Merge remote-tracking branch 'origin/main' into feat/streaming-hf-native

pyproject.toml

@@ -216,7 +216,7 @@ robometer = ["lerobot[transformers-dep]", "lerobot[qwen-vl-utils-dep]", "lerobot
 topreward = ["lerobot[transformers-dep]"]
 xvla = ["lerobot[transformers-dep]"]
 eo1 = ["lerobot[transformers-dep]", "lerobot[qwen-vl-utils-dep]"]
-hilserl = ["lerobot[transformers-dep]", "lerobot[dataset]", "gym-hil>=0.1.13,<0.2.0", "lerobot[grpcio-dep]", "lerobot[placo-dep]"]
+hilserl = ["lerobot[transformers-dep]", "lerobot[dataset]", "gym-hil>=0.1.14,<0.2.0", "lerobot[grpcio-dep]", "lerobot[placo-dep]"]
 vla_jepa = ["lerobot[transformers-dep]", "lerobot[diffusers-dep]", "lerobot[qwen-vl-utils-dep]"]
 
 # Features
@@ -231,9 +231,9 @@ video_benchmark = ["scikit-image>=0.23.2,<0.26.0", "pandas>=2.2.2,<2.4.0"]
 
 # Simulation
 # NOTE: Explicitly listing scipy helps flatten the dependecy tree.
-aloha = ["lerobot[dataset]", "gym-aloha>=0.1.2,<0.2.0", "lerobot[scipy-dep]"]
+aloha = ["lerobot[dataset]", "gym-aloha>=0.1.4,<0.2.0", "lerobot[scipy-dep]"]
 pusht = ["lerobot[dataset]", "gym-pusht>=0.1.5,<0.2.0", "pymunk>=6.6.0,<7.0.0"] # TODO: Fix pymunk version in gym-pusht instead
-libero = ["lerobot[dataset]", "lerobot[transformers-dep]", "hf-libero>=0.1.3,<0.2.0; sys_platform == 'linux'", "lerobot[scipy-dep]"]
+libero = ["lerobot[dataset]", "lerobot[transformers-dep]", "hf-libero>=0.1.4,<0.2.0; sys_platform == 'linux'", "lerobot[scipy-dep]"]
 metaworld = ["lerobot[dataset]", "metaworld==3.0.0", "lerobot[scipy-dep]"]
 # NOTE: vlabench is NOT exposed as a `lerobot` extra. Its only distribution
 # is the OpenMOSS/VLABench GitHub repo (package name `VLABench`, no PyPI

src/lerobot/datasets/sampler.py

@@ -30,6 +30,7 @@ class EpisodeAwareSampler:
         drop_n_first_frames: int = 0,
         drop_n_last_frames: int = 0,
         shuffle: bool = False,
+        generator: torch.Generator | None = None,
     ):
         """Sampler that optionally incorporates episode boundary information.
 
@@ -41,6 +42,10 @@ class EpisodeAwareSampler:
             drop_n_first_frames: Number of frames to drop from the start of each episode.
             drop_n_last_frames: Number of frames to drop from the end of each episode.
             shuffle: Whether to shuffle the indices.
+            generator: Generator used for shuffling. Exposing this attribute (even when None) lets
+                       `accelerate` register it as the synchronized RNG in distributed training, so
+                       every rank draws the same permutation and batch shards stay disjoint. When
+                       None, shuffling falls back to the global torch RNG.
         """
         if drop_n_first_frames < 0:
             raise ValueError(f"drop_n_first_frames must be >= 0, got {drop_n_first_frames}")
@@ -73,10 +78,11 @@ class EpisodeAwareSampler:
 
         self.indices = indices
         self.shuffle = shuffle
+        self.generator = generator
 
     def __iter__(self) -> Iterator[int]:
         if self.shuffle:
-            for i in torch.randperm(len(self.indices)):
+            for i in torch.randperm(len(self.indices), generator=self.generator):
                 yield self.indices[i]
         else:
             for i in self.indices:

src/lerobot/scripts/lerobot_train.py

@@ -232,15 +232,18 @@ def train(cfg: TrainPipelineConfig, accelerator: "Accelerator | None" = None):
         torch.backends.cudnn.benchmark = True
     torch.backends.cuda.matmul.allow_tf32 = True
 
-    # Dataset loading synchronization: main process downloads first to avoid race conditions
+    # Dataset loading synchronization: each node's local main process downloads first to avoid
+    # race conditions (the global main process only exists on node 0, so gating on it would let
+    # all ranks of the other nodes download and build the Arrow cache concurrently).
+    if accelerator.is_local_main_process:
         if is_main_process:
             logging.info("Creating dataset")
         dataset = make_dataset(cfg)
 
     accelerator.wait_for_everyone()
 
-    # Now all other processes can safely load the dataset
+    # Now all other processes can safely load the dataset from the local cache
-    if not is_main_process:
+    if not accelerator.is_local_main_process:
         dataset = make_dataset(cfg)
 
