PyTorch/XLA supports Python versions 3.9, 3.10, and 3.11. For example, the PyTorch/XLA 2.5 release has wheels available for these versions, but users may encounter issues with Python 3.12 due to compatibility constraints[3][6][7]. To install PyTorch/XLA, especially for TPU environments, it is recommended to use Python versions within this supported range.
For instance, if you are trying to install PyTorch/XLA 2.5, you might need to downgrade to Python 3.11 if you are currently using Python 3.12[3]. The installation command typically involves specifying the Python version compatibility:
bash
pip install torch~=2.5.0 torch_xla[tpu]~=2.5.0 -f https://storage.googleapis.com/libtpu-releases/index.html -f https://storage.googleapis.com/libtpu-wheels/index.html
Ensure that your Python version matches the supported range for successful installation.
Citations:[1] https://github.com/pytorch/xla/releases
[2] https://pytorch.org/xla/release/r2.4/index.html
[3] https://stackoverflow.com/questions/79314991/why-am-i-getting-no-matching-distribution-found-for-torch-xla-2-5-0-when-inst
[4] https://github.com/pytorch/pytorch/blob/main/RELEASE.md
[5] https://pytorch.org/xla/release/1.9/index.html
[6] https://github.com/pytorch/xla/issues/3662
[7] https://github.com/pytorch/xla
[8] https://cloud.google.com/vertex-ai/docs/supported-frameworks-list
[9] https://cloud.google.com/blog/products/ai-machine-learning/whats-new-with-pytorchxla-2-5