fix(build): install CPU-only torch in ml image (drops ~5.6GB CUDA layer)

2026-05-15 21:04:26 -04:00
parent a4c7d44780
commit 681d7777f3
2 changed files with 11 additions and 3 deletions
@@ -2,15 +2,18 @@

 # ML stack — versions current as of 2026-05-14 with Python 3.14 wheel coverage.

-torch>=2.12,<3.0
-
+# torch + torchvision are NOT listed here: they are installed CPU-only from
+# the PyTorch CPU index in Dockerfile.ml. The default PyPI torch wheel bundles
+# the NVIDIA CUDA runtime (a ~5.6GB image layer); this pipeline is CPU-only,
+# so Dockerfile.ml uses the +cpu wheels from
+# https://download.pytorch.org/whl/cpu instead.
+#
 # IMPORTANT: torchvision 0.27 declares requires_python "!=3.14.1,>=3.10" —
 # Python 3.14.1 specifically is excluded due to a known incompatibility.
 # The python-ci runner pulls python:3.14-bookworm (latest patch); if that
 # resolves to 3.14.1 the install will fail. Pin a specific Python patch in
 # the runner image (CI-Runner/CI-python/Dockerfile) if this becomes a
 # blocker. 3.14.0 and 3.14.2+ are fine.
-torchvision>=0.27,<0.28

 transformers>=5.8,<6.0
 onnxruntime>=1.26,<2.0