[Core] Disable the chunked prefill feature in Non-MLA LLMs (#2894)

### What this PR does / why we need it?
This PR enforces the forcible disabling of the chunked prefill feature
in Non-MLA models, as the performance of operators supporting this
functionality is currently suboptimal. Unless the user has enabled
chunked prefill in the ascend_scheduler_config, we would allow this
feature.

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

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

Related: https://github.com/vllm-project/vllm-ascend/pull/2659

- vLLM version: main
- vLLM main:
d21a36f5f9

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

vllm_ascend/platform.py

@@ -128,6 +128,35 @@ class NPUPlatform(Platform):
         model_config = vllm_config.model_config
         parallel_config = vllm_config.parallel_config
         cache_config = vllm_config.cache_config
+        decoding_config = vllm_config.decoding_config
+        scheduler_config = vllm_config.scheduler_config
+        ascend_scheduler_config = ascend_config.ascend_scheduler_config
+
+        if model_config is not None and not model_config.use_mla:
+            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 \
+                decoding_config.backend == "auto" and \
+                not scheduler_config.delay_factor > 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)
         if kv_cache_dtype is not None: