feat(dependencies): minimal default tag install (#3362)

tests/policies/groot/test_groot_lerobot.py

@@ -31,7 +31,7 @@ from lerobot.policies.groot.processor_groot import make_groot_pre_post_processor
 from lerobot.processor import PolicyProcessorPipeline
 from lerobot.types import PolicyAction
 from lerobot.utils.device_utils import auto_select_torch_device
-from tests.utils import require_cuda  # noqa: E402
+from tests.utils import require_cuda
 
 pytest.importorskip("transformers")
 

tests/policies/hilserl/test_modeling_classifier.py

@@ -21,7 +21,7 @@ from lerobot.configs.types import FeatureType, NormalizationMode, PolicyFeature
 from lerobot.policies.sac.reward_model.configuration_classifier import RewardClassifierConfig
 from lerobot.policies.sac.reward_model.modeling_classifier import ClassifierOutput
 from lerobot.utils.constants import OBS_IMAGE, REWARD
-from tests.utils import require_package
+from tests.utils import skip_if_package_missing
 
 
 def test_classifier_output():
@@ -37,7 +37,7 @@ def test_classifier_output():
     )
 
 
-@require_package("transformers")
+@skip_if_package_missing("transformers")
 @pytest.mark.skip(
     reason="helper2424/resnet10 needs to be updated to work with the latest version of transformers"
 )
@@ -81,7 +81,7 @@ def test_binary_classifier_with_default_params():
     assert not torch.isnan(output.hidden_states).any(), "Tensor contains NaN values"
 
 
-@require_package("transformers")
+@skip_if_package_missing("transformers")
 @pytest.mark.skip(
     reason="helper2424/resnet10 needs to be updated to work with the latest version of transformers"
 )
@@ -123,7 +123,7 @@ def test_multiclass_classifier():
     assert not torch.isnan(output.hidden_states).any(), "Tensor contains NaN values"
 
 
-@require_package("transformers")
+@skip_if_package_missing("transformers")
 @pytest.mark.skip(
     reason="helper2424/resnet10 needs to be updated to work with the latest version of transformers"
 )
@@ -138,7 +138,7 @@ def test_default_device():
         assert p.device == torch.device("cpu")
 
 
-@require_package("transformers")
+@skip_if_package_missing("transformers")
 @pytest.mark.skip(
     reason="helper2424/resnet10 needs to be updated to work with the latest version of transformers"
 )

tests/policies/smolvla/test_smolvla_rtc.py

@@ -19,15 +19,15 @@
 import pytest
 import torch
 
-from lerobot.configs.types import FeatureType, PolicyFeature, RTCAttentionSchedule  # noqa: E402
-from lerobot.policies.factory import make_pre_post_processors  # noqa: E402
-from lerobot.policies.rtc.configuration_rtc import RTCConfig  # noqa: E402
+from lerobot.configs.types import FeatureType, PolicyFeature, RTCAttentionSchedule
+from lerobot.policies.factory import make_pre_post_processors
+from lerobot.policies.rtc.configuration_rtc import RTCConfig
 from lerobot.policies.smolvla.configuration_smolvla import SmolVLAConfig  # noqa: F401
-from lerobot.utils.random_utils import set_seed  # noqa: E402
-from tests.utils import require_cuda, require_package  # noqa: E402
+from lerobot.utils.random_utils import set_seed
+from tests.utils import require_cuda, skip_if_package_missing
 
 
-@require_package("transformers")
+@skip_if_package_missing("transformers")
 @require_cuda
 def test_smolvla_rtc_initialization():
     from lerobot.policies.smolvla.modeling_smolvla import SmolVLAPolicy  # noqa: F401
@@ -65,7 +65,7 @@ def test_smolvla_rtc_initialization():
     print("✓ SmolVLA RTC initialization: Test passed")
 
 
-@require_package("transformers")
+@skip_if_package_missing("transformers")
 @require_cuda
 def test_smolvla_rtc_initialization_without_rtc_config():
     from lerobot.policies.smolvla.modeling_smolvla import SmolVLAPolicy  # noqa: F401
@@ -87,7 +87,7 @@ def test_smolvla_rtc_initialization_without_rtc_config():
     print("✓ SmolVLA RTC initialization without RTC config: Test passed")
 
 
-@require_package("transformers")
+@skip_if_package_missing("transformers")
 @require_cuda
 @pytest.mark.skipif(True, reason="Requires pretrained SmolVLA model weights")
 def test_smolvla_rtc_inference_with_prev_chunk():
@@ -170,7 +170,7 @@ def test_smolvla_rtc_inference_with_prev_chunk():
     print("✓ SmolVLA RTC inference with prev_chunk: Test passed")
 
 
-@require_package("transformers")
+@skip_if_package_missing("transformers")
 @require_cuda
 @pytest.mark.skipif(True, reason="Requires pretrained SmolVLA model weights")
 def test_smolvla_rtc_inference_without_prev_chunk():
@@ -244,7 +244,7 @@ def test_smolvla_rtc_inference_without_prev_chunk():
     print("✓ SmolVLA RTC inference without prev_chunk: Test passed")
 
