[Misc] Drop Prefetch MLP Env (#7357)

### What this PR does / why we need it?
remove deprecated environment variables related to MLP prefetching

### Does this PR introduce _any_ user-facing change?
yes, the deprecated env vars can not be used then.

- vLLM version: v0.17.0
- vLLM main:
4034c3d32e

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

docs/source/tutorials/features/suffix_speculative_decoding.md

@@ -80,8 +80,6 @@ export ASCEND_RT_VISIBLE_DEVICES=0,1,2,3
 export TASK_QUEUE_ENABLE=1
 # Enable the AIVector core to directly schedule ROCE communication.
 export HCCL_OP_EXPANSION_MODE="AIV"
-# Enable MLP prefetch for better performance.
-export VLLM_ASCEND_ENABLE_PREFETCH_MLP=1
 # Enable FlashComm_v1 optimization when tensor parallel is enabled.
 export VLLM_ASCEND_ENABLE_FLASHCOMM1=1
 
@@ -94,7 +92,7 @@ vllm serve /data/Qwen3-32B \
   --max-num-batched-tokens 40960 \
   --speculative-config '{"method": "suffix", "num_speculative_tokens": 3}' \
   --gpu-memory-utilization 0.9 \
-  --additional-config '{"pa_shape_list":[48,64,72,80]}' \
+  --additional-config '{"pa_shape_list":[48,64,72,80], "weight_prefetch_config":{"enable":true}}' \
   --port 8011
 ```
 

vllm_ascend/ascend_config.py

@@ -14,7 +14,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import os
-import warnings
 from typing import TYPE_CHECKING
 
 from vllm.logger import logger
@@ -48,9 +47,11 @@ class AscendConfig:
         eplb_config = additional_config.get("eplb_config", {})
         self.eplb_config = EplbConfig(eplb_config)
 
+        weight_prefetch_config = additional_config.get("weight_prefetch_config", {})
+        self.weight_prefetch_config = WeightPrefetchConfig(weight_prefetch_config)
+
         # Dump / PrecisionDebugger configuration
         self.dump_config_path = additional_config.get("dump_config_path", None)
-        self._construct_weight_prefetch_config(additional_config)
         self.layer_sharding = additional_config.get("layer_sharding", None)
         if self.layer_sharding:
             logger.info_once(
@@ -158,29 +159,6 @@ class AscendConfig:
             and get_ascend_device_type() != AscendDeviceType.A5
         )
 
-    def _construct_weight_prefetch_config(self, additional_config):
-        weight_prefetch_config = additional_config.get("weight_prefetch_config", {})
-        self.weight_prefetch_config = WeightPrefetchConfig(weight_prefetch_config)
-        # Deprecated env var handling for backward compatibility
-        if os.getenv("VLLM_ASCEND_ENABLE_PREFETCH_MLP", "0") == "1":
-            MAX_PREFETCH_WEIGHT_SIZE: int = 18 * 1024 * 1024
-            gate_up_prefetch_size = int(os.getenv("VLLM_ASCEND_MLP_GATE_UP_PREFETCH_SIZE", MAX_PREFETCH_WEIGHT_SIZE))
-            down_prefetch_size = int(os.getenv("VLLM_ASCEND_MLP_DOWN_PREFETCH_SIZE", MAX_PREFETCH_WEIGHT_SIZE))
-            self.weight_prefetch_config.set_mlp_pre_version_compatibale_config(
-                gate_up_prefetch_size, down_prefetch_size
-            )
-            logger.info_once(
-                f"MLP weight prefetch enabled from env variable VLLM_ASCEND_ENABLE_PREFETCH_MLP."
-                f"gate_up_prefetch_size={gate_up_prefetch_size}, "
-                f"down_prefetch_size={down_prefetch_size}."
-            )
-            warnings.warn(
-                "VLLM_ASCEND_ENABLE_PREFETCH_MLP is deprecated and will be removed in a v0.16.0 version. "
-                "Please use weight_prefetch_config in additional-config for now instead.",
-                DeprecationWarning,
-                stacklevel=2,
-            )
-
     @staticmethod
     def _get_compile_ranges(compilation_config):
         from vllm_ascend.utils import vllm_version_is
@@ -380,28 +358,19 @@ class WeightPrefetchConfig:
     Configuration Object for weight_prefetch_config from additional_config
     """
 
-    mlp_pre_version_compatibale_config: dict = {}
-
     prefetch_ratio: dict = {
         "attn": {
             "qkv": 1.0,
             "o": 1.0,
         },
         "moe": {"gate_up": 0.8},
-        "mlp": {"gate_up": 1, "down": 1.0},
+        "mlp": {"gate_up": 1.0, "down": 1.0},
     }
 
     def __init__(self, weight_prefetch_config: dict):
         self.enabled = weight_prefetch_config.get("enabled", False)
         self.prefetch_ratio = weight_prefetch_config.get("prefetch_ratio", self.prefetch_ratio)
 
-    def set_mlp_pre_version_compatibale_config(self, gate_up_prefetch_size: int, down_prefetch_size: int):
-        config = {
-            "gate_up": gate_up_prefetch_size,
-            "down": down_prefetch_size,
