chore(dependencies): update uv.lock

fix(datasets): close file handle on VideoDecoder init failure in cache (#3542 )
If VideoDecoder() raises during initialization, the fsspec file handle was leaked since it was opened via __enter__() but never closed on the exception path. Now explicitly closes the handle before re-raising.
2026-05-11 14:49:43 +00:00 · 2026-05-11 04:54:01 +00:00 · 2026-05-10 17:30:37 +02:00 · 2026-05-10 13:05:35 +02:00 · 2026-05-10 12:24:22 +02:00 · 2026-05-10 11:49:31 +02:00
6 changed files with 723 additions and 619 deletions
@@ -19,8 +19,8 @@ on:
  workflow_dispatch:

  # Runs at 02:00
-  schedule:
-    - cron: "0 2 * * *"
+  # schedule:
+  #   - cron: "0 2 * * *"

 env:
  CLOSE_ISSUE_MESSAGE: >
@@ -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 = [
@@ -282,7 +282,11 @@ class VideoDecoderCache:
        with self._lock:
            if video_path not in self._cache:
                file_handle = fsspec.open(video_path).__enter__()
-                decoder = VideoDecoder(file_handle, seek_mode="approximate")
+                try:
+                    decoder = VideoDecoder(file_handle, seek_mode="approximate")
+                except Exception:
+                    file_handle.close()
+                    raise
                self._cache[video_path] = (decoder, file_handle)

            return self._cache[video_path][0]
@@ -939,7 +939,7 @@ class Qwen2_5_VLFlashAttention2(Qwen2_5_VLAttention):
        input_dtype = query_states.dtype
        if input_dtype == torch.float32:
            if torch.is_autocast_enabled():
-                target_dtype = torch.get_autocast_gpu_dtype()
+                target_dtype = torch.get_autocast_dtype(query_states.device.type)
            # Handle the case where the model is quantized
            elif hasattr(self.config, "_pre_quantization_dtype"):
                target_dtype = self.config._pre_quantization_dtype
@@ -985,7 +985,7 @@ class Florence2FlashAttention2(Florence2Attention):
        input_dtype = query_states.dtype
        if input_dtype == torch.float32:
            if torch.is_autocast_enabled():
-                target_dtype = torch.get_autocast_gpu_dtype()
+                target_dtype = torch.get_autocast_dtype(query_states.device.type)
            # Handle the case where the model is quantized
            elif hasattr(self.config, "_pre_quantization_dtype"):
                target_dtype = self.config._pre_quantization_dtype
Author	SHA1	Message	Date
github-actions[bot]	7ae056b14a	chore(dependencies): update uv.lock	2026-05-11 04:54:01 +00:00
Jash Shah	9e83510c99	fix(datasets): close file handle on VideoDecoder init failure in cache (#3542 ) If VideoDecoder() raises during initialization, the fsspec file handle was leaked since it was opened via __enter__() but never closed on the exception path. Now explicitly closes the handle before re-raising.	2026-05-10 17:30:37 +02:00
Anthony Shoumikhin	1f7b03f5f2	chore(deps): allow torch 2.11/2.12 and fix autocast deprecation (#3435 ) * 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>	2026-05-10 13:05:35 +02:00
Steven Palma	cb8edf17e6	chore(dependencies): update uv.lock (#3475 )	2026-05-10 12:24:22 +02:00
Steven Palma	5699f6cbf4	chore(ci): disable auto-stale (#3550 )	2026-05-10 11:49:31 +02:00