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fix: Upgrade main to TRT 8.6, CUDA 11.8, Torch Dev
- Upgrade versions, make required code edits for functionality and coverage for tests and CI
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.circleci/config.yml

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default: "2.1.0.dev20230421+cu118"
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torch-build-index:
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type: string
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default: "https://download.pytorch.org/whl/cu118"
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default: "https://download.pytorch.org/whl/nightly/cu118"
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steps:
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- run:
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name: Install Torch
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default: "2.1.0.dev20230421+cu118"
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torch-build-index:
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type: string
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default: "https://download.pytorch.org/whl/cu118"
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default: "https://download.pytorch.org/whl/nightly/cu118"
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torch-build-legacy:
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type: string
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default: "1.13.1+cu118"
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default: "1.13.1+cu117"
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torch-build-index-legacy:
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type: string
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default: "https://download.pytorch.org/whl/cu118"
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default: "https://download.pytorch.org/whl/cu117"
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cudnn-version:
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type: string
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default: "8.5.0.96"

README.md

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@@ -31,12 +31,7 @@ In the case of building on top of a custom base container, you first must determ
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version of the PyTorch C++ ABI. If your source of PyTorch is pytorch.org, likely this is the pre-cxx11-abi in which case you must modify `//docker/dist-build.sh` to not build the
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C++11 ABI version of Torch-TensorRT.
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You can then build the container using:
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```bash
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docker build --build-arg BASE_IMG=<IMAGE> -f docker/Dockerfile -t torch_tensorrt:latest .
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```
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You can then build the container using the build command in the [docker README](docker/README.md#instructions)
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If you would like to build outside a docker container, please follow the section [Compiling Torch-TensorRT](#compiling-torch-tensorrt)
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These are the following dependencies used to verify the testcases. Torch-TensorRT can work with other versions, but the tests are not guaranteed to pass.
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- Bazel 5.2.0
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- Libtorch 2.1.0.dev20230314 (built with CUDA 11.7)
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- CUDA 11.7
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- Libtorch 2.1.0.dev20230421 (built with CUDA 11.8)
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- CUDA 11.8
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- cuDNN 8.5.0
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- TensorRT 8.5.1.7
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- TensorRT 8.6.0
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## Prebuilt Binaries and Wheel files
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docker/Dockerfile

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# Base image starts with CUDA
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ARG BASE_IMG=nvidia/cuda:11.7.1-devel-ubuntu22.04
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ARG BASE_IMG=nvidia/cuda:11.8.0-devel-ubuntu22.04
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FROM ${BASE_IMG} as base
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ARG TENSORRT_VERSION

docker/README.md

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* The `Dockerfile` currently uses <a href="https://github.com/bazelbuild/bazelisk">Bazelisk</a> to select the Bazel version, and uses the exact library versions of Torch and CUDA listed in <a href="https://github.com/pytorch/TensorRT#dependencies">dependencies</a>.
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* The desired versions of CUDNN and TensorRT must be specified as build-args, with major, minor, and patch versions as in: `--build-arg TENSORRT_VERSION=a.b.c --build-arg CUDNN_VERSION=x.y.z`
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* [**Optional**] The desired base image be changed by explicitly setting a base image, as in `--build-arg BASE_IMG=nvidia/cuda:11.7.1-devel-ubuntu22.04`, though this is optional
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* [**Optional**] The desired base image be changed by explicitly setting a base image, as in `--build-arg BASE_IMG=nvidia/cuda:11.8.0-devel-ubuntu22.04`, though this is optional
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* [**Optional**] Additionally, the desired Python version can be changed by explicitly setting a version, as in `--build-arg PYTHON_VERSION=3.10`, though this is optional as well.
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* This `Dockerfile` installs `pre-cxx11-abi` versions of Pytorch and builds Torch-TRT using `pre-cxx11-abi` libtorch as well.
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### Instructions
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- The example below uses CUDNN 8.5.0 and TensorRT 8.5.1
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- The example below uses CUDNN 8.5.0 and TensorRT 8.6.0
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- See <a href="https://github.com/pytorch/TensorRT#dependencies">dependencies</a> for a list of current default dependencies.
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> From root of Torch-TensorRT repo
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Build:
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```
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DOCKER_BUILDKIT=1 docker build --build-arg TENSORRT_VERSION=8.5.1 --build-arg CUDNN_VERSION=8.5.0 -f docker/Dockerfile -t torch_tensorrt:latest .
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DOCKER_BUILDKIT=1 docker build --build-arg TENSORRT_VERSION=8.6.0 --build-arg CUDNN_VERSION=8.5.0 -f docker/Dockerfile -t torch_tensorrt:latest .
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```
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Run:

py/setup.py

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long_description=long_description,
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ext_modules=ext_modules,
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install_requires=[
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"torch==2.0.0",
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"torch>=1.13.1",
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],
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setup_requires=[],
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cmdclass={

py/versions.py

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__version__ = "1.4.0.dev0"
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__cuda_version__ = "11.7"
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__cuda_version__ = "11.8"
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__cudnn_version__ = "8.5"
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__tensorrt_version__ = "8.5"
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__tensorrt_version__ = "8.6"

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