[V0.11.0][Core] Restore scheduling logic under default configuration (vllm-project#3967)

This PR reverts the changes introduced in PR vllm-project#2894 Initially, due to
performance issues with the older version of the chunked prefill ops,
the default behavior was to use the Ascend scheduler to disable the
chunked prefill feature. However, with the improvements in the
performance of the new chunked prefill ops, this interception strategy
has been removed. This change also aligns with the community's default
configuration behavior.

No.

CI passed with new added/existing test.

- vLLM version: v0.11.0
- vLLM main:
vllm-project/vllm@83f478b

Signed-off-by: rjg-lyh <1318825571@qq.com>

Author: rjg-lyh

tests/ut/test_platform.py

@@ -754,7 +754,7 @@ def test_aclgraph_enable(self):
             self.platform.check_and_update_config(VllmConfig)
             self.assertTrue(
                 "PIECEWISE compilation enabled on NPU. use_inductor not supported - "
-                "using only ACL Graph mode" in cm.output[1])
+                "using only ACL Graph mode" in cm.output[0])
             self.assertEqual(
                 VllmConfig.compilation_config.level,
                 CompilationLevel.PIECEWISE,

vllm_ascend/platform.py

@@ -129,36 +129,7 @@ def check_and_update_config(cls, vllm_config: VllmConfig) -> None:
         model_config = vllm_config.model_config
         parallel_config = vllm_config.parallel_config
         cache_config = vllm_config.cache_config
-        scheduler_config = vllm_config.scheduler_config
         ascend_scheduler_config = ascend_config.ascend_scheduler_config
-        structured_outputs_config = vllm_config.structured_outputs_config
-
-        if (model_config is not None and not model_config.use_mla
-                and not scheduler_config.async_scheduling
-                and model_config.runner_type != "pooling"):
-            logger.info(
-                "Non-MLA LLMs forcibly disable the chunked prefill feature,"
-                "as the performance of operators supporting this feature "
-                "functionality is currently suboptimal.")
-            if not model_config.is_multimodal_model and \
-                structured_outputs_config.backend == "auto" and \
-                not getattr(scheduler_config, "scheduler_delay_factor", 0) > 0 and \
-                not scheduler_config.send_delta_data and \
-                scheduler_config.policy == "fcfs":
-                ascend_scheduler_config.enabled = True
-                chunked_prefill_enabled_in_ascend_scheduler = getattr(
-                    ascend_scheduler_config, "enable_chunked_prefill", False)
-                if chunked_prefill_enabled_in_ascend_scheduler:
-                    logger.warning(
-                        "Chunked prefill feature is enabled in ascend_scheduler,"
-                        "but note that the operator supporting this feature "
-                        "would lead to performance degradation.")
-                # In this situation, max_num_batched_tokens would have been rewritten.
-                # So we must make sure max_num_batched_tokens is not smaller than max_model_len.
-                if (scheduler_config.max_num_batched_tokens
-                        < scheduler_config.max_model_len
-                        and not chunked_prefill_enabled_in_ascend_scheduler):
-                    scheduler_config.max_num_batched_tokens = scheduler_config.max_model_len
 
         kv_cache_dtype = vllm_config.additional_config.get(
             "kv_cache_dtype", None)
@@ -293,11 +264,20 @@ def check_and_update_config(cls, vllm_config: VllmConfig) -> None:
             if cache_config.block_size is None:
                 cache_config.block_size = 128
 
-            if cache_config.enable_prefix_caching and cache_config.block_size != 128:
+            if cache_config.enable_prefix_caching or \
+                not ascend_scheduler_config.enabled or \
+                getattr(ascend_scheduler_config, "enable_chunked_prefill", False):
                 logger.warning(
-                    "If prefix caching is enabled, block size must be set to 128."
+                    "If chunked prefill or prefix caching is enabled, block size must be set to 128."
                 )
+                origin_block_size = cache_config.block_size
                 cache_config.block_size = 128
+                # TODO(MengqingCao): Remove the model_type check, after resolving the hidden error in get_kv_cache_groups.
+                if model_config and model_config.hf_config.model_type == "qwen3_next":
+                    logger.warning(
+                        "When running qwen3-next model, block_size needs to be restored to its original value."
+                    )
+                    cache_config.block_size = origin_block_size
 
         # Activate custom ops for v1, except on 310P
         if not is_310p():