     # Create environment used for evaluating checkpoints during training on simulation data.
@@ -386,12 +389,19 @@ def train(cfg: TrainPipelineConfig, accelerator: "Accelerator | None" = None):
     # create dataloader for offline training
     if hasattr(active_cfg, "drop_n_last_frames"):
         shuffle = False
+        # A dedicated generator (rather than the global torch RNG) lets accelerator.prepare
+        # synchronize the shuffle permutation across ranks, keeping batch shards disjoint even
+        # when ranks consume the global RNG asymmetrically (e.g. eval on the main process only).
+        sampler_generator = torch.Generator()
+        if cfg.seed is not None:
+            sampler_generator.manual_seed(cfg.seed)
         sampler = EpisodeAwareSampler(
             dataset.meta.episodes["dataset_from_index"],
             dataset.meta.episodes["dataset_to_index"],
             episode_indices_to_use=dataset.episodes,
             drop_n_last_frames=active_cfg.drop_n_last_frames,
             shuffle=True,
+            generator=sampler_generator,
         )
     else:
         shuffle = True

tests/datasets/test_sampler.py

@@ -114,6 +114,30 @@ def test_shuffle():
     assert set(sampler) == {0, 1, 2, 3, 4, 5}
 
 
+def test_shuffle_with_generator_is_deterministic():
+    # Two samplers shuffling with same-seed generators must yield identical permutations.
+    # This is what keeps batch shards disjoint across ranks in distributed training, where
+    # accelerate synchronizes the sampler's generator state instead of the global torch RNG.
+    sampler_a = EpisodeAwareSampler([0], [6], shuffle=True, generator=torch.Generator().manual_seed(42))
+    sampler_b = EpisodeAwareSampler([0], [6], shuffle=True, generator=torch.Generator().manual_seed(42))
+    assert list(sampler_a) == list(sampler_b)
+
+    # Desyncing the global RNG must not affect the permutation.
+    sampler_c = EpisodeAwareSampler([0], [6], shuffle=True, generator=torch.Generator().manual_seed(42))
+    order_before = list(sampler_c)
+    sampler_c.generator.manual_seed(42)
+    torch.randperm(1000)  # consume global RNG, as rank-asymmetric code (e.g. eval) would
+    assert list(sampler_c) == order_before
+
+
+def test_generator_attribute_defaults_to_none():
+    # accelerate detects synchronizable samplers via `hasattr(sampler, "generator")`,
+    # so the attribute must exist even when no generator is passed.
+    sampler = EpisodeAwareSampler([0], [6], shuffle=True)
+    assert sampler.generator is None
+    assert set(sampler) == {0, 1, 2, 3, 4, 5}
+
+
 def test_negative_drop_first_frames_raises():
     with pytest.raises(ValueError, match="drop_n_first_frames must be >= 0"):
         EpisodeAwareSampler([0], [10], drop_n_first_frames=-1)

uv.lock

@@ -1764,7 +1764,7 @@ wheels = [
 
 [[package]]
 name = "gym-aloha"
-version = "0.1.3"
+version = "0.1.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "dm-control" },
@@ -1772,14 +1772,14 @@ dependencies = [
     { name = "imageio", extra = ["ffmpeg"] },
     { name = "mujoco" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/b5/5e/4bb7204730501c2f645e0532a2df4339206948b2882f77cbf0eaf75bc5fe/gym_aloha-0.1.3.tar.gz", hash = "sha256:b794b246a2e6da6ce5f75e152f553fbd4412704bc217fe6311d0ede3bb72a75e", size = 443468, upload-time = "2025-10-09T14:02:35.024Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/4a/c5/a5b8bdbddfcadec0b52b50e6d1a70325e09e6b594e5f55929d67d9122e2c/gym_aloha-0.1.4.tar.gz", hash = "sha256:0dc4e645045aeb3e74e3c320872d28df6dc93a8751d6ab2f266a2ca11323131f", size = 443466, upload-time = "2026-06-10T09:13:25.525Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/57/6c/10da397177c48ce360efa66ec21b10b10ef5fa2766256fcd8d7d9b5fa6fc/gym_aloha-0.1.3-py3-none-any.whl", hash = "sha256:a94e5747e71307897ded7ae17ed97fab05e814dcb714a16d320f110444f9d0c3", size = 447908, upload-time = "2025-10-09T14:02:33.253Z" },
+    { url = "https://files.pythonhosted.org/packages/35/e3/3afd0e517a503aabe255bf65f5136490acb79c43189e8d56a3aa63081a10/gym_aloha-0.1.4-py3-none-any.whl", hash = "sha256:d9044290fbccddf0be4246b5287cf0eb6b9ddee545a3d222ce8d78c93ce7125e", size = 447908, upload-time = "2026-06-10T09:13:23.868Z" },
 ]
 
