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xc-llm-ascend/tests/singlecard/test_ascend_config.py

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#
# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
# This file is a part of the vllm-ascend project.
#
# 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.
import pytest
from tests.conftest import VllmRunner
from vllm_ascend.ascend_config import clear_ascend_config, get_ascend_config
def _clean_up_ascend_config(func):
def wrapper(*args, **kwargs):
clear_ascend_config()
func(*args, **kwargs)
clear_ascend_config()
return wrapper
@_clean_up_ascend_config
def test_run_without_ascend_config():
with VllmRunner("facebook/opt-125m"):
ascend_config = get_ascend_config()
assert not ascend_config.torchair_graph_config.enabled
assert not ascend_config.torchair_graph_config.use_cached_graph
assert ascend_config.torchair_graph_config.graph_batch_sizes == []
assert not ascend_config.torchair_graph_config.graph_batch_sizes_init
assert not ascend_config.ascend_scheduler_config.enabled
assert ascend_config.expert_tensor_parallel_size == 1
@_clean_up_ascend_config
def test_run_with_ascend_config():
input_additional_config = {
"torchair_graph_config": {
# torchair graph only works with deepseek. The e2e test should be added
# in multicard test with deepseek models.
"enabled": False,
"use_cached_graph": True,
"graph_batch_sizes": [1, 2, 4, 8],
"graph_batch_sizes_init": False,
},
"ascend_scheduler_config": {
"enabled": True,
"enable_chunked_prefill": True,
},
"expert_tensor_parallel_size": 1
}
with VllmRunner("facebook/opt-125m",
additional_config=input_additional_config):
ascend_config = get_ascend_config()
assert not ascend_config.torchair_graph_config.enabled
assert ascend_config.torchair_graph_config.use_cached_graph
assert ascend_config.torchair_graph_config.graph_batch_sizes == [
1, 2, 4, 8
]
assert not ascend_config.torchair_graph_config.graph_batch_sizes_init
assert ascend_config.ascend_scheduler_config.enabled
assert ascend_config.ascend_scheduler_config.enable_chunked_prefill
assert ascend_config.expert_tensor_parallel_size == 1
@_clean_up_ascend_config
def test_ascend_config_init_error():
# ascend_config should be initialized first
with pytest.raises(RuntimeError):
_ = get_ascend_config()
@_clean_up_ascend_config
def test_ascend_config_load_error():
# graph_batch_sizes should be list.
with pytest.raises(TypeError):
input_additional_config_fake_1 = {
"torchair_graph_config": {
"graph_batch_sizes": "fake_size",
},
}
with VllmRunner("facebook/opt-125m",
additional_config=input_additional_config_fake_1):
pass
# graph_batch_sizes_init should not be True when graph_batch_sizes is not empty.
with pytest.raises(ValueError):
input_additional_config_fake_2 = {
"torchair_graph_config": {
"graph_batch_sizes": [1, 2, 4, 8],
"graph_batch_sizes_init": True,
},
}
with VllmRunner("facebook/opt-125m",
additional_config=input_additional_config_fake_2):
pass
# torchair graph only works with deepseek.
with pytest.raises(NotImplementedError):
input_additional_config_fake_2 = {
"torchair_graph_config": {
"enabled": True,
},
}
with VllmRunner("facebook/opt-125m",
enforce_eager=False,
additional_config=input_additional_config_fake_2):
pass