### 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>
168 lines
6.7 KiB
Python
168 lines
6.7 KiB
Python
#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from vllm.config import SchedulerConfig
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from tests.ut.base import TestBase
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from vllm_ascend.core.schedule_config import AscendSchedulerConfig
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class TestAscendSchedulerConfig(TestBase):
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def setUp(self):
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self.basic_scheduler_config = SchedulerConfig(
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max_num_batched_tokens=8192,
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max_model_len=8192,
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is_multimodal_model=False,
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send_delta_data=False,
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scheduler_delay_factor=0,
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)
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def test_initialize_from_config_with_default(self):
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# No additional config given, check the default value here.
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ascend_config = AscendSchedulerConfig.initialize_from_config(
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self.basic_scheduler_config, {})
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self.assertEqual(ascend_config.enable_chunked_prefill, False)
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self.assertEqual(ascend_config.policy, "fcfs")
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self.assertEqual(ascend_config.num_scheduler_steps, 1)
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self.assertEqual(ascend_config.scheduler_cls,
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"vllm_ascend.core.scheduler.AscendScheduler")
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self.assertEqual(ascend_config.max_num_encoder_input_tokens, 8192)
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self.assertEqual(ascend_config.encoder_cache_size, 8192)
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def test_initialize_from_config_with_override(self):
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# test override
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ascend_config = AscendSchedulerConfig.initialize_from_config(
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self.basic_scheduler_config,
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AscendSchedulerConfig(
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enable_chunked_prefill=False,
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policy="fcfs",
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num_scheduler_steps=1,
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scheduler_cls="vllm_ascend.core.scheduler.AscendScheduler",
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max_num_batched_tokens=2048,
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max_model_len=2048,
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),
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)
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self.assertEqual(ascend_config.enable_chunked_prefill, False)
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self.assertEqual(ascend_config.policy, "fcfs")
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self.assertEqual(ascend_config.num_scheduler_steps, 1)
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self.assertEqual(ascend_config.scheduler_cls,
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"vllm_ascend.core.scheduler.AscendScheduler")
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self.assertEqual(ascend_config.max_num_batched_tokens, 2048)
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self.assertEqual(ascend_config.encoder_cache_size, 2048)
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def test_not_implemented_policy(self):
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with self.assertRaises(NotImplementedError) as context:
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AscendSchedulerConfig.initialize_from_config(
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self.basic_scheduler_config,
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AscendSchedulerConfig(
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policy="custom_policy",
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max_num_batched_tokens=2048,
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max_model_len=2048,
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),
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)
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self.assertIn(
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"currently AscendScheduler only supports fcfs policy",
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str(context.exception),
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)
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def test_not_implemented_multimodal(self):
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with self.assertRaises(NotImplementedError) as context:
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AscendSchedulerConfig.initialize_from_config(
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SchedulerConfig(is_multimodal_model=True), {})
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self.assertIn("currently AscendScheduler only supports LLM models",
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str(context.exception))
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def test_not_implemented_multi_step(self):
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with self.assertRaises(NotImplementedError) as context:
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AscendSchedulerConfig.initialize_from_config(
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self.basic_scheduler_config,
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AscendSchedulerConfig(
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num_scheduler_steps=2,
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max_num_batched_tokens=2048,
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max_model_len=2048,
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),
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)
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self.assertIn(
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"currently AscendScheduler doesn't support multi-step",
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str(context.exception),
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)
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def test_not_implemented_send_delta_data(self):
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with self.assertRaises(NotImplementedError) as context:
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AscendSchedulerConfig.initialize_from_config(
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self.basic_scheduler_config,
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AscendSchedulerConfig(
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send_delta_data=True,
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max_num_batched_tokens=2048,
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max_model_len=2048,
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),
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)
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self.assertIn(
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"currently AscendScheduler doesn't support send_delta_data",
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str(context.exception),
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)
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def test_not_implemented_delay_factor(self):
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with self.assertRaises(NotImplementedError) as context:
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AscendSchedulerConfig.initialize_from_config(
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self.basic_scheduler_config,
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AscendSchedulerConfig(
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delay_factor=1,
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max_num_batched_tokens=2048,
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max_model_len=2048,
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),
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)
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self.assertIn(
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"currently AscendScheduler doesn't support scheduler_delay_factor",
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str(context.exception),
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)
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def test_no_override(self):
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ascend_config = AscendSchedulerConfig.initialize_from_config(
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self.basic_scheduler_config, {})
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self.assertEqual(ascend_config.max_num_encoder_input_tokens, 8192)
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self.assertEqual(ascend_config.encoder_cache_size, 8192)
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def test_valid_config_with_chunked_prefill(self):
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ascend_config = AscendSchedulerConfig.initialize_from_config(
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self.basic_scheduler_config,
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AscendSchedulerConfig(
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enable_chunked_prefill=True,
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max_num_batched_tokens=2048,
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max_model_len=4096,
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),
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)
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self.assertEqual(ascend_config.max_num_batched_tokens, 2048)
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self.assertEqual(ascend_config.max_model_len, 4096)
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self.assertTrue(ascend_config.enable_chunked_prefill)
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def test_invalid_config_without_chunked_prefill(self):
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with self.assertRaises(ValueError) as context:
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AscendSchedulerConfig.initialize_from_config(
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self.basic_scheduler_config,
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AscendSchedulerConfig(
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enable_chunked_prefill=False,
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max_num_batched_tokens=2048,
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max_model_len=4096,
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),
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)
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self.assertIn(
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"Ascend scheduler is enabled without chunked prefill feature",
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str(context.exception),
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)
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self.assertIn("max_num_batched_tokens (2048)", str(context.exception))
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self.assertIn("max_model_len (4096)", str(context.exception))
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