-        }
-        self.mlp_pre_version_compatibale_config = config
-
 
 class EplbConfig:
     """

vllm_ascend/envs.py

@@ -77,16 +77,6 @@ env_variables: dict[str, Callable[[], Any]] = {
     # For a detailed introduction to the parameters and the differences and applicable scenarios
     # between this feature and FLASHCOMM1, please refer to the feature guide in the documentation.
     "VLLM_ASCEND_FLASHCOMM2_PARALLEL_SIZE": lambda: int(os.getenv("VLLM_ASCEND_FLASHCOMM2_PARALLEL_SIZE", 0)),
-    # Whether to enable MLP weight prefetch, only used in small concurrency.
-    "VLLM_ASCEND_ENABLE_PREFETCH_MLP": lambda: bool(int(os.getenv("VLLM_ASCEND_ENABLE_PREFETCH_MLP", "0"))),
-    # buffer size for gate up prefetch
-    "VLLM_ASCEND_MLP_GATE_UP_PREFETCH_SIZE": lambda: int(
-        os.getenv("VLLM_ASCEND_MLP_GATE_UP_PREFETCH_SIZE", 18 * 1024 * 1024)
-    ),
-    # buffer size for down proj prefetch
-    "VLLM_ASCEND_MLP_DOWN_PREFETCH_SIZE": lambda: int(
-        os.getenv("VLLM_ASCEND_MLP_DOWN_PREFETCH_SIZE", 18 * 1024 * 1024)
-    ),
     # Whether to enable msMonitor tool to monitor the performance of vllm-ascend.
     "MSMONITOR_USE_DAEMON": lambda: bool(int(os.getenv("MSMONITOR_USE_DAEMON", "0"))),
     # Whether to enable MLAPO optimization for DeepSeek W8A8 series models.

vllm_ascend/ops/weight_prefetch.py

@@ -43,9 +43,6 @@ class WeightPrefetchMethod:
     MLP_GATE_UP: str = "gate_up"
     MLP_DOWN: str = "down"
 
-    # backward compatibility: delete in future versions
-    mlp_pre_version_compatibale_config: dict = {}
-
     def __init__(self, weight_prefetch_config: WeightPrefetchConfig) -> None:
         self.is_moe = is_moe_model(get_current_vllm_config())
         self.mla_sfa_prefetch_enable = weight_prefetch_config.enabled
@@ -70,7 +67,6 @@ class WeightPrefetchMethod:
             enable=weight_prefetch_config.enabled and not self.is_moe,
             prefetch_ratio=weight_prefetch_config.prefetch_ratio.get("mlp", {}) or {"gate_up": 1.0, "down": 1.0},
         )
-        self.mlp_pre_version_compatibale_config = weight_prefetch_config.mlp_pre_version_compatibale_config
 
     def maybe_prefetch_attn_weight_preprocess(
         self, layer_cls_name: str, weight: torch.Tensor, start_flag: torch.Tensor
@@ -114,7 +110,7 @@ class WeightPrefetchMethod:
     def maybe_prefetch_mlp_weight_preprocess(
         self, prefetch_layer_name: str, x_dependency: torch.Tensor | None, curr_layer_prefix: str | None = None
     ):
-        if not self.mlp.enable and not self.mlp_pre_version_compatibale_config:
+        if not self.mlp.enable:
             self.mlp.is_active_this_forward = False
             return
 
@@ -146,12 +142,9 @@ class WeightPrefetchMethod:
             model_instance = _EXTRA_CTX.model_instance
             layer_idx = int(curr_layer_prefix.split(".")[2])
             weight = model_instance.model.layers[layer_idx].mlp.gate_up_proj.weight  # type: ignore
-            if self.mlp_pre_version_compatibale_config:
+            weight_size = (
-                weight_size = self.mlp_pre_version_compatibale_config.get(self.MLP_GATE_UP, 0)
+                weight.data.element_size() * weight.data.numel() * self.mlp.prefetch_ratio.get(self.MLP_GATE_UP, 0)
-            else:
+            )
-                weight_size = (
-                    weight.data.element_size() * weight.data.numel() * self.mlp.prefetch_ratio.get(self.MLP_GATE_UP, 0)
-                )
             if weight_size > MAX_PREFETCH_WEIGHT_SIZE:
                 weight_size = MAX_PREFETCH_WEIGHT_SIZE
             torch.ops.vllm.prefetch_preprocess(weight=weight, start_flag=x_dependency, max_weight_size=int(weight_size))
@@ -161,12 +154,7 @@ class WeightPrefetchMethod:
         layer_idx = _EXTRA_CTX.layer_idx
         model_instance = _EXTRA_CTX.model_instance
         weight = model_instance.model.layers[layer_idx].mlp.down_proj.weight  # type: ignore
-        if self.mlp_pre_version_compatibale_config:
+        weight_size = weight.data.element_size() * weight.data.numel() * self.mlp.prefetch_ratio.get(self.MLP_DOWN, 0)
-            weight_size = self.mlp_pre_version_compatibale_config.get(self.MLP_DOWN, 0)
-        else:
-            weight_size = (
-                weight.data.element_size() * weight.data.numel() * self.mlp.prefetch_ratio.get(self.MLP_DOWN, 0)
-            )
         if weight_size > MAX_PREFETCH_WEIGHT_SIZE:
             weight_size = MAX_PREFETCH_WEIGHT_SIZE
         torch.ops.vllm.prefetch_preprocess(weight=weight, start_flag=x_dependency, max_weight_size=int(weight_size))