Drop 12.4 support

Author: NicolasHug

.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

.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

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