Files
xc-llm-ascend/tests/ut/test_ascend_config.py
wangxiyuan 69b817ed65 [CI] Add unit test framework (#1201)
This PR added the unit test framework to enable ut for vLLM Ascend. Unit
test runs on CPU machines. It'll be ran once lint check is passed the
same as e2e test.

For unit test, this PR created a new folder called `ut` under `tests`
module. All the test file in `ut` should keep the same with the code in
`vllm-ascend`. The file name should be start with `test_` prefix. For
example, in this PR. the `test_ascend_config.py` is added for
`ascend_config.py` test.

A new fille `worker/test_worker_v1.py` is also added as the placeholder.
This file should be the unit test for `vllm-ascend/worker/worker_v1.py`.

Additional, a new `fake_weight` folder is added, it contains the
config.json from `facebook/opt-125m`, so that the test will not always
visit huggingface.

TODO:
We should add all the unit test file one by one in the future.

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-06-16 18:32:28 +08:00

245 lines
9.7 KiB
Python

import os
import unittest
from unittest import mock
from transformers import PretrainedConfig
from vllm.config import ModelConfig, VllmConfig
from vllm_ascend.ascend_config import (check_ascend_config,
clear_ascend_config, get_ascend_config,
init_ascend_config)
class TestAscendConfig(unittest.TestCase):
@staticmethod
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_init_ascend_config_without_additional_config(self):
test_vllm_config = VllmConfig()
# No additional config given, check the default value here.
ascend_config = init_ascend_config(test_vllm_config)
self.assertEqual(ascend_config.expert_tensor_parallel_size, 0)
self.assertIsNone(ascend_config.expert_map_path)
torchair_graph_config = ascend_config.torchair_graph_config
self.assertFalse(torchair_graph_config.enabled)
self.assertFalse(torchair_graph_config.use_cached_graph)
self.assertEqual(torchair_graph_config.graph_batch_sizes, [])
self.assertFalse(torchair_graph_config.graph_batch_sizes_init)
self.assertFalse(torchair_graph_config.enable_multistream_mla)
self.assertFalse(torchair_graph_config.enable_multistream_moe)
self.assertTrue(torchair_graph_config.enable_view_optimize)
self.assertFalse(torchair_graph_config.enable_kv_nz)
ascend_scheduler_config = ascend_config.ascend_scheduler_config
self.assertFalse(ascend_scheduler_config.enabled)
@_clean_up_ascend_config
def test_init_ascend_config_with_additional_config(self):
test_vllm_config = VllmConfig()
test_vllm_config.additional_config = {
"torchair_graph_config": {
"enabled": True,
"use_cached_graph": True,
"graph_batch_sizes": [1, 2, 4],
"graph_batch_sizes_init": False,
"enable_multistream_mla": True,
"enable_multistream_moe": True,
"enable_view_optimize": True,
"enable_kv_nz": True
},
"ascend_scheduler_config": {
"enabled": True
},
"expert_tensor_parallel_size": 1,
"expert_map_path": "test_expert_map_path",
"refresh": True
}
ascend_config = init_ascend_config(test_vllm_config)
self.assertEqual(ascend_config.expert_tensor_parallel_size, 1)
self.assertEqual(ascend_config.expert_map_path, "test_expert_map_path")
torchair_graph_config = ascend_config.torchair_graph_config
self.assertTrue(torchair_graph_config.enabled)
self.assertTrue(torchair_graph_config.use_cached_graph)
self.assertEqual(torchair_graph_config.graph_batch_sizes, [1, 2, 4])
self.assertFalse(torchair_graph_config.graph_batch_sizes_init)
self.assertTrue(torchair_graph_config.enable_multistream_mla)
self.assertTrue(torchair_graph_config.enable_multistream_moe)
self.assertTrue(torchair_graph_config.enable_view_optimize)
self.assertTrue(torchair_graph_config.enable_kv_nz)
ascend_scheduler_config = ascend_config.ascend_scheduler_config
self.assertTrue(ascend_scheduler_config.enabled)
@_clean_up_ascend_config
def test_init_ascend_config_with_refresh(self):
test_vllm_config = VllmConfig()
ascend_config = init_ascend_config(test_vllm_config)
self.assertFalse(ascend_config.torchair_graph_config.enabled)
test_vllm_config.additional_config = {
"torchair_graph_config": {
"enabled": True,
},
}
ascend_config = init_ascend_config(test_vllm_config)