 [[package]]
 name = "gym-hil"
-version = "0.1.13"
+version = "0.1.14"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "gymnasium" },
@@ -1789,9 +1789,9 @@ dependencies = [
     { name = "pygame" },
     { name = "pynput" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/f3/41/e89c87b3c66fb2f8ab5818bff4aa552977911eabaee7c12a8a336dcc406f/gym_hil-0.1.13.tar.gz", hash = "sha256:b9eab7a0acc811f181254e3ad72865830fdbb292c236895f374135d3d62f1b27", size = 5668001, upload-time = "2025-10-21T09:57:24.01Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/0c/64/b5cfe59d6a69d20497218f01ad2bdaa2a5a72b850bdb1a445d804ecc9948/gym_hil-0.1.14.tar.gz", hash = "sha256:aeee688dcb3ec72e7bcbe604df4a3f990cce49c8a2da469dd67c3a4eeb4c6bbb", size = 5667991, upload-time = "2026-06-10T09:16:38.98Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/c2/8d/9e3ab53f9aac7bd542f339efd0a9283fa76e034474987e0705379274dfcf/gym_hil-0.1.13-py3-none-any.whl", hash = "sha256:b6444fc43ce1a68ce403df14f99100d9c903ae05d822959e9cd0b76a50b93320", size = 5750805, upload-time = "2025-10-21T09:57:22.068Z" },
+    { url = "https://files.pythonhosted.org/packages/72/97/a7a9c3886306a89046ba5c989bc8b79008e7ec973228bad1fa20d7a94bba/gym_hil-0.1.14-py3-none-any.whl", hash = "sha256:9a2799d47a4561e0b0bb8d37fb3d84934657240be328d13991ea06758726533d", size = 5750805, upload-time = "2026-06-10T09:16:36.827Z" },
 ]
 
 [[package]]
@@ -1881,7 +1881,7 @@ sdist = { url = "https://files.pythonhosted.org/packages/e6/3e/ffad88145b342d5a9
 
 [[package]]
 name = "hf-libero"
-version = "0.1.3"
+version = "0.1.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "bddl", marker = "sys_platform == 'linux'" },
@@ -1902,7 +1902,10 @@ dependencies = [
     { name = "transformers", marker = "sys_platform == 'linux'" },
     { name = "wandb", marker = "sys_platform == 'linux'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/7e/ca/7f1c90aedcd067d608681cf03469ae548990ba0806f68a67927dcc801f04/hf_libero-0.1.3.tar.gz", hash = "sha256:0d6b9a215a658db86f66c03d063d6d877d2e9f96d2d326cfa9f43ba4da4a6d5a", size = 2960521, upload-time = "2025-11-03T17:58:00.003Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/af/aa/4e9eb8715e0bff9cb6553db563a35d253393097d446f82bd53575e8b253d/hf_libero-0.1.4.tar.gz", hash = "sha256:c058d67ad5a2b589529c14d614282ef4cca3a7763dafa134f58a6c9039657e34", size = 2961319, upload-time = "2026-06-10T09:56:13.994Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/2a/79/c286b894c051988d062241682834df915c945bcf51009ffdffbe5ecf69bf/hf_libero-0.1.4-py3-none-any.whl", hash = "sha256:207f76e2f28bff30f78132223d8592fe8f64b1f8fd90ce7024948ada0d7e2c27", size = 3169084, upload-time = "2026-06-10T09:56:12.441Z" },
+]
 
 [[package]]
 name = "hf-xet"
@@ -3090,12 +3093,12 @@ requires-dist = [
     { name = "flash-attn", marker = "sys_platform != 'darwin' and extra == 'groot'", specifier = ">=2.5.9,<3.0.0" },
     { name = "grpcio", marker = "extra == 'grpcio-dep'", specifier = "==1.73.1" },
     { name = "grpcio-tools", marker = "extra == 'dev'", specifier = "==1.73.1" },
-    { name = "gym-aloha", marker = "extra == 'aloha'", specifier = ">=0.1.2,<0.2.0" },
+    { name = "gym-aloha", marker = "extra == 'aloha'", specifier = ">=0.1.4,<0.2.0" },
-    { name = "gym-hil", marker = "extra == 'hilserl'", specifier = ">=0.1.13,<0.2.0" },
+    { name = "gym-hil", marker = "extra == 'hilserl'", specifier = ">=0.1.14,<0.2.0" },
     { name = "gym-pusht", marker = "extra == 'pusht'", specifier = ">=0.1.5,<0.2.0" },
     { name = "gymnasium", specifier = ">=1.1.1,<2.0.0" },
     { name = "hebi-py", marker = "extra == 'phone'", specifier = ">=2.8.0,<2.12.0" },
-    { name = "hf-libero", marker = "sys_platform == 'linux' and extra == 'libero'", specifier = ">=0.1.3,<0.2.0" },
+    { name = "hf-libero", marker = "sys_platform == 'linux' and extra == 'libero'", specifier = ">=0.1.4,<0.2.0" },
     { name = "hidapi", marker = "extra == 'gamepad'", specifier = ">=0.14.0,<0.15.0" },
     { name = "huggingface-hub", specifier = ">=1.0.0,<2.0.0" },
     { name = "ipykernel", marker = "extra == 'notebook'", specifier = ">=6.0.0,<7.0.0" },