[V0 deprecation]clean up is_v1_supported_oracle (#28116)

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>

tests/v1/test_oracle.py

 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-import os
-
 import pytest
 
-import vllm.envs as envs
-from vllm import LLM
 from vllm.engine.arg_utils import AsyncEngineArgs
 
 MODEL = "meta-llama/Llama-3.2-1B-Instruct"
 
 
-def test_reject_bad_config(monkeypatch):
-    with monkeypatch.context() as m:
-        m.setenv("VLLM_USE_V1", "0")
-
-
-def test_unsupported_configs(monkeypatch):
-    with monkeypatch.context() as m:
-        m.setenv("VLLM_USE_V1", "1")
-
-        with pytest.raises(NotImplementedError):
-            AsyncEngineArgs(
-                model=MODEL,
-                speculative_config={
-                    "model": MODEL,
-                },
-            ).create_engine_config()
-
-
-def test_enable_by_default_fallback(monkeypatch):
-    with monkeypatch.context() as m:
-        if os.getenv("VLLM_USE_V1", None):
-            m.delenv("VLLM_USE_V1")
-
-        # Should default to V1 for supported config.
-        _ = AsyncEngineArgs(
+def test_unsupported_configs():
+    with pytest.raises(NotImplementedError):
+        AsyncEngineArgs(
             model=MODEL,
-            enforce_eager=True,
+            speculative_config={
+                "model": MODEL,
+            },
         ).create_engine_config()
-        assert envs.VLLM_USE_V1
-        m.delenv("VLLM_USE_V1")
-
-
-def test_v1_llm_by_default(monkeypatch):
-    with monkeypatch.context() as m:
-        if os.getenv("VLLM_USE_V1", None):
-            m.delenv("VLLM_USE_V1")
-
-        # Should default to V1 for supported config.
-        llm = LLM(MODEL, enforce_eager=True, enable_lora=True)
-        print(llm.generate("Hello my name is"))
-        assert hasattr(llm.llm_engine, "engine_core")
-        m.delenv("VLLM_USE_V1")

vllm/engine/arg_utils.py

@@ -1290,15 +1290,7 @@ class EngineArgs:
         """
         Create the VllmConfig.
 
-        NOTE: for autoselection of V0 vs V1 engine, we need to
-        create the ModelConfig first, since ModelConfig's attrs
-        (e.g. the model arch) are needed to make the decision.
-
-        This function set VLLM_USE_V1=X if VLLM_USE_V1 is
-        unspecified by the user.
-
-        If VLLM_USE_V1 is specified by the user but the VllmConfig
-        is incompatible, we raise an error.
+        NOTE: If VllmConfig is incompatible, we raise an error.
         """
         current_platform.pre_register_and_update()
 
@@ -1324,22 +1316,7 @@ class EngineArgs:
         self.model = model_config.model
         self.tokenizer = model_config.tokenizer
 
-        # * If VLLM_USE_V1 is unset, we enable V1 for "supported features"
-        #   and fall back to V0 for experimental or unsupported features.
-        # * If VLLM_USE_V1=1, we enable V1 for supported + experimental
-        #   features and raise error for unsupported features.
-        # * If VLLM_USE_V1=0, we disable V1.
-        use_v1 = False
-        try_v1 = envs.VLLM_USE_V1 or not envs.is_set("VLLM_USE_V1")
-        if try_v1 and self._is_v1_supported_oracle(model_config):
-            use_v1 = True
-
-        # If user explicitly set VLLM_USE_V1, sanity check we respect it.
-        if envs.is_set("VLLM_USE_V1"):
-            assert use_v1 == envs.VLLM_USE_V1
-        # Otherwise, set the VLLM_USE_V1 variable globally.
-        else:
-            envs.set_vllm_use_v1(use_v1)
+        self._check_feature_supported(model_config)
 
