84 lines
2.4 KiB
Python
84 lines
2.4 KiB
Python
import json
|
|
|
|
import openai # use the official client for correctness check
|
|
import pytest
|
|
import pytest_asyncio
|
|
# downloading lora to test lora requests
|
|
from huggingface_hub import snapshot_download
|
|
|
|
from ...utils import RemoteOpenAIServer
|
|
|
|
# any model with a chat template should work here
|
|
MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
|
|
# technically this needs Mistral-7B-v0.1 as base, but we're not testing
|
|
# generation quality here
|
|
LORA_NAME = "typeof/zephyr-7b-beta-lora"
|
|
|
|
|
|
@pytest.fixture(scope="module")
|
|
def zephyr_lora_files():
|
|
return snapshot_download(repo_id=LORA_NAME)
|
|
|
|
|
|
@pytest.fixture(scope="module")
|
|
def server_with_lora_modules_json(zephyr_lora_files):
|
|
# Define the json format LoRA module configurations
|
|
lora_module_1 = {
|
|
"name": "zephyr-lora",
|
|
"path": zephyr_lora_files,
|
|
"base_model_name": MODEL_NAME
|
|
}
|
|
|
|
lora_module_2 = {
|
|
"name": "zephyr-lora2",
|
|
"path": zephyr_lora_files,
|
|
"base_model_name": MODEL_NAME
|
|
}
|
|
|
|
args = [
|
|
# use half precision for speed and memory savings in CI environment
|
|
"--dtype",
|
|
"bfloat16",
|
|
"--max-model-len",
|
|
"8192",
|
|
"--enforce-eager",
|
|
# lora config below
|
|
"--enable-lora",
|
|
"--lora-modules",
|
|
json.dumps(lora_module_1),
|
|
json.dumps(lora_module_2),
|
|
"--max-lora-rank",
|
|
"64",
|
|
"--max-cpu-loras",
|
|
"2",
|
|
"--max-num-seqs",
|
|
"64",
|
|
]
|
|
|
|
with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
|
|
yield remote_server
|
|
|
|
|
|
@pytest_asyncio.fixture
|
|
async def client_for_lora_lineage(server_with_lora_modules_json):
|
|
async with server_with_lora_modules_json.get_async_client(
|
|
) as async_client:
|
|
yield async_client
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_check_lora_lineage(client_for_lora_lineage: openai.AsyncOpenAI,
|
|
zephyr_lora_files):
|
|
models = await client_for_lora_lineage.models.list()
|
|
models = models.data
|
|
served_model = models[0]
|
|
lora_models = models[1:]
|
|
assert served_model.id == MODEL_NAME
|
|
assert served_model.root == MODEL_NAME
|
|
assert served_model.parent is None
|
|
assert all(lora_model.root == zephyr_lora_files
|
|
for lora_model in lora_models)
|
|
assert all(lora_model.parent == MODEL_NAME for lora_model in lora_models)
|
|
assert lora_models[0].id == "zephyr-lora"
|
|
assert lora_models[1].id == "zephyr-lora2"
|