fix pi052 FAST training consistency

Align tokenizer fitting and loss reduction with the effective training dataset, and fail early when FAST supervision cannot be produced safely.

Co-authored-by: Cursor <cursoragent@cursor.com>

tests/processor/test_tokenizer_processor.py

@@ -94,6 +94,7 @@ def test_action_tokenizer_config_preserves_token_mapping():
     processor.max_action_tokens = 384
     processor.fast_skip_tokens = 64
     processor.paligemma_tokenizer_name = "custom/paligemma"
+    processor.allow_truncation = False
     processor.action_tokenizer_name = "custom/fast"
     processor.action_tokenizer_input_object = None
 
@@ -102,10 +103,31 @@ def test_action_tokenizer_config_preserves_token_mapping():
         "max_action_tokens": 384,
         "fast_skip_tokens": 64,
         "paligemma_tokenizer_name": "custom/paligemma",
+        "allow_truncation": False,
         "action_tokenizer_name": "custom/fast",
     }
 
 
+def test_action_tokenizer_can_reject_truncated_sequences():
+    processor = object.__new__(ActionTokenizerProcessorStep)
+    processor.max_action_tokens = 4
+    processor.fast_skip_tokens = 128
+    processor.allow_truncation = False
+    processor.action_tokenizer = lambda _actions: [1, 2, 3]
+    processor._paligemma_tokenizer = type(
+        "Tokenizer",
+        (),
+        {
+            "vocab_size": 1000,
+            "bos_token_id": 2,
+            "encode": lambda _self, text, **_kwargs: [10, 11] if text == "Action: " else [12, 1],
+        },
+    )()
+
+    with pytest.raises(ValueError, match="max_action_tokens=4"):
+        processor._tokenize_action(torch.zeros(1, 2, 1))
+
+
 @pytest.fixture
 def mock_tokenizer():
     """Provide a mock tokenizer for testing."""