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[XPU]Fixed the issue of performance degradation caused by enabling ENABLE_V1_KVCACHE_SCHEDULER (#3900)

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* fix bug

* fix bug

* update

* udpate

* update
This commit is contained in:
yinwei
2025-09-05 19:17:25 +08:00
committed by GitHub
parent 473cde779f
commit 77c1bd0813
4 changed files with 20 additions and 4 deletions
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5
fastdeploy/config.py
View File

@@ -1236,7 +1236,10 @@ class FDConfig:
if self.max_num_batched_tokens is None:
if int(envs.ENABLE_V1_KVCACHE_SCHEDULER):
self.max_num_batched_tokens = 8192 # if set to max_model_len, it's easy to be OOM
if paddle.is_compiled_with_xpu():
self.max_num_batched_tokens = self.max_model_len
else:
self.max_num_batched_tokens = 8192 # if set to max_model_len, it's easy to be OOM
else:
if self.cache_config.enable_chunked_prefill:
self.max_num_batched_tokens = 2048

7
fastdeploy/engine/args_utils.py
View File

@@ -19,6 +19,8 @@ from dataclasses import asdict, dataclass
from dataclasses import fields as dataclass_fields
from typing import Any, Dict, List, Optional
import paddle
from fastdeploy import envs
from fastdeploy.config import (
CacheConfig,
@@ -1006,7 +1008,10 @@ class EngineArgs:
if self.max_num_batched_tokens is None:
if int(envs.ENABLE_V1_KVCACHE_SCHEDULER):
self.max_num_batched_tokens = 8192 # if set to max_model_len, it's easy to be OOM
if paddle.is_compiled_with_xpu():
self.max_num_batched_tokens = self.max_model_len
else:
self.max_num_batched_tokens = 8192 # if set to max_model_len, it's easy to be OOM
else:
if self.enable_chunked_prefill:
self.max_num_batched_tokens = 2048

4
fastdeploy/engine/sched/resource_manager_v1.py
View File

@@ -345,7 +345,9 @@ class ResourceManagerV1(ResourceManager):
while self.waiting and token_budget > 0:
if len(self.running) == self.max_num_seqs:
break
if self.config.model_config.enable_mm and self.exist_prefill(scheduled_reqs):
if (self.config.model_config.enable_mm or paddle.is_compiled_with_xpu()) and self.exist_prefill(
scheduled_reqs
):
break
request = self.waiting[0]
if request.status == RequestStatus.WAITING:

8
fastdeploy/worker/xpu_model_runner.py
View File

@@ -383,6 +383,7 @@ class XPUModelRunner(ModelRunnerBase):
req_len = len(req_dicts)
has_prefill_task = False
has_decode_task = False
for i in range(req_len):
request = req_dicts[i]
idx = request.idx
@@ -392,6 +393,9 @@ class XPUModelRunner(ModelRunnerBase):
prefill_end_index = request.prefill_end_index
length = prefill_end_index - prefill_start_index
input_ids = request.prompt_token_ids + request.output_token_ids
logger.debug(
f"Handle prefill request {request} at idx {idx} prefill_start_index {prefill_start_index} prefill_end_index {prefill_end_index} need_prefilled_token_num {len(input_ids)}"
)
self.share_inputs["input_ids"][idx : idx + 1, :length] = np.array(
input_ids[prefill_start_index:prefill_end_index]
)
@@ -401,6 +405,8 @@ class XPUModelRunner(ModelRunnerBase):
self.share_inputs["block_tables"][idx : idx + 1, :encoder_block_num] = np.array(
request.block_tables, dtype="int32"
)
if self.share_inputs["is_block_step"][idx]: # has tasks to continue to decode
has_decode_task = True
self.share_inputs["stop_flags"][idx : idx + 1] = False
self.share_inputs["seq_lens_decoder"][idx : idx + 1] = prefill_start_index
self.share_inputs["seq_lens_this_time"][idx : idx + 1] = length
@@ -474,7 +480,7 @@ class XPUModelRunner(ModelRunnerBase):
self.share_inputs["stop_seqs"][:stop_seqs_num, : len(request.get("stop_token_ids")[0])] = np.array(
request.get("stop_token_ids"), dtype="int64"
)
if has_prefill_task:
if has_prefill_task or has_decode_task:
self.share_inputs["not_need_stop"][0] = True
def process_prefill_inputs(self, req_dicts: List[Request]):