revision

lerobot/common/datasets/abstract.py

@@ -59,8 +59,6 @@ class AbstractDataset(TensorDictReplayBuffer):
         collate_fn: Callable | None = None,
         writer: Writer | None = None,
         transform: "torchrl.envs.Transform" = None,
-        # Don't actually load any data. This is a stand-in solution to get the transforms.
-        dummy: bool = False,
     ):
         assert (
             self.available_datasets is not None
@@ -79,7 +77,7 @@ class AbstractDataset(TensorDictReplayBuffer):
                 f"The version of the dataset ({self.version}) is not enforced when root is provided ({self.root})."
             )
 
-        storage = self._download_or_load_dataset() if not dummy else None
+        storage = self._download_or_load_dataset()
 
         super().__init__(
             storage=storage,

lerobot/common/datasets/aloha.py

@@ -97,7 +97,6 @@ class AlohaDataset(AbstractDataset):
         collate_fn: Callable | None = None,
         writer: Writer | None = None,
         transform: "torchrl.envs.Transform" = None,
-        dummy: bool = False,
     ):
         super().__init__(
             dataset_id,
@@ -111,7 +110,6 @@ class AlohaDataset(AbstractDataset):
             collate_fn=collate_fn,
             writer=writer,
             transform=transform,
-            dummy=dummy,
         )
 
     @property

lerobot/common/datasets/factory.py

@@ -21,12 +21,7 @@ def make_offline_buffer(
     overwrite_batch_size=None,
     overwrite_prefetch=None,
     stats_path=None,
-    # Don't actually load any data. This is a stand-in solution to get the transforms.
-    dummy=False,
 ):
-    if dummy and normalize and stats_path is None:
-        raise ValueError("`stats_path` is required if `dummy` and `normalize` are True.")
-
     if cfg.policy.balanced_sampling:
         assert cfg.online_steps > 0
         batch_size = None
@@ -93,7 +88,6 @@ def make_offline_buffer(
         root=DATA_DIR,
         pin_memory=pin_memory,
         prefetch=prefetch if isinstance(prefetch, int) else None,
-        dummy=dummy,
     )
 
     if cfg.policy.name == "tdmpc":

lerobot/common/datasets/pusht.py

@@ -100,7 +100,6 @@ class PushtDataset(AbstractDataset):
         collate_fn: Callable | None = None,
         writer: Writer | None = None,
         transform: "torchrl.envs.Transform" = None,
-        dummy: bool = False,
     ):
         super().__init__(
             dataset_id,
@@ -114,7 +113,6 @@ class PushtDataset(AbstractDataset):
             collate_fn=collate_fn,
             writer=writer,
             transform=transform,
-            dummy=dummy,
         )
 
     def _download_and_preproc_obsolete(self):

lerobot/common/datasets/simxarm.py

@@ -51,7 +51,6 @@ class SimxarmDataset(AbstractDataset):
         collate_fn: Callable | None = None,
         writer: Writer | None = None,
         transform: "torchrl.envs.Transform" = None,
-        dummy: bool = False,
     ):
         super().__init__(
             dataset_id,
@@ -65,7 +64,6 @@ class SimxarmDataset(AbstractDataset):
             collate_fn=collate_fn,
             writer=writer,
             transform=transform,
-            dummy=dummy,
         )
 
     def _download_and_preproc_obsolete(self):

lerobot/scripts/eval.py

@@ -194,7 +194,7 @@ def eval(cfg: dict, out_dir=None, stats_path=None):
 
     logging.info("Making transforms.")
     # TODO(alexander-soare): Completely decouple datasets from evaluation.
-    offline_buffer = make_offline_buffer(cfg, stats_path=stats_path, dummy=stats_path is not None)
+    offline_buffer = make_offline_buffer(cfg, stats_path=stats_path)
 
     logging.info("Making environment.")
     env = make_env(cfg, transform=offline_buffer.transform)

tests/test_datasets.py

@@ -2,8 +2,9 @@ import pytest
 import torch
 
 from lerobot.common.datasets.factory import make_offline_buffer
+from lerobot.common.utils import init_hydra_config
 
-from .utils import DEVICE, init_config
+from .utils import DEVICE, DEFAULT_CONFIG_PATH
 
 
 @pytest.mark.parametrize(
@@ -18,7 +19,10 @@ from .utils import DEVICE, init_config
     ],
 )
 def test_factory(env_name, dataset_id):
-    cfg = init_config(overrides=[f"env={env_name}", f"env.task={dataset_id}", f"device={DEVICE}"])
+    cfg = init_hydra_config(
+        DEFAULT_CONFIG_PATH,
+        overrides=[f"env={env_name}", f"env.task={dataset_id}", f"device={DEVICE}"]
+    )
     offline_buffer = make_offline_buffer(cfg)
     for key in offline_buffer.image_keys:
         img = offline_buffer[0].get(key)

tests/test_envs.py

@@ -7,8 +7,9 @@ from lerobot.common.datasets.factory import make_offline_buffer
 from lerobot.common.envs.factory import make_env
 from lerobot.common.envs.pusht.env import PushtEnv
 from lerobot.common.envs.simxarm.env import SimxarmEnv
+from lerobot.common.utils import init_hydra_config
 
-from .utils import DEVICE, init_config
+from .utils import DEVICE, DEFAULT_CONFIG_PATH
 
 
 def print_spec_rollout(env):
@@ -89,7 +90,10 @@ def test_pusht(from_pixels, pixels_only):
     ],
 )
 def test_factory(env_name):
-    cfg = init_config(overrides=[f"env={env_name}", f"device={DEVICE}"])
+    cfg = init_hydra_config(
+        DEFAULT_CONFIG_PATH,
+        overrides=[f"env={env_name}", f"device={DEVICE}"],
+    )
 
     offline_buffer = make_offline_buffer(cfg)
 

tests/test_policies.py

@@ -1,4 +1,3 @@
-from omegaconf import open_dict
 import pytest
 from tensordict import TensorDict
 from tensordict.nn import TensorDictModule
@@ -10,8 +9,8 @@ from lerobot.common.policies.factory import make_policy
 from lerobot.common.envs.factory import make_env
 from lerobot.common.datasets.factory import make_offline_buffer
 from lerobot.common.policies.abstract import AbstractPolicy
-
-from .utils import DEVICE, init_config
+from lerobot.common.utils import init_hydra_config
+from .utils import DEVICE, DEFAULT_CONFIG_PATH
 
 @pytest.mark.parametrize(
     "env_name,policy_name,extra_overrides",
@@ -34,7 +33,8 @@ def test_concrete_policy(env_name, policy_name, extra_overrides):
         - Updating the policy.
         - Using the policy to select actions at inference time.
     """
-    cfg = init_config(
+    cfg = init_hydra_config(
+        DEFAULT_CONFIG_PATH,
         overrides=[
             f"env={env_name}",
             f"policy={policy_name}",

tests/utils.py

@@ -1,13 +1,6 @@
 import os
-import hydra
-from hydra import compose, initialize
 
-CONFIG_PATH = "../lerobot/configs"
+# Pass this as the first argument to init_hydra_config.
+DEFAULT_CONFIG_PATH = "lerobot/configs/default.yaml"
 
 DEVICE = os.environ.get('LEROBOT_TESTS_DEVICE', "cuda")
-
-def init_config(config_name="default", overrides=None):
-    hydra.core.global_hydra.GlobalHydra.instance().clear()
-    initialize(config_path=CONFIG_PATH)
-    cfg = compose(config_name=config_name, overrides=overrides)
-    return cfg