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

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}, ""),
         (