requirements_aarch64.txt

#
# DGX Spark / aarch64 CUDA install
#
# `torchcodec==0.8.1` currently has no PyPI wheel for aarch64, but HF `datasets` audio decoding
# requires `torchcodec` at runtime for this project (sample["audio"]["array"]).
#
# This requirements file forces CUDA-enabled PyTorch + TorchCodec by using the PyTorch CUDA wheel index
# as the *primary* package source.
#
--pre
#
# IMPORTANT:
# If you use `--extra-index-url`, pip may still install CPU-only PyTorch from PyPI on aarch64.
# Use the PyTorch CUDA index as `--index-url` to avoid accidentally getting `torch==...+cpu`.
#
# If you need non-PyTorch packages from PyPI, we add PyPI as a *fallback* via `--extra-index-url`.
--index-url https://download.pytorch.org/whl/nightly/cu130
--extra-index-url https://pypi.org/simple

transformers[torch]==4.48.2
datasets==4.4.1
scikit-learn==1.6.1
numpy==2.3.4
librosa
soundfile
wandb
#
# TorchCodec is highly coupled to torch nightlies; avoid pinning to an older nightly date.
# Let pip pick the newest compatible pre-release from the same cu128 nightly index.
torchcodec
onnx==1.19.1
onnxruntime==1.23.2
onnxscript==0.5.6
torchvision==0.25.0.dev20260122+cu130
torch==2.11.0.dev20260122
torchaudio==2.11.0.dev20260122