From 95fecb91c8739222a77dd3125f47b7dd6bb98017 Mon Sep 17 00:00:00 2001 From: Jim Chen Date: Wed, 8 Oct 2025 17:21:28 +0800 Subject: [PATCH 1/2] build: upgrade PyTorch to 2.7.1 with CUDA 12.8 and multi-platform support - feat: upgrade PyTorch to 2.7.1 and CUDA 12.8 * Update README setup to require CUDA toolkit 12.8 instead of 12.4 (Linux and Windows) * Bump torch dependency from 2.6.0 to 2.7.1 * Switch the PyTorch CUDA wheel index from cu124 to cu128 - Revert "docs: add troubleshooting section for libcudnn dependencies in README" * The issue of relying on two different versions of CUDNN in this project has been resolved. - build(pyproject): relax python version and constrain package deps * Only download torch from PyTorch; obtain all other packages from PyPI. * Restrict numpy, onnxruntime, pandas to be compatible with Python 3.9 - build(pyproject): require triton 3.3.0+ for arm64 support * Add triton version 3.3.0 or newer to the dependencies to support arm64 architecture. - build: skip Triton on Windows since it isn't supported * Add a platform marker to the triton dependency to skip it on Windows, as triton does not support Windows. - build: configure PyTorch sources for cross-platform compatibility * macOS uses CPU-only PyTorch from pytorch-cpu index * Linux and Windows use CUDA 12.8 PyTorch from pytorch index * triton only installs on Linux with CUDA 12.8 support * Update lockfile to support multi-platform builds - fix: restrict av to <16.0.0 for Python 3.9 compatibility * Add av<16.0.0 to dependencies to maintain Python 3.9 support * Update comment to include av in the restriction list * Update uv.lock accordingly PyAV dropped Python 3.9 support in v16.0.0: https://github.com/PyAV-Org/PyAV/commit/106089447cab9dc6d3ca2d1ab7e0aeff76d7a6a4 - fix: resolve PyTorch ARM64 platform compatibility issue * Update uv.lock to properly handle aarch64 platforms for PyTorch dependencies * Add resolution markers for ARM64 Linux systems to use CPU-only PyTorch builds * Ensure CUDA builds are only used on x86_64 platforms where supported Resolves ARM64 Docker build failures by preventing uv from attempting to install CUDA PyTorch on unsupported platforms - chore: change .python-version to 3.10 --- Signed-off-by: CHEN, CHUN Signed-off-by: Jim Chen Co-authored-by: GitHub Copilot --- .python-version | 1 + README.md | 28 +- pyproject.toml | 40 +- uv.lock | 3473 +++++++++++++++++++++++++++-------------------- 4 files changed, 2033 insertions(+), 1509 deletions(-) create mode 100644 .python-version diff --git a/.python-version b/.python-version new file mode 100644 index 00000000..c8cfe395 --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.10 diff --git a/README.md b/README.md index e036120b..ff9d2aa5 100644 --- a/README.md +++ b/README.md @@ -62,6 +62,15 @@ This repository provides fast automatic speech recognition (70x realtime with la

Setup ⚙️

+### 0. CUDA Installation + +To use WhisperX with GPU acceleration, install the CUDA toolkit 12.8 before WhisperX. Skip this step if using only the CPU. + +- For **Linux** users, install the CUDA toolkit 12.8 following this guide: + [CUDA Installation Guide for Linux](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/). +- For **Windows** users, download and install the CUDA toolkit 12.8: + [CUDA Downloads](https://developer.nvidia.com/cuda-12-8-1-download-archive). + ### 1. Simple Installation (Recommended) The easiest way to install WhisperX is through PyPi: @@ -102,25 +111,6 @@ uv sync --all-extras --dev You may also need to install ffmpeg, rust etc. Follow openAI instructions here https://github.com/openai/whisper#setup. -### Common Issues & Troubleshooting 🔧 - -#### libcudnn Dependencies (GPU Users) - -If you're using WhisperX with GPU support and encounter errors like: - -- `Could not load library libcudnn_ops_infer.so.8` -- `Unable to load any of {libcudnn_cnn.so.9.1.0, libcudnn_cnn.so.9.1, libcudnn_cnn.so.9, libcudnn_cnn.so}` -- `libcudnn_ops_infer.so.8: cannot open shared object file: No such file or directory` - -This means your system is missing the CUDA Deep Neural Network library (cuDNN). This library is needed for GPU acceleration but isn't always installed by default. - -**Install cuDNN (example for apt based systems):** - -```bash -sudo apt update -sudo apt install libcudnn8 libcudnn8-dev -y -``` - ### Speaker Diarization To **enable Speaker Diarization**, include your Hugging Face access token (read) that you can generate from [Here](https://huggingface.co/settings/tokens) after the `--hf_token` argument and accept the user agreement for the following models: [Segmentation](https://huggingface.co/pyannote/segmentation-3.0) and [Speaker-Diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) (if you choose to use Speaker-Diarization 2.x, follow requirements [here](https://huggingface.co/pyannote/speaker-diarization) instead.) diff --git a/pyproject.toml b/pyproject.toml index b1663c5a..876cf5ed 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -9,16 +9,19 @@ requires-python = ">=3.9, <3.13" license = { text = "BSD-2-Clause" } dependencies = [ - "ctranslate2<4.5.0", + "ctranslate2>=4.5.0", "faster-whisper>=1.1.1", "nltk>=3.9.1", - "numpy>=2.0.2", - "onnxruntime>=1.19", - "pandas>=2.2.3", + # Restrict numpy, onnxruntime, pandas, av to be compatible with Python 3.9 + "numpy>=2.0.2,<2.1.0", + "onnxruntime>=1.19,<1.20.0", + "pandas>=2.2.3,<2.3.0", + "av<16.0.0", "pyannote-audio>=3.3.2,<4.0.0", - "torch>=2.5.1", - "torchaudio>=2.5.1", + "torch>=2.7.1", + "torchaudio", "transformers>=4.48.0", + "triton>=3.3.0; sys_platform == 'linux'" # only install triton on Linux ] @@ -34,3 +37,28 @@ include-package-data = true [tool.setuptools.packages.find] where = ["."] include = ["whisperx*"] + +[tool.uv.sources] +torch = [ + { index = "pytorch-cpu", marker = "sys_platform == 'darwin'" }, + { index = "pytorch-cpu", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { index = "pytorch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, +] +torchaudio = [ + { index = "pytorch-cpu", marker = "sys_platform == 'darwin'" }, + { index = "pytorch-cpu", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { index = "pytorch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, +] +triton = [ + { index = "pytorch", marker = "sys_platform == 'linux'" }, +] + +[[tool.uv.index]] +name = "pytorch" +url = "https://download.pytorch.org/whl/cu128" +explicit = true + +[[tool.uv.index]] +name = "pytorch-cpu" +url = "https://download.pytorch.org/whl/cpu" +explicit = true diff --git a/uv.lock b/uv.lock index 4c073e56..2690e576 100644 --- a/uv.lock +++ b/uv.lock @@ -2,23 +2,36 @@ version = 1 revision = 3 requires-python = ">=3.9, <3.13" resolution-markers = [ - "python_full_version >= '3.12'", - "python_full_version == '3.11.*'", - "python_full_version < '3.11'", + "python_full_version >= '3.12' and sys_platform == 'darwin'", + "python_full_version == '3.11.*' and sys_platform == 'darwin'", + "python_full_version == '3.10.*' and sys_platform == 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