admin/lerobot
1
0
Fork 0
mirror of https://github.com/huggingface/lerobot.git synced 2026-05-16 09:09:48 +00:00
Code Issues Packages Projects Releases Wiki Activity

chore(deps): allow torch 2.11/2.12 and fix autocast deprecation (#3435)

Browse Source 
* chore(deps): allow torch 2.11/2.12 and fix autocast deprecation

- Bump torch to >=2.7,<2.13 (was <2.11), torchvision to <0.28 (was <0.26),
  and torchcodec to <0.13 (was <0.11) to allow installs against the latest
  stable torch 2.11 and the upcoming 2.12 line.
- Replace removed torch.get_autocast_gpu_dtype() with torch.get_autocast_dtype("cuda")
  in Florence2 and Qwen2.5-VL-MoE FlashAttention paths (the former is removed in 2.11+).
- Refresh uv.lock for the new resolution (torch 2.11.0+cu130, torchvision 0.26.0+cu130,
  torchcodec 0.11.1, full CUDA 13 stack).

Verified locally with `uv sync --locked` from a clean .venv and the lerobot
test suite (pytest -n 8 --dist=loadfile --timeout=300). Failure set is
identical to the pre-bump baseline: 18 pre-existing failures
(test_sac_policy*, test_pi0_rtc*, test_pi05_rtc*, test_replay_buffer*),
0 new, 0 fixed.

AI assistance: this change was authored with Claude Code per AI_POLICY.md.

* fix(policies): use device-agnostic autocast dtype lookup

Pass query_states.device.type to torch.get_autocast_dtype() instead of
hardcoding 'cuda', so the cast matches the active autocast context when
running under CPU/MPS/XPU autocast.

---------

Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
This commit is contained in:
Anthony Shoumikhin
2026-05-10 04:05:35 -07:00
committed by GitHub
parent cb8edf17e6
commit 1f7b03f5f2
4 changed files with 202 additions and 150 deletions
Download Patch File Download Diff File Expand all files Collapse all files
pyproject.toml
+3 -3
View File
@@ -59,8 +59,8 @@ keywords = ["lerobot", "huggingface", "robotics", "machine learning", "artifici
dependencies = [
# Core ML
"torch>=2.7,<2.11.0",
"torchvision>=0.22.0,<0.26.0",
"torch>=2.7,<2.13.0",
"torchvision>=0.22.0,<0.28.0",
"numpy>=2.0.0,<2.3.0", # NOTE: Explicitly listing numpy helps the resolver converge faster. Upper bound imposed by opencv-python-headless.
"opencv-python-headless>=4.9.0,<4.14.0",
"Pillow>=10.0.0,<13.0.0",
@@ -99,7 +99,7 @@ dataset = [
"pandas>=2.0.0,<3.0.0", # NOTE: Transitive dependency of datasets
"pyarrow>=21.0.0,<30.0.0", # NOTE: Transitive dependency of datasets
"lerobot[av-dep]",
"torchcodec>=0.3.0,<0.11.0; sys_platform != 'win32' and (sys_platform != 'linux' or (platform_machine != 'aarch64' and platform_machine != 'arm64' and platform_machine != 'armv7l')) and (sys_platform != 'darwin' or platform_machine != 'x86_64')", # NOTE: Windows support starts at version 0.7 (needs torch==2.8), ffmpeg>=8 support starts at version 0.8.1 (needs torch==2.9), system-wide ffmpeg support starts at version 0.10 (needs torch==2.10).
"torchcodec>=0.3.0,<0.13.0; sys_platform != 'win32' and (sys_platform != 'linux' or (platform_machine != 'aarch64' and platform_machine != 'arm64' and platform_machine != 'armv7l')) and (sys_platform != 'darwin' or platform_machine != 'x86_64')", # NOTE: Windows support starts at version 0.7 (needs torch==2.8), ffmpeg>=8 support starts at version 0.8.1 (needs torch==2.9), system-wide ffmpeg support starts at version 0.10 (needs torch==2.10), 0.11 needs torch==2.11, 0.12 needs torch==2.12.
"jsonlines>=4.0.0,<5.0.0",
]
training = [