Merge branch 'main' into fix-gpt-oss-tool-parser-v2

Author: ShaikAbdulHafeez03

tests/engine/test_arg_utils.py

@@ -279,7 +279,7 @@ def test_prefix_cache_default():
     args = parser.parse_args([])
 
     engine_args = EngineArgs.from_cli_args(args=args)
-    assert not engine_args.enable_prefix_caching, "prefix caching defaults to off."
+    assert engine_args.enable_prefix_caching, "prefix caching should default to on."
 
     # with flag to turn it on.
     args = parser.parse_args(["--enable-prefix-caching"])

tests/v1/core/test_scheduler.py

@@ -76,11 +76,11 @@ def test_get_num_unfinished_requests():
 @pytest.mark.parametrize(
     "enable_prefix_caching, prompt_logprobs",
     [
-        (None, None),
+        (False, None),
         (True, 5),
     ],
 )
-def test_schedule(enable_prefix_caching: bool | None, prompt_logprobs: int | None):
+def test_schedule(enable_prefix_caching: bool, prompt_logprobs: int | None):
     """Test scheduling.
     Two cases: default APC/no prompt logprobs; APC=True + prompt logprobs
     """
@@ -582,12 +582,12 @@ def test_check_stop_min_tokens():
 @pytest.mark.parametrize(
     "enable_prefix_caching, prompt_logprobs",
     [
-        (None, None),
+        (False, None),
         (True, 5),
     ],
 )
 def test_schedule_concurrent_batches(
-    enable_prefix_caching: bool | None, prompt_logprobs: int | None
+    enable_prefix_caching: bool, prompt_logprobs: int | None
 ):
     scheduler = create_scheduler(
         max_num_batched_tokens=1024,
@@ -1425,7 +1425,7 @@ def create_scheduler_with_priority(
     model: str = "facebook/opt-125m",
     max_num_seqs: int = 16,
     max_num_batched_tokens: int = 8192,
-    enable_prefix_caching: bool | None = None,
+    enable_prefix_caching: bool = False,
     long_prefill_token_threshold: int = 0,
     disable_chunked_mm_input: bool = False,
     use_kv_connector: bool = False,
@@ -1444,7 +1444,7 @@ def create_scheduler_with_priority(
       max_num_batch_tokens: max num tokens to batch
       enable_prefix_caching: optionally force APC config
                              (True/False) or use default
-                             (None)
+                             (False)
 
     Returns:
       {class}`Scheduler` instance with priority scheduling
@@ -1467,17 +1467,12 @@ def create_scheduler_with_priority(
         seed=42,
     )
     # Cache config, optionally force APC
-    kwargs_cache = (
-        {}
-        if enable_prefix_caching is None
-        else {"enable_prefix_caching": enable_prefix_caching}
-    )
     cache_config = CacheConfig(
         block_size=block_size,
         gpu_memory_utilization=0.9,
         swap_space=0,
         cache_dtype="auto",
-        **kwargs_cache,
+        enable_prefix_caching=enable_prefix_caching,
     )
     kv_transfer_config = (
         KVTransferConfig(

tests/v1/core/utils.py

@@ -42,7 +42,7 @@ def create_scheduler(
     model: str = "facebook/opt-125m",
     max_num_seqs: int = 16,
     max_num_batched_tokens: int = 8192,
-    enable_prefix_caching: bool | None = None,
+    enable_prefix_caching: bool = False,
     long_prefill_token_threshold: int = 0,
     disable_chunked_mm_input: bool = False,
     use_kv_connector: None | bool | MockKVConfig = None,
@@ -63,7 +63,7 @@ def create_scheduler(
       max_num_batch_tokens: max num tokens to batch
       enable_prefix_caching: optionally force APC config
                              (True/False) or use default
-                             (None)
+                             (False)
 
     Returns:
       {class}`Scheduler` instance
@@ -87,17 +87,12 @@ def create_scheduler(
         skip_tokenizer_init=skip_tokenizer_init,
     )
     # Cache config, optionally force APC
-    kwargs_cache = (
-        {}
-        if enable_prefix_caching is None
-        else {"enable_prefix_caching": enable_prefix_caching}
-    )
     cache_config = CacheConfig(
         block_size=block_size,
         gpu_memory_utilization=0.9,
         swap_space=0,
         cache_dtype="auto",
-        **kwargs_cache,
+        enable_prefix_caching=enable_prefix_caching,
     )
     kv_transfer_config = None
     if isinstance(use_kv_connector, MockKVConfig):

tests/v1/kv_offload/test_cpu_offloading.py

@@ -12,10 +12,14 @@
 from vllm import LLM, SamplingParams, TokensPrompt
 from vllm.config import KVEventsConfig, KVTransferConfig
 from vllm.distributed.kv_events import BlockStored, KVEventBatch
+from vllm.platforms import current_platform
 from vllm.utils.system_utils import set_env_var
 
