PyTorch is an open-source machine learning library for Python, based on the
Torch library, used for applications such as natural language processing.
It is primarily developed by Facebook's AI Research lab.
PyTorch provides two high-level features:
* Tensor computation (like NumPy) with strong GPU acceleration
* Deep neural networks built on a tape-based autograd system
It is a popular choice for deep learning research and production due to its
flexibility and ease of use.
NOTE: If this package has multiple flavors (see below), then use one of them instead of the name specified above. NOTE: This is a Python port. Instead of py312-pytorch listed in the above command, you can pick from the names under the Packages section.
===> The following configuration options are available for py312-pytorch-2.14.1:
VULKAN=on: Vulkan GPU support
===> Use 'make config' to modify these settings
You installed PyTorch: an AI toolkit.
## Need env var on amd64 Zen5/Zen6 CPU architectures
Due to the bug in the OpenBLAS CPU arch detection PyTorch will
crash on Zen5/Zen6 CPU architectures.
Reference: https://github.com/OpenMathLib/OpenBLAS/issues/6029
Use the following environment variable to work around this problem:
OPENBLAS_CORETYPE=SKYLAKEX (some other values might work too)
The same problem exists in all software that uses OpenBLAS, not just PyTorch.
## Need env var on aarch64 due to high TLS requirements
When running PyTorch on aarch64 you will need to have this environment
variable set:
LD_STATIC_TLS_EXTRA=4096
It pre-allocates more TLS space when the Python process starts so that
the PyTorch shared libraries will have sufficient TLS space when they are
loaded dynamically.
