Fix/remove some broken model executor tests (#21224)

Signed-off-by: Rabi Mishra <[email protected]>

Author: rabi

tests/model_executor/test_guided_processors.py

@@ -189,19 +189,6 @@ def test_multiple_guided_options_not_allowed(sample_json_schema, sample_regex):
         GuidedDecodingParams(json=sample_json_schema, grammar="test grammar")
 
 
-def test_guided_decoding_backend_options():
-    """Test backend-specific options"""
-    with pytest.warns(DeprecationWarning):
-        guided_decoding_params = GuidedDecodingParams(
-            backend=
-            "xgrammar:no-fallback,disable-any-whitespace,no-additional-properties"
-        )
-    assert guided_decoding_params.backend == "xgrammar"
-    assert guided_decoding_params.disable_fallback
-    assert guided_decoding_params.disable_any_whitespace
-    assert guided_decoding_params.disable_additional_properties
-
-
 def test_pickle_xgrammar_tokenizer_data():
     try:
         import xgrammar as xgr

tests/model_executor/test_model_load_with_params.py

@@ -49,7 +49,7 @@ def test_model_loading_with_params(vllm_runner):
 
         def check_model(model):
             assert isinstance(model, BertEmbeddingModel)
-            assert isinstance(model._pooler, CLSPool)
+            assert isinstance(model.pooler.pooling, CLSPool)
 
         vllm_model.apply_model(check_model)
 
@@ -87,7 +87,7 @@ def test_roberta_model_loading_with_params(vllm_runner):
 
         def check_model(model):
             assert isinstance(model, RobertaEmbeddingModel)
-            assert isinstance(model._pooler, MeanPool)
+            assert isinstance(model.pooler.pooling, MeanPool)
 
         vllm_model.apply_model(check_model)
 
@@ -114,7 +114,7 @@ def test_facebook_roberta_model_loading_with_params(vllm_runner):
         def check_model(model):
             assert isinstance(model, RobertaEmbeddingModel)
             assert not hasattr(model, "lm_head")
-            assert isinstance(model._pooler, CLSPool)
+            assert isinstance(model.pooler.pooling, CLSPool)
 
         vllm_model.apply_model(check_model)