 CPU_BLOCK_SIZES = [48]
-ATTN_BACKENDS = ["FLASH_ATTN", "FLASHINFER"]
+ATTN_BACKENDS = ["FLASH_ATTN"]
+
+if current_platform.is_cuda():
+    ATTN_BACKENDS.append("FLASHINFER")
 
 
 class MockSubscriber:

vllm/config/cache.py

@@ -73,8 +73,8 @@ class CacheConfig:
     sliding_window: int | None = None
     """Sliding window size for the KV cache. This is primarily set in
     `ModelConfig` and that value should be manually duplicated here."""
-    enable_prefix_caching: bool | None = None
-    """Whether to enable prefix caching. Enabled by default for V1."""
+    enable_prefix_caching: bool = True
+    """Whether to enable prefix caching."""
     prefix_caching_hash_algo: PrefixCachingHashAlgo = "sha256"
     """Set the hash algorithm for prefix caching:\n
     - "sha256" uses Pickle for object serialization before hashing.\n

vllm/engine/arg_utils.py

@@ -425,7 +425,7 @@ class EngineArgs:
         ParallelConfig.max_parallel_loading_workers
     )
     block_size: BlockSize | None = CacheConfig.block_size
-    enable_prefix_caching: bool | None = CacheConfig.enable_prefix_caching
+    enable_prefix_caching: bool | None = None
     prefix_caching_hash_algo: PrefixCachingHashAlgo = (
         CacheConfig.prefix_caching_hash_algo
     )
@@ -1975,10 +1975,11 @@ def _set_default_args(
         if self.prefill_context_parallel_size > 1:
             default_chunked_prefill = False
             default_prefix_caching = False
-            logger.warning(
+            logger.warning_once(
                 "--prefill-context-parallel-size > 1 is not compatible with "
                 "chunked prefill and prefix caching now. Chunked prefill "
-                "and prefix caching have been disabled by default."
+                "and prefix caching have been disabled by default.",
+                scope="local",
             )
 
         if self.enable_chunked_prefill is None:
@@ -1988,15 +1989,27 @@ def _set_default_args(
                 "%s chunked prefill by default",
                 "Enabling" if default_chunked_prefill else "Disabling",
             )
+        elif (
+            model_config.runner_type == "generate"
+            and not self.enable_chunked_prefill
+            and default_chunked_prefill
+        ):
+            logger.warning_once(
+                "This model does not officially support disabling chunked prefill. "
+                "Disabling this manually may cause the engine to crash "
+                "or produce incorrect outputs.",
+                scope="local",
+            )
         elif (
             model_config.runner_type == "pooling"
             and self.enable_chunked_prefill
             and not default_chunked_prefill
         ):
-            logger.warning(
+            logger.warning_once(
                 "This model does not officially support chunked prefill. "
                 "Enabling this manually may cause the engine to crash "
                 "or produce incorrect outputs.",
+                scope="local",
             )
 
         if self.enable_prefix_caching is None:
@@ -2011,10 +2024,11 @@ def _set_default_args(
             and self.enable_prefix_caching
             and not default_prefix_caching
         ):
-            logger.warning(
+            logger.warning_once(
                 "This model does not officially support prefix caching. "
                 "Enabling this manually may cause the engine to crash "
                 "or produce incorrect outputs.",
+                scope="local",
             )
 
         world_size = self.pipeline_parallel_size * self.tensor_parallel_size

vllm/v1/core/sched/scheduler.py

@@ -180,7 +180,7 @@ def __init__(
         self.kv_cache_manager = KVCacheManager(
             kv_cache_config=kv_cache_config,
             max_model_len=self.max_model_len,
-            enable_caching=bool(self.cache_config.enable_prefix_caching),
+            enable_caching=self.cache_config.enable_prefix_caching,
             use_eagle=self.use_eagle,
             log_stats=self.log_stats,
             enable_kv_cache_events=self.enable_kv_cache_events,