorch__tensorrt_1_1Input.html#exhale-struct-structtorch-tensorrt-1-1Input">
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Input
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</a>
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</li>
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Class
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<a href="classtorch__tensorrt_1_1DataType.html#exhale-class-classtorch-tensorrt-1-1DataType">
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DataType
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</li>
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Class
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<a href="classtorch__tensorrt_1_1TensorFormat.html#exhale-class-classtorch-tensorrt-1-1TensorFormat">
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TensorFormat
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</a>
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</li>
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<li class="lastChild">
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Enum
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<a href="enum_torch__tensorrt_8h_1a3fbe5d72e4fc624dbd038853079620eb.html#exhale-enum-torch-tensorrt-8h-1a3fbe5d72e4fc624dbd038853079620eb">
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EngineCapability
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<!-- only tree view element -->
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</section>
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