2025-06-05 16:28:01 +08:00
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# This file is a part of the vllm-ascend project.
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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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import pytest
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from tests.conftest import VllmRunner
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from vllm_ascend.ascend_config import clear_ascend_config, get_ascend_config
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def _clean_up_ascend_config(func):
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def wrapper(*args, **kwargs):
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clear_ascend_config()
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func(*args, **kwargs)
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clear_ascend_config()
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return wrapper
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@_clean_up_ascend_config
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def test_run_without_ascend_config():
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with VllmRunner("facebook/opt-125m"):
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ascend_config = get_ascend_config()
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assert not ascend_config.torchair_graph_config.enabled
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assert not ascend_config.torchair_graph_config.use_cached_graph
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assert ascend_config.torchair_graph_config.graph_batch_sizes == []
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assert not ascend_config.torchair_graph_config.graph_batch_sizes_init
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assert not ascend_config.ascend_scheduler_config.enabled
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assert ascend_config.expert_tensor_parallel_size == 1
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@_clean_up_ascend_config
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def test_run_with_ascend_config():
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input_additional_config = {
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"torchair_graph_config": {
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# torchair graph only works with deepseek. The e2e test should be added
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# in multicard test with deepseek models.
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"enabled": False,
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"use_cached_graph": True,
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"graph_batch_sizes": [1, 2, 4, 8],
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"graph_batch_sizes_init": False,
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},
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"ascend_scheduler_config": {
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"enabled": True,
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"enable_chunked_prefill": True,
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},
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"expert_tensor_parallel_size": 1
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}
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with VllmRunner("facebook/opt-125m",
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additional_config=input_additional_config):
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ascend_config = get_ascend_config()
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assert not ascend_config.torchair_graph_config.enabled
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assert ascend_config.torchair_graph_config.use_cached_graph
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assert ascend_config.torchair_graph_config.graph_batch_sizes == [
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1, 2, 4, 8
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]
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assert not ascend_config.torchair_graph_config.graph_batch_sizes_init
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assert ascend_config.ascend_scheduler_config.enabled
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assert ascend_config.ascend_scheduler_config.enable_chunked_prefill
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assert ascend_config.expert_tensor_parallel_size == 1
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@_clean_up_ascend_config
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def test_ascend_config_init_error():
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# ascend_config should be initialized first
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with pytest.raises(RuntimeError):
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_ = get_ascend_config()
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@_clean_up_ascend_config
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def test_ascend_config_load_error():
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# graph_batch_sizes should be list.
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with pytest.raises(TypeError):
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input_additional_config_fake_1 = {
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"torchair_graph_config": {
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"graph_batch_sizes": "fake_size",
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},
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}
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with VllmRunner("facebook/opt-125m",
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additional_config=input_additional_config_fake_1):
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pass
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# graph_batch_sizes_init should not be True when graph_batch_sizes is not empty.
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with pytest.raises(ValueError):
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input_additional_config_fake_2 = {
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"torchair_graph_config": {
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"graph_batch_sizes": [1, 2, 4, 8],
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"graph_batch_sizes_init": True,
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},
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}
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with VllmRunner("facebook/opt-125m",
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additional_config=input_additional_config_fake_2):
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pass
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# torchair graph only works with deepseek.
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with pytest.raises(NotImplementedError):
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input_additional_config_fake_2 = {
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"torchair_graph_config": {
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"enabled": True,
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},
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}
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with VllmRunner("facebook/opt-125m",
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2025-06-05 23:39:38 +08:00
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enforce_eager=False,
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2025-06-05 16:28:01 +08:00
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additional_config=input_additional_config_fake_2):
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pass
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