         # Set default arguments for V1 Engine.
         self._set_default_args(usage_context, model_config)
@@ -1708,17 +1685,10 @@ class EngineArgs:
 
         return config
 
-    def _is_v1_supported_oracle(self, model_config: ModelConfig) -> bool:
-        """Oracle for whether to use V0 or V1 Engine by default."""
-
-        #############################################################
-        # Unsupported Feature Flags on V1.
-
+    def _check_feature_supported(self, model_config: ModelConfig):
+        """Raise an error if the feature is not supported."""
         if self.logits_processor_pattern != EngineArgs.logits_processor_pattern:
-            _raise_or_fallback(
-                feature_name="--logits-processor-pattern", recommend_to_remove=False
-            )
-            return False
+            _raise_unsupported_error(feature_name="--logits-processor-pattern")
 
         # No Concurrent Partial Prefills so far.
         if (
@@ -1726,12 +1696,9 @@ class EngineArgs:
             or self.max_long_partial_prefills
             != SchedulerConfig.max_long_partial_prefills
         ):
-            _raise_or_fallback(
-                feature_name="Concurrent Partial Prefill", recommend_to_remove=False
-            )
-            return False
+            _raise_unsupported_error(feature_name="Concurrent Partial Prefill")
 
-        # V1 supports N-gram, Medusa, and Eagle speculative decoding.
+        # N-gram, Medusa, and Eagle are supported for speculative decoding.
         if self.speculative_config is not None:
             # speculative_config could still be a dict at this point
             if isinstance(self.speculative_config, dict):
@@ -1746,35 +1713,6 @@ class EngineArgs:
                     "such as ngram, medusa, eagle, or mtp."
                 )
 
-        V1_BACKENDS = [
-            "FLASH_ATTN",
-            "PALLAS",
-            "TRITON_ATTN",
-            "TRITON_MLA",
-            "CUTLASS_MLA",
-            "FLASHMLA",
-            "FLASH_ATTN_MLA",
-            "FLASHINFER",
-            "FLASHINFER_MLA",
-            "ROCM_AITER_MLA",
-            "TORCH_SDPA",
-            "FLEX_ATTENTION",
-            "TREE_ATTN",
-            "XFORMERS",
-            "ROCM_ATTN",
-            "ROCM_AITER_UNIFIED_ATTN",
-        ]
-        if (
-            envs.is_set("VLLM_ATTENTION_BACKEND")
-            and envs.VLLM_ATTENTION_BACKEND not in V1_BACKENDS
-        ):
-            name = f"VLLM_ATTENTION_BACKEND={envs.VLLM_ATTENTION_BACKEND}"
-            _raise_or_fallback(feature_name=name, recommend_to_remove=True)
-            return False
-
-        #############################################################
-        # Experimental Features - allow users to opt in.
-
         if self.pipeline_parallel_size > 1:
             supports_pp = getattr(
                 self.distributed_executor_backend, "supports_pp", False
@@ -1790,18 +1728,10 @@ class EngineArgs:
                     "executor or multiprocessing executor or external "
                     "launcher"
                 )
-                _raise_or_fallback(feature_name=name, recommend_to_remove=False)
-                return False
+                _raise_unsupported_error(feature_name=name)
 
         if current_platform.is_cpu() and model_config.get_sliding_window() is not None:
-            _raise_or_fallback(
-                feature_name="sliding window (CPU backend)", recommend_to_remove=False
-            )
-            return False
-
-        #############################################################
-
-        return True
+            _raise_unsupported_error(feature_name="sliding window (CPU backend)")
 
     def _set_default_args(
         self, usage_context: UsageContext, model_config: ModelConfig
@@ -2000,17 +1930,12 @@ class AsyncEngineArgs(EngineArgs):
         return parser
 
 
-def _raise_or_fallback(feature_name: str, recommend_to_remove: bool):
-    if envs.is_set("VLLM_USE_V1") and envs.VLLM_USE_V1:
-        raise NotImplementedError(
-            f"VLLM_USE_V1=1 is not supported with {feature_name}."
-        )
-    msg = f"{feature_name} is not supported by the V1 Engine. "
-    msg += "Falling back to V0. "
-    if recommend_to_remove:
-        msg += f"We recommend to remove {feature_name} from your config "
-        msg += "in favor of the V1 Engine."
-    logger.warning(msg)
+def _raise_unsupported_error(feature_name: str):
+    msg = (
+        f"{feature_name} is not supported. We recommend to "
+        f"remove {feature_name} from your config."
+    )
+    raise NotImplementedError(msg)
 
 
 def human_readable_int(value):