self.assertFalse(ascend_config.torchair_graph_config.enabled)
test_vllm_config.additional_config = {
"torchair_graph_config": {
"enabled": True,
},
"refresh": True,
}
ascend_config = init_ascend_config(test_vllm_config)
self.assertTrue(ascend_config.torchair_graph_config.enabled)
@_clean_up_ascend_config
def test_init_ascend_config_with_wrong_input(self):
test_vllm_config = VllmConfig()
test_vllm_config.additional_config = {
"torchair_graph_config": {
"enabled": True,
"graph_batch_sizes": "fake_size",
},
"refresh": True,
}
with self.assertRaises(TypeError):
init_ascend_config(test_vllm_config)
test_vllm_config.additional_config = {
"torchair_graph_config": {
"enabled": False,
"graph_batch_sizes": [1, 2, 4, 8],
"graph_batch_sizes_init": True,
},
"refresh": True,
}
with self.assertRaises(ValueError):
init_ascend_config(test_vllm_config)
@_clean_up_ascend_config
def test_get_ascend_config(self):
test_vllm_config = VllmConfig()
ascend_config = init_ascend_config(test_vllm_config)
self.assertEqual(get_ascend_config(), ascend_config)
@_clean_up_ascend_config
def test_get_ascend_config_without_init(self):
with self.assertRaises(RuntimeError):
get_ascend_config()
@_clean_up_ascend_config
def test_clear_ascend_config(self):
test_vllm_config = VllmConfig()
ascend_config = init_ascend_config(test_vllm_config)
self.assertEqual(get_ascend_config(), ascend_config)
clear_ascend_config()
with self.assertRaises(RuntimeError):
get_ascend_config()
@_clean_up_ascend_config
def test_check_ascend_config_pass(self):
test_vllm_config = VllmConfig()
init_ascend_config(test_vllm_config)
check_ascend_config(test_vllm_config, False)
# For V1 engine
with mock.patch.dict(os.environ, {"VLLM_USE_V1": "1"}):
test_vllm_config.additional_config = {
"torchair_graph_config": {
"enabled": True,
},
"refresh": True
}
init_ascend_config(test_vllm_config)
check_ascend_config(test_vllm_config, False)
test_vllm_config.additional_config = {
"torchair_graph_config": {
"enabled": False,
},
"refresh": True
}
init_ascend_config(test_vllm_config)
check_ascend_config(test_vllm_config, False)
@_clean_up_ascend_config
def test_check_ascend_config_wrong_case(self):
test_vllm_config = VllmConfig()
# For V0 engine
with mock.patch.dict(os.environ, {"VLLM_USE_V1": "0"}):
with self.assertRaises(NotImplementedError):
test_vllm_config.additional_config = {
"torchair_graph_config": {
"enabled": True,
},
"refresh": True
}
init_ascend_config(test_vllm_config)
check_ascend_config(test_vllm_config, False)
with self.assertRaises(NotImplementedError):
test_vllm_config.additional_config = {
"ascend_scheduler_config": {
"enabled": True,
},
"refresh": True
}
init_ascend_config(test_vllm_config)
check_ascend_config(test_vllm_config, True)
# For V1 engine
with mock.patch.dict(os.environ, {"VLLM_USE_V1": "1"}):
# torchair + eager mode
with self.assertRaises(RuntimeError):
test_vllm_config.additional_config = {
"torchair_graph_config": {
"enabled": True,
},
"refresh": True
}
init_ascend_config(test_vllm_config)
enforce_eager = True
check_ascend_config(test_vllm_config, enforce_eager)
# torchair + non deepseek model
with self.assertRaises(NotImplementedError):
test_vllm_config.additional_config = {
"torchair_graph_config": {
"enabled": True,
},
"refresh": True
}
model_path = os.path.join(os.path.dirname(__file__),
"fake_weight")
fake_model_config = ModelConfig(model=model_path)
fake_model_config.hf_config = PretrainedConfig()
fake_model_config.hf_config.model_type = "llama"
test_vllm_config.model_config = fake_model_config
init_ascend_config(test_vllm_config)
check_ascend_config(test_vllm_config, False)
# aclgraph + deepseek model
with self.assertRaises(NotImplementedError):
test_vllm_config.additional_config = {
"torchair_graph_config": {
"enabled": False,
},
"refresh": True
}
model_path = os.path.join(os.path.dirname(__file__),
"fake_weight")
fake_model_config = ModelConfig(model=model_path)
fake_model_config.hf_config = PretrainedConfig()
fake_model_config.hf_config.model_type = "deepseek"
test_vllm_config.model_config = fake_model_config
init_ascend_config(test_vllm_config)
check_ascend_config(test_vllm_config, False)