From 88a7940fbc43bbc2f6e1e8ccdd1e714117557484 Mon Sep 17 00:00:00 2001 From: Nicolas Hug Date: Wed, 26 Feb 2025 09:31:34 +0000 Subject: [PATCH] Drop 12.4 support --- .github/workflows/docs.yaml | 3 --- .github/workflows/linux_cuda_wheel.yaml | 8 +------- README.md | 18 ++++++++---------- 3 files changed, 9 insertions(+), 20 deletions(-) diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml index 59ddf382d..89e8401de 100644 --- a/.github/workflows/docs.yaml +++ b/.github/workflows/docs.yaml @@ -75,9 +75,6 @@ jobs: uses: pytorch/test-infra/.github/actions/setup-miniconda@main with: python-version: ${{ matrix.python-version }} - # - # For some reason nvidia::libnpp=12.4 doesn't install but nvidia/label/cuda-12.4.0::libnpp does. - # So we use the latter convention for libnpp. # We install conda packages at the start because otherwise conda may have conflicts with dependencies. default-packages: "nvidia/label/cuda-${{ matrix.cuda-version }}.0::libnpp nvidia::cuda-nvrtc=${{ matrix.cuda-version }} nvidia::cuda-toolkit=${{ matrix.cuda-version }} nvidia::cuda-cudart=${{ matrix.cuda-version }} nvidia::cuda-driver-dev=${{ matrix.cuda-version }} conda-forge::ffmpeg=${{ matrix.ffmpeg-version-for-tests }}" - name: Check env diff --git a/.github/workflows/linux_cuda_wheel.yaml b/.github/workflows/linux_cuda_wheel.yaml index ec3c195b7..3eebc48fc 100644 --- a/.github/workflows/linux_cuda_wheel.yaml +++ b/.github/workflows/linux_cuda_wheel.yaml @@ -66,12 +66,9 @@ jobs: # For the actual release we should add that label and change this to # include more python versions. python-version: ['3.9'] - cuda-version: ['11.8', '12.4', '12.6'] + cuda-version: ['11.8', '12.6'] # TODO: put back ffmpeg 5 https://github.com/pytorch/torchcodec/issues/325 ffmpeg-version-for-tests: ['4.4.2', '6', '7'] - exclude: - - cuda-version: '12.4' # TODO put this back it fails with infra issue. - ffmpeg-version-for-tests: '4.4.2' container: image: "pytorch/manylinux2_28-builder:cuda${{ matrix.cuda-version }}" @@ -92,9 +89,6 @@ jobs: uses: pytorch/test-infra/.github/actions/setup-miniconda@main with: python-version: ${{ matrix.python-version }} - # - # For some reason nvidia::libnpp=12.4 doesn't install but nvidia/label/cuda-12.4.0::libnpp does. - # So we use the latter convention for libnpp. # We install conda packages at the start because otherwise conda may have conflicts with dependencies. default-packages: "nvidia/label/cuda-${{ matrix.cuda-version }}.0::libnpp nvidia::cuda-nvrtc=${{ matrix.cuda-version }} nvidia::cuda-toolkit=${{ matrix.cuda-version }} nvidia::cuda-cudart=${{ matrix.cuda-version }} nvidia::cuda-driver-dev=${{ matrix.cuda-version }} conda-forge::ffmpeg=${{ matrix.ffmpeg-version-for-tests }}" - name: Check env diff --git a/README.md b/README.md index 855b3e4bf..7fc912529 100644 --- a/README.md +++ b/README.md @@ -146,14 +146,12 @@ First, make sure you have a GPU that has NVDEC hardware that can decode the format you want. Refer to Nvidia's GPU support matrix for more details [here](https://developer.nvidia.com/video-encode-and-decode-gpu-support-matrix-new). -1. Install CUDA Toolkit. Pytorch and TorchCodec supports CUDA Toolkit - versions 11.8, 12.1 or 12.4. In particular TorchCodec depends on - CUDA libraries libnpp and libnvrtc (which are part of CUDA Toolkit). +1. Install Pytorch corresponding to your CUDA Toolkit using the + [official instructions](https://pytorch.org/get-started/locally/). You'll + need the `libnpp` and `libnvrtc` CUDA libraries, which are usually part of + the CUDA Toolkit. -2. Install Pytorch that corresponds to your CUDA Toolkit version using the - [official instructions](https://pytorch.org/get-started/locally/). - -3. Install or compile FFmpeg with NVDEC support. +2. Install or compile FFmpeg with NVDEC support. TorchCodec with CUDA should work with FFmpeg versions in [5, 7]. If FFmpeg is not already installed, or you need a more recent version, an @@ -184,13 +182,13 @@ format you want. Refer to Nvidia's GPU support matrix for more details ffmpeg -hwaccel cuda -hwaccel_output_format cuda -i test/resources/nasa_13013.mp4 -f null - ``` -4. Install TorchCodec by passing in an `--index-url` parameter that corresponds +3. Install TorchCodec by passing in an `--index-url` parameter that corresponds to your CUDA Toolkit version, example: ```bash - # This corresponds to CUDA Toolkit version 12.4. It should be the same one + # This corresponds to CUDA Toolkit version 12.6. It should be the same one # you used when you installed PyTorch (If you installed PyTorch with pip). - pip install torchcodec --index-url=https://download.pytorch.org/whl/cu124 + pip install torchcodec --index-url=https://download.pytorch.org/whl/cu126 ``` Note that without passing in the `--index-url` parameter, `pip` installs