first iteration

tests/test_cli_peft.py

@@ -24,10 +24,6 @@ def lerobot_train(args):
     return run_command(cmd="lerobot-train", module="lerobot_train", args=args)
 
 
-def lerobot_record(args):
-    return run_command(cmd="lerobot-record", module="lerobot_record", args=args)
-
-
 def resolve_model_id_for_peft_training(policy_type):
     """PEFT training needs pretrained models, this finds the pretrained model of a policy type for PEFT training."""
     if policy_type == "smolvla":
@@ -155,81 +151,3 @@ def test_peft_training_params_are_fewer(policy_type, tmp_path):
                 f"--output_dir={output_dir}",
             ]
         )
-
-
-class DummyRobot:
-    name = "dummy"
-    cameras = []
-    action_features = {"foo": 1.0, "bar": 2.0}
-    observation_features = {"obs1": 1.0, "obs2": 2.0}
-    is_connected = True
-
-    def connect(self, *args):
-        pass
-
-    def disconnect(self):
-        pass
-
-
-def dummy_make_robot_from_config(*args, **kwargs):
-    return DummyRobot()
-
-
-@pytest.mark.parametrize("policy_type", ["smolvla"])
-@skip_if_package_missing("peft")
-def test_peft_record_loads_policy(policy_type, tmp_path):
-    """Train a policy with PEFT and attempt to load it with `lerobot-record`."""
-    from peft import PeftModel
-
-    output_dir = tmp_path / f"output_{policy_type}"
-    model_id = resolve_model_id_for_peft_training(policy_type)
-
-    lerobot_train(
-        [
-            f"--policy.path={model_id}",
-            "--policy.push_to_hub=false",
-            "--policy.input_features=null",
-            "--policy.output_features=null",
-            "--peft.method=LORA",
-            "--dataset.repo_id=lerobot/pusht",
-            "--dataset.episodes=[0, 1]",
-            "--steps=1",
-            f"--output_dir={output_dir}",
-        ]
-    )
-
-    policy_dir = output_dir / "checkpoints" / "last" / "pretrained_model"
-    dataset_dir = tmp_path / "eval_pusht"
-    single_task = "move the table"
-    loaded_policy = None
-
-    def dummy_record_loop(*args, **kwargs):
-        nonlocal loaded_policy
-
-        if "dataset" not in kwargs:
-            return
-
-        dataset = kwargs["dataset"]
-        dataset.add_frame({"task": single_task})
-        loaded_policy = kwargs["policy"]
-
-    with (
-        patch("lerobot.scripts.lerobot_record.make_robot_from_config", dummy_make_robot_from_config),
-        # disable record loop since we're only interested in successful loading of the policy.
-        patch("lerobot.scripts.lerobot_record.record_loop", dummy_record_loop),
-        # disable speech output
-        patch("lerobot.utils.utils.say"),
-    ):
-        lerobot_record(
-            [
-                f"--policy.path={policy_dir}",
-                "--robot.type=so101_follower",
-                "--robot.port=/dev/null",
-                "--dataset.repo_id=lerobot/eval_pusht",
-                f'--dataset.single_task="{single_task}"',
-                f"--dataset.root={dataset_dir}",
-                "--dataset.push_to_hub=false",
-            ]
-        )
-
-        assert isinstance(loaded_policy, PeftModel)