大改

vllm_npu/core/schedule_config.py

@@ -0,0 +1,108 @@
+#
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# This file is a part of the vllm-ascend project.
+#
+
+from dataclasses import dataclass, fields
+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 = 1
+    long_prefill_token_threshold: int = MAX_INT
+    policy: str = "fcfs"
+    scheduler_cls: Union[str, Type[object]] = (
+        "vllm_npu.core.scheduler.AscendScheduler")
+    enable_pd_transfer: bool = False
+    decode_max_num_seqs: int = 0
+
+    @classmethod
+    def initialize_from_config(
+        cls,
+        vllm_scheduler_config: SchedulerConfig,
+        ascend_scheduler_config,
+    ):
+        scheduler_config = {
+            field.name: getattr(vllm_scheduler_config, field.name)
+            for field in fields(vllm_scheduler_config) if field.init
+        }
+        # 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["scheduler_cls"] = (
+            "vllm_npu.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):
+                scheduler_config[k] = getattr(ascend_scheduler_config, k)
+        return cls(**scheduler_config)
+
+    def __post_init__(self) -> None:
+        self.max_num_encoder_input_tokens = self.max_num_batched_tokens
+        self.encoder_cache_size = self.max_num_batched_tokens
+        self.chunked_prefill_enabled = self.enable_chunked_prefill
+        if (self.max_num_batched_tokens < self.max_model_len
+                and not self.chunked_prefill_enabled):
+            raise ValueError(
+                "Ascend scheduler is enabled without chunked prefill feature. "
+                f"Argument max_num_batched_tokens ({self.max_num_batched_tokens}) is "
+                f"smaller than max_model_len ({self.max_model_len}). "
+                "This effectively limits the maximum sequence length to "
+                "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 1 meaning not enabled.
+        if self.max_long_partial_prefills is None:
+            self.max_long_partial_prefills = 1
+            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.send_delta_data:
+            raise NotImplementedError(
+                "currently AscendScheduler doesn't support send_delta_data.")
+        if getattr(self, "scheduler_delay_factor", 0) > 0:
+            raise NotImplementedError(
+                "currently AscendScheduler doesn't support scheduler_delay_factor."
+            )