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upgrade pytorch from 2.9.0.dev to 2.10.0.dev (#3826)
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MODULE.bazel

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module(
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name = "torch_tensorrt",
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version = "2.9.0a0",
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version = "2.10.0a0",
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repo_name = "org_pytorch_tensorrt",
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)
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README.md

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<h4> Easily achieve the best inference performance for any PyTorch model on the NVIDIA platform. </h4>
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[![Documentation](https://img.shields.io/badge/docs-master-brightgreen)](https://nvidia.github.io/Torch-TensorRT/)
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[![pytorch](https://img.shields.io/badge/PyTorch-2.9-green)](https://download.pytorch.org/whl/nightly/cu130)
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[![pytorch](https://img.shields.io/badge/PyTorch-2.10-green)](https://download.pytorch.org/whl/nightly/cu130)
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[![cuda](https://img.shields.io/badge/CUDA-13.0-green)](https://developer.nvidia.com/cuda-downloads)
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[![trt](https://img.shields.io/badge/TensorRT-10.12.0-green)](https://github.com/nvidia/tensorrt)
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[![trt](https://img.shields.io/badge/TensorRT-10.13.0-green)](https://github.com/nvidia/tensorrt)
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[![license](https://img.shields.io/badge/license-BSD--3--Clause-blue)](./LICENSE)
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[![Linux x86-64 Nightly Wheels](https://github.com/pytorch/TensorRT/actions/workflows/build-test-linux-x86_64.yml/badge.svg?branch=nightly)](https://github.com/pytorch/TensorRT/actions/workflows/build-test-linux-x86_64.yml)
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[![Linux SBSA Nightly Wheels](https://github.com/pytorch/TensorRT/actions/workflows/build-test-linux-aarch64.yml/badge.svg?branch=nightly)](https://github.com/pytorch/TensorRT/actions/workflows/build-test-linux-aarch64.yml)
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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 8.1.1
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- Libtorch 2.9.0.dev (latest nightly)
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- CUDA 12.8 (CUDA 12.6 on Jetson)
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- Libtorch 2.10.0.dev (latest nightly)
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- CUDA 13.0 (CUDA 12.6 on Jetson)
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- TensorRT 10.13.2.6 (TensorRT 10.3 on Jetson)
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## Deprecation Policy

cpp/include/torch_tensorrt/macros.h

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#define STR(x) XSTR(x)
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#define TORCH_TENSORRT_MAJOR_VERSION 2
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#define TORCH_TENSORRT_MINOR_VERSION 9
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#define TORCH_TENSORRT_MINOR_VERSION 10
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#define TORCH_TENSORRT_PATCH_VERSION 0
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#define TORCH_TENSORRT_VERSION \
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STR(TORCH_TENSORRT_MAJOR_VERSION) \

py/requirements.txt

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packaging
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pybind11==2.6.2
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--extra-index-url https://download.pytorch.org/whl/nightly/cu130
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torch>=2.9.0.dev,<2.10.0
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torch>=2.10.0.dev,<2.11.0
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--extra-index-url https://pypi.ngc.nvidia.com
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pyyaml
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dllist

pyproject.toml

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"ninja>=1.11.0",
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"pyyaml>=6.0",
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"cffi>=1.15.1",
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"torch>=2.9.0.dev,<2.10.0; platform_machine != 'aarch64' or (platform_machine == 'aarch64' and 'tegra' not in platform_release)",
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"torch>=2.10.0.dev,<2.11.0; platform_machine != 'aarch64' or (platform_machine == 'aarch64' and 'tegra' not in platform_release)",
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"torch>=2.8.0,<2.9.0; platform_machine == 'aarch64' and 'tegra' in platform_release",
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"pybind11==2.6.2",
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]

setup.py

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# standard linux and windows requirements
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requirements = base_requirements + ["numpy"]
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if not IS_DLFW_CI:
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requirements = requirements + ["torch>=2.9.0.dev,<2.10.0"]
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requirements = requirements + ["torch>=2.10.0.dev,<2.11.0"]
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if USE_TRT_RTX:
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requirements = requirements + [
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"tensorrt_rtx>=1.0.0.21",
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if IS_DLFW_CI:
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return sbsa_requirements
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return sbsa_requirements + [
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"torch>=2.9.0.dev,<2.10.0",
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"torch>=2.10.0.dev,<2.11.0",
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"tensorrt>=10.13.0,<10.14.0",
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"tensorrt-cu12>=10.13.0,<10.14.0",
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"tensorrt-cu12-bindings>=10.13.0,<10.14.0",

tests/py/requirements.txt

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# flashinfer-python is broken on python 3.9 at the moment, so skip it for now
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flashinfer-python; python_version >'3.9' and python_version <'3.13'
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--extra-index-url https://download.pytorch.org/whl/nightly/cu130
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torchvision>=0.24.0.dev,<0.25.0
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torchvision>=0.25.0.dev,<0.26.0
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timm>=1.0.3

version.txt

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2.9.0a0
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2.10.0a0

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