From ebd45b659631c5cad72655aed2f53d5edd21a76e Mon Sep 17 00:00:00 2001
From: rjg-lyh <83491835+rjg-lyh@users.noreply.github.com>
Date: Mon, 10 Nov 2025 20:02:23 +0800
Subject: [PATCH] [V0.11.0][Core] Restore scheduling logic under default
 configuration (#4094)

### What this PR does / why we need it?
Cherry-pick #3967 from main branch. This PR reverts the changes
introduced in PR #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.

### Does this PR introduce _any_ user-facing change?
No.

### How was this patch tested?
CI passed with new added/existing test.

Signed-off-by: rjg-lyh <1318825571@qq.com>
---
 tests/ut/test_platform.py |  2 +-
 vllm_ascend/platform.py   | 42 ++++++++++-----------------------------
 2 files changed, 12 insertions(+), 32 deletions(-)

diff --git a/tests/ut/test_platform.py b/tests/ut/test_platform.py
index ffb7018..21e4e94 100644
--- a/tests/ut/test_platform.py
+++ b/tests/ut/test_platform.py
@@ -754,7 +754,7 @@ class TestNPUPlatform(TestBase):
             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,
diff --git a/vllm_ascend/platform.py b/vllm_ascend/platform.py
index 449c3b0..9da4aa6 100644
--- a/vllm_ascend/platform.py
+++ b/vllm_ascend/platform.py
@@ -129,36 +129,7 @@ class NPUPlatform(Platform):
         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 @@ class NPUPlatform(Platform):
             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():