feat(pi052): add language-supervised policy

tests/policies/pi0_fast/test_pi0_fast_tokenizer_fit.py

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+#!/usr/bin/env python
+
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from types import SimpleNamespace
+
+import pytest
+
+from lerobot.policies import factory
+from lerobot.policies.pi0_fast.configuration_pi0_fast import PI0FastConfig
+from lerobot.policies.pi052 import fit_fast_tokenizer as fit_module
+
+
+def test_pi0_fast_resolves_dataset_specific_tokenizer(monkeypatch, tmp_path):
+    config = PI0FastConfig(
+        auto_fit_fast_tokenizer=True,
+        action_tokenizer_name="base-tokenizer",
+        fast_tokenizer_cache_dir=str(tmp_path),
+        fast_tokenizer_fit_samples=17,
+        chunk_size=12,
+        n_action_steps=12,
+    )
+    received = {}
+
+    def fake_fit(**kwargs):
+        received.update(kwargs)
+        return "/cache/fitted-tokenizer"
+
+    monkeypatch.setattr(fit_module, "fit_fast_tokenizer", fake_fit)
+
+    assert fit_module.resolve_fast_tokenizer(config, "user/dataset") == "/cache/fitted-tokenizer"
+    assert received == {
+        "dataset_repo_id": "user/dataset",
+        "cache_dir": tmp_path,
+        "base_tokenizer_name": "base-tokenizer",
+        "n_samples": 17,
+        "chunk_size": 12,
+        "dataset_root": None,
+        "dataset_revision": None,
+        "episodes": None,
+        "exclude_episodes": None,
+        "normalization_mode": config.normalization_mapping["ACTION"],
+        "action_stats": None,
+        "use_relative_actions": False,
+        "relative_action_mask": None,
+    }
+
+
+def test_fast_fit_failure_is_not_silently_replaced(monkeypatch, tmp_path):
+    config = PI0FastConfig(auto_fit_fast_tokenizer=True, fast_tokenizer_cache_dir=str(tmp_path))
+    monkeypatch.setattr(
+        fit_module,
+        "fit_fast_tokenizer",
+        lambda **kwargs: (_ for _ in ()).throw(RuntimeError("fit failed")),
+    )
+
+    with pytest.raises(RuntimeError, match="fit failed"):
+        fit_module.resolve_fast_tokenizer(config, "user/dataset")
+
+
+def test_only_global_rank_zero_fits_shared_tokenizer(monkeypatch):
+    monkeypatch.setenv("RANK", "8")
+    monkeypatch.setenv("LOCAL_RANK", "0")
+    assert not fit_module._is_global_leader()
+
+    monkeypatch.setenv("RANK", "0")
+    assert fit_module._is_global_leader()
+
+
+def test_pretrained_pi0_fast_overrides_only_fitted_tokenizer(monkeypatch):
+    config = PI0FastConfig(auto_fit_fast_tokenizer=True)
+    calls = []
+
+    monkeypatch.setattr(
+        fit_module,
+        "resolve_fast_tokenizer",
+        lambda config, dataset_repo_id, *args: "/cache/fitted-tokenizer",
+    )
+
+    def fake_from_pretrained(cls, *args, **kwargs):
+        calls.append(kwargs)
+        return SimpleNamespace(steps=[])
+
+    monkeypatch.setattr(factory.PolicyProcessorPipeline, "from_pretrained", classmethod(fake_from_pretrained))
+
+    factory.make_pre_post_processors(
+        config,
+        pretrained_path="checkpoint",
+        dataset_repo_id="user/dataset",
+    )
+
+    assert calls[0]["overrides"] == {
+        "action_tokenizer_processor": {"action_tokenizer_name": "/cache/fitted-tokenizer"}
+    }