 
-@require_package("transformers")
+@skip_if_package_missing("transformers")
 @require_cuda
 @pytest.mark.skipif(True, reason="Requires pretrained SmolVLA model weights")
 def test_smolvla_rtc_validation_rules():

tests/policies/test_policies.py

@@ -20,16 +20,16 @@ from pathlib import Path
 import einops
 import pytest
 import torch
+
+pytest.importorskip("datasets", reason="datasets is required (install lerobot[dataset])")
+
 from packaging import version
 from safetensors.torch import load_file
 
-from lerobot import available_policies
 from lerobot.configs.default import DatasetConfig
 from lerobot.configs.train import TrainPipelineConfig
 from lerobot.configs.types import FeatureType, PolicyFeature
-from lerobot.datasets.factory import make_dataset
-from lerobot.datasets.feature_utils import dataset_to_policy_features
-from lerobot.datasets.utils import cycle
+from lerobot.datasets import make_dataset
 from lerobot.envs.factory import make_env, make_env_config
 from lerobot.envs.utils import close_envs, preprocess_observation
 from lerobot.optim.factory import make_optimizer_and_scheduler
@@ -45,10 +45,23 @@ from lerobot.policies.pretrained import PreTrainedPolicy
 from lerobot.policies.vqbet.configuration_vqbet import VQBeTConfig
 from lerobot.policies.vqbet.modeling_vqbet import VQBeTHead
 from lerobot.utils.constants import ACTION, OBS_IMAGES, OBS_STATE
+from lerobot.utils.feature_utils import dataset_to_policy_features
+from lerobot.utils.import_utils import is_package_available
 from lerobot.utils.random_utils import seeded_context
+from lerobot.utils.utils import cycle
 from tests.artifacts.policies.save_policy_to_safetensors import get_policy_stats
 from tests.utils import DEVICE, require_cpu, require_env, require_x86_64_kernel
 
+# Policies that require optional heavy dependencies to instantiate
+_POLICY_REQUIRED_PACKAGES: dict[str, tuple[str, ...]] = {
+    "diffusion": ("diffusers",),
+}
+
+_ALL_POLICIES = ["act", "diffusion", "tdmpc", "vqbet"]
+AVAILABLE_POLICIES = [
+    p for p in _ALL_POLICIES if all(is_package_available(pkg) for pkg in _POLICY_REQUIRED_PACKAGES.get(p, ()))
+]
+
 
 @pytest.fixture
 def dummy_dataset_metadata(lerobot_dataset_metadata_factory, info_factory, tmp_path):
@@ -84,7 +97,7 @@ def dummy_dataset_metadata(lerobot_dataset_metadata_factory, info_factory, tmp_p
     return ds_meta
 
 
-@pytest.mark.parametrize("policy_name", available_policies)
+@pytest.mark.parametrize("policy_name", AVAILABLE_POLICIES)
 def test_get_policy_and_config_classes(policy_name: str):
     """Check that the correct policy and config classes are returned."""
     policy_cls = get_policy_class(policy_name)
@@ -255,7 +268,7 @@ def test_act_backbone_lr():
     assert len(optimizer.param_groups[1]["params"]) == 20
 
 
-@pytest.mark.parametrize("policy_name", available_policies)
+@pytest.mark.parametrize("policy_name", AVAILABLE_POLICIES)
 def test_policy_defaults(dummy_dataset_metadata, policy_name: str):
     """Check that the policy can be instantiated with defaults."""
     policy_cls = get_policy_class(policy_name)
@@ -268,7 +281,7 @@ def test_policy_defaults(dummy_dataset_metadata, policy_name: str):
     policy_cls(policy_cfg)
 
 
-@pytest.mark.parametrize("policy_name", available_policies)
+@pytest.mark.parametrize("policy_name", AVAILABLE_POLICIES)
 def test_save_and_load_pretrained(dummy_dataset_metadata, tmp_path, policy_name: str):
     policy_cls = get_policy_class(policy_name)
     policy_cfg = make_policy_config(policy_name)
@@ -343,7 +356,7 @@ def test_multikey_construction(multikey: bool):
         # to normalize the image at all. In our current codebase we dont normalize at all. But there is still a minor difference
         # that fails the test. However, by testing to normalize the image with 0.5 0.5 in the current codebase, the test pass.
         # Thus, we deactivate this test for now.
-        (
+        pytest.param(
             "lerobot/pusht",
             "diffusion",
             {
@@ -352,6 +365,7 @@ def test_multikey_construction(multikey: bool):
                 "down_dims": [128, 256, 512],
             },
             "",
+            marks=pytest.mark.skipif(not is_package_available("diffusers"), reason="diffusers not installed"),
         ),
         ("lerobot/aloha_sim_insertion_human", "act", {"n_action_steps": 10}, ""),
         (

tests/policies/test_relative_actions.py

@@ -10,6 +10,8 @@ import numpy as np
 import pytest
 import torch
 
+pytest.importorskip("datasets", reason="datasets is required (install lerobot[dataset])")
+
 from lerobot.configs.types import FeatureType, NormalizationMode, PolicyFeature
 from lerobot.datasets.compute_stats import get_feature_stats
 from lerobot.datasets.lerobot_dataset import LeRobotDataset