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refactor(factory): remove PI052 processor overrides
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@@ -14,8 +14,9 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from types import SimpleNamespace
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from lerobot.policies import factory
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from lerobot.policies.pi0_fast import processor_pi0_fast
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from lerobot.policies.pi0_fast.configuration_pi0_fast import PI0FastConfig
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from lerobot.policies.pi052 import fit_fast_tokenizer as fit_module
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@@ -47,17 +48,28 @@ def test_pi0_fast_resolves_dataset_specific_tokenizer(monkeypatch, tmp_path):
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}
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def test_pretrained_pi0_fast_rebuilds_processor_only_during_dataset_fit(monkeypatch):
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def test_pretrained_pi0_fast_overrides_only_fitted_tokenizer(monkeypatch):
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config = PI0FastConfig(auto_fit_fast_tokenizer=True)
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expected = (object(), object())
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calls = []
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monkeypatch.setattr(processor_pi0_fast, "make_pi0_fast_pre_post_processors", lambda **_: expected)
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assert (
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factory.make_pre_post_processors(
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config,
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pretrained_path="checkpoint",
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dataset_repo_id="user/dataset",
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)
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== expected
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monkeypatch.setattr(
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fit_module,
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"resolve_fast_tokenizer",
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lambda config, dataset_repo_id: "/cache/fitted-tokenizer",
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)
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def fake_from_pretrained(cls, *args, **kwargs):
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calls.append(kwargs)
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return SimpleNamespace(steps=[])
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monkeypatch.setattr(factory.PolicyProcessorPipeline, "from_pretrained", classmethod(fake_from_pretrained))
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factory.make_pre_post_processors(
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config,
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pretrained_path="checkpoint",
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dataset_repo_id="user/dataset",
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)
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assert calls[0]["overrides"] == {
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"action_tokenizer_processor": {"action_tokenizer_name": "/cache/fitted-tokenizer"}
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}
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