init v0.11.0rc0

vllm_ascend/core/schedule_config.py

@@ -20,14 +20,19 @@ from typing import Type, Union
 
 from vllm.config import SchedulerConfig
 
+MAX_INT = 2147483647
+
 
 @dataclass
 class AscendSchedulerConfig(SchedulerConfig):
     enable_chunked_prefill: bool = False
+    max_long_partial_prefills: int = MAX_INT
+    long_prefill_token_threshold: int = MAX_INT
     policy: str = "fcfs"
-    num_scheduler_steps: int = 1
     scheduler_cls: Union[str, Type[object]] = (
         "vllm_ascend.core.scheduler.AscendScheduler")
+    enable_pd_transfer: bool = False
+    decode_max_num_seqs: int = 0
 
     @classmethod
     def initialize_from_config(
@@ -41,10 +46,13 @@ class AscendSchedulerConfig(SchedulerConfig):
         }
         # Override default values into original SchedulerConfig
         scheduler_config["enable_chunked_prefill"] = False
+        scheduler_config["max_long_partial_prefills"] = None
+        scheduler_config["long_prefill_token_threshold"] = None
         scheduler_config["policy"] = "fcfs"
-        scheduler_config["num_scheduler_steps"] = 1
         scheduler_config["scheduler_cls"] = (
             "vllm_ascend.core.scheduler.AscendScheduler")
+        scheduler_config["enable_pd_transfer"] = False
+        scheduler_config["decode_max_num_seqs"] = 0
         # Override params in original SchedulerConfig with params in ascend_scheduler_config
         for k, _ in scheduler_config.items():
             if hasattr(ascend_scheduler_config, k):
@@ -65,20 +73,36 @@ class AscendSchedulerConfig(SchedulerConfig):
                 "max_num_batched_tokens and makes vLLM reject longer "
                 "sequences. Please increase max_num_batched_tokens or "
                 "decrease max_model_len.")
+        # concurrent partial prefills. Default is inf
+        if self.max_long_partial_prefills is None:
+            self.max_long_partial_prefills = MAX_INT
+            self.long_prefill_token_threshold = MAX_INT
+
+        if self.long_prefill_token_threshold is None or \
+            self.long_prefill_token_threshold <= 0:
+            if self.max_model_len is None:
+                self.long_prefill_token_threshold = MAX_INT
+            else:
+                self.long_prefill_token_threshold = \
+                    max(1, int(self.max_model_len * 0.04))
+
+        if self.max_long_partial_prefills < 0:
+            raise ValueError(
+                f"max_long_partial_prefills must be non-negative, but got "
+                f"{self.max_long_partial_prefills}")
+        if self.long_prefill_token_threshold < 0:
+            raise ValueError(
+                f"long_prefill_token_threshold must be non-negative, but got "
+                f"{self.long_prefill_token_threshold}")
+
         if self.policy != "fcfs":
             raise NotImplementedError(
                 f"currently AscendScheduler only supports fcfs policy, got {self.policy}"
             )
-        if self.is_multimodal_model:
-            raise NotImplementedError(
-                "currently AscendScheduler only supports LLM models.")
-        if self.num_scheduler_steps > 1:
-            raise NotImplementedError(
-                "currently AscendScheduler doesn't support multi-step.")
         if self.send_delta_data:
             raise NotImplementedError(
                 "currently AscendScheduler doesn't support send_delta_data.")
-        if self.delay_factor > 0:
+        if getattr(self, "scheduler_delay_factor", 0) > 0:
             raise NotImplementedError(
                 "currently AscendScheduler doesn't support scheduler_delay_factor."
             )