refactor(pi052): load native base checkpoint

tests/policies/pi052/test_pi052_bucketed_ce.py

@@ -36,56 +36,6 @@ def test_shifted_ce_none_retains_distinct_per_sample_losses():
     assert losses[0] < losses[1]
 
 
-def test_checkpoint_resolution_forwards_explicit_hub_options(monkeypatch, tmp_path):
-    import lerobot.policies.pi05.modeling_pi05 as modeling_pi05
-
-    checkpoint = tmp_path / "model.safetensors"
-    checkpoint.touch()
-    calls = []
-
-    def fake_cached_file(model_id, filename, **kwargs):
-        calls.append((model_id, filename, kwargs))
-        return None if filename.endswith("index.json") else str(checkpoint)
-
-    monkeypatch.setattr(modeling_pi05, "cached_file", fake_cached_file)
-    files = modeling_pi05._resolve_weight_files(
-        "org/model",
-        force_download=True,
-        resume_download=True,
-        proxies={"https": "proxy"},
-        token="secret",
-        cache_dir=tmp_path / "cache",
-        local_files_only=True,
-        revision="commit",
-    )
-
-    assert files == [checkpoint]
-    for _model_id, _filename, kwargs in calls:
-        assert kwargs["revision"] == "commit"
-        assert kwargs["cache_dir"] == tmp_path / "cache"
-        assert kwargs["force_download"] is True
-        assert kwargs["resume_download"] is True
-        assert kwargs["proxies"] == {"https": "proxy"}
-        assert kwargs["token"] == "secret"
-        assert kwargs["local_files_only"] is True
-
-
-def test_checkpoint_resolution_rejects_local_directory_without_weights(tmp_path):
-    import lerobot.policies.pi05.modeling_pi05 as modeling_pi05
-
-    with pytest.raises(FileNotFoundError, match="model.safetensors"):
-        modeling_pi05._resolve_weight_files(
-            tmp_path,
-            force_download=False,
-            resume_download=None,
-            proxies=None,
-            token=None,
-            cache_dir=None,
-            local_files_only=False,
-            revision=None,
-        )
-
-
 @pytest.mark.parametrize("z_loss_weight", [0.0, 1e-4])
 @pytest.mark.parametrize("rows,valid_rows", [(24, 9), (48, 25)])
 def test_bucketed_ce_matches_dense_loss_and_gradients(z_loss_weight, rows, valid_rows):