Files
xc-llm-ascend/tests/ut/core/test_schedule_config.py
linfeng-yuan 4af5b80606 [Scheduler] validate max_num_batched_tokens and max_model_len in AscendSchedulerConfig (#2434)
### What this PR does / why we need it?
Add configuration check logic for ascend scheduler: if chunked_prefill
is disabled, max_num_batched_tokens couldn't be less than max_model_len,
following vLLM;

### Does this PR introduce _any_ user-facing change?
users cannot set max_num_batched_tokens smaller than max_model_len with
ascend scheduler
### How was this patch tested?
CI and vllm serving passed

- vLLM version: v0.10.0
- vLLM main:
f77a0802b7

Signed-off-by: linfeng-yuan <1102311262@qq.com>
2025-08-23 19:39:44 +08:00

168 lines
6.7 KiB
Python

#
# 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.
from vllm.config import SchedulerConfig
from tests.ut.base import TestBase
from vllm_ascend.core.schedule_config import AscendSchedulerConfig
class TestAscendSchedulerConfig(TestBase):
def setUp(self):
self.basic_scheduler_config = SchedulerConfig(
max_num_batched_tokens=8192,
max_model_len=8192,
is_multimodal_model=False,
send_delta_data=False,
scheduler_delay_factor=0,
)
def test_initialize_from_config_with_default(self):
# No additional config given, check the default value here.
ascend_config = AscendSchedulerConfig.initialize_from_config(
self.basic_scheduler_config, {})
self.assertEqual(ascend_config.enable_chunked_prefill, False)
self.assertEqual(ascend_config.policy, "fcfs")
self.assertEqual(ascend_config.num_scheduler_steps, 1)
self.assertEqual(ascend_config.scheduler_cls,
"vllm_ascend.core.scheduler.AscendScheduler")
self.assertEqual(ascend_config.max_num_encoder_input_tokens, 8192)
self.assertEqual(ascend_config.encoder_cache_size, 8192)
def test_initialize_from_config_with_override(self):
# test override
ascend_config = AscendSchedulerConfig.initialize_from_config(
self.basic_scheduler_config,
AscendSchedulerConfig(
enable_chunked_prefill=False,
policy="fcfs",
num_scheduler_steps=1,
scheduler_cls="vllm_ascend.core.scheduler.AscendScheduler",
max_num_batched_tokens=2048,
max_model_len=2048,
),
)
self.assertEqual(ascend_config.enable_chunked_prefill, False)
self.assertEqual(ascend_config.policy, "fcfs")
self.assertEqual(ascend_config.num_scheduler_steps, 1)
self.assertEqual(ascend_config.scheduler_cls,
"vllm_ascend.core.scheduler.AscendScheduler")
self.assertEqual(ascend_config.max_num_batched_tokens, 2048)
self.assertEqual(ascend_config.encoder_cache_size, 2048)
def test_not_implemented_policy(self):
with self.assertRaises(NotImplementedError) as context:
AscendSchedulerConfig.initialize_from_config(
self.basic_scheduler_config,
AscendSchedulerConfig(
policy="custom_policy",
max_num_batched_tokens=2048,
max_model_len=2048,
),
)
self.assertIn(
"currently AscendScheduler only supports fcfs policy",
str(context.exception),
)
def test_not_implemented_multimodal(self):
with self.assertRaises(NotImplementedError) as context:
AscendSchedulerConfig.initialize_from_config(
SchedulerConfig(is_multimodal_model=True), {})
self.assertIn("currently AscendScheduler only supports LLM models",
str(context.exception))
def test_not_implemented_multi_step(self):
with self.assertRaises(NotImplementedError) as context:
AscendSchedulerConfig.initialize_from_config(
self.basic_scheduler_config,
AscendSchedulerConfig(
num_scheduler_steps=2,
max_num_batched_tokens=2048,
max_model_len=2048,
),
)
self.assertIn(
"currently AscendScheduler doesn't support multi-step",
str(context.exception),
)
def test_not_implemented_send_delta_data(self):
with self.assertRaises(NotImplementedError) as context:
AscendSchedulerConfig.initialize_from_config(
self.basic_scheduler_config,
AscendSchedulerConfig(
send_delta_data=True,
max_num_batched_tokens=2048,
max_model_len=2048,
),
)
self.assertIn(
"currently AscendScheduler doesn't support send_delta_data",
str(context.exception),
)
def test_not_implemented_delay_factor(self):
with self.assertRaises(NotImplementedError) as context:
AscendSchedulerConfig.initialize_from_config(
self.basic_scheduler_config,
AscendSchedulerConfig(
delay_factor=1,
max_num_batched_tokens=2048,
max_model_len=2048,
),
)
self.assertIn(
"currently AscendScheduler doesn't support scheduler_delay_factor",
str(context.exception),
)
def test_no_override(self):
ascend_config = AscendSchedulerConfig.initialize_from_config(
self.basic_scheduler_config, {})
self.assertEqual(ascend_config.max_num_encoder_input_tokens, 8192)
self.assertEqual(ascend_config.encoder_cache_size, 8192)
def test_valid_config_with_chunked_prefill(self):
ascend_config = AscendSchedulerConfig.initialize_from_config(
self.basic_scheduler_config,
AscendSchedulerConfig(
enable_chunked_prefill=True,
max_num_batched_tokens=2048,
max_model_len=4096,
),
)
self.assertEqual(ascend_config.max_num_batched_tokens, 2048)
self.assertEqual(ascend_config.max_model_len, 4096)
self.assertTrue(ascend_config.enable_chunked_prefill)
def test_invalid_config_without_chunked_prefill(self):
with self.assertRaises(ValueError) as context:
AscendSchedulerConfig.initialize_from_config(
self.basic_scheduler_config,
AscendSchedulerConfig(
enable_chunked_prefill=False,
max_num_batched_tokens=2048,
max_model_len=4096,
),
)
self.assertIn(
"Ascend scheduler is enabled without chunked prefill feature",
str(context.exception),
)
self.assertIn("max_num_batched_tokens (2048)", str(context.exception))
self.assertIn("max_model_len (4096)", str(context.exception))