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110 lines
3.5 KiB
Python
110 lines
3.5 KiB
Python
import json
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import openai # use the official client for correctness check
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import pytest
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import pytest_asyncio
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# downloading lora to test lora requests
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from huggingface_hub import snapshot_download
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from ...utils import RemoteOpenAIServer
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# any model with a chat template should work here
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MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
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# technically this needs Mistral-7B-v0.1 as base, but we're not testing
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# generation quality here
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LORA_NAME = "typeof/zephyr-7b-beta-lora"
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@pytest.fixture(scope="module")
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def zephyr_lora_files():
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return snapshot_download(repo_id=LORA_NAME)
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@pytest.fixture(scope="module")
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def server_with_lora_modules_json(zephyr_lora_files):
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# Define the json format LoRA module configurations
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lora_module_1 = {
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"name": "zephyr-lora",
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"path": zephyr_lora_files,
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"base_model_name": MODEL_NAME
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}
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lora_module_2 = {
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"name": "zephyr-lora2",
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"path": zephyr_lora_files,
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"base_model_name": MODEL_NAME
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}
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args = [
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# use half precision for speed and memory savings in CI environment
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"--dtype",
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"bfloat16",
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"--max-model-len",
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"8192",
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"--enforce-eager",
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# lora config below
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"--enable-lora",
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"--lora-modules",
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json.dumps(lora_module_1),
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json.dumps(lora_module_2),
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"--max-lora-rank",
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"64",
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"--max-cpu-loras",
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"2",
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"--max-num-seqs",
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"64",
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]
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# Enable the /v1/load_lora_adapter endpoint
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envs = {"VLLM_ALLOW_RUNTIME_LORA_UPDATING": "True"}
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with RemoteOpenAIServer(MODEL_NAME, args, env_dict=envs) as remote_server:
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yield remote_server
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@pytest_asyncio.fixture
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async def client_for_lora_lineage(server_with_lora_modules_json):
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async with server_with_lora_modules_json.get_async_client(
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) as async_client:
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yield async_client
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@pytest.mark.asyncio
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async def test_static_lora_lineage(client_for_lora_lineage: openai.AsyncOpenAI,
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zephyr_lora_files):
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models = await client_for_lora_lineage.models.list()
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models = models.data
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served_model = models[0]
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lora_models = models[1:]
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assert served_model.id == MODEL_NAME
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assert served_model.root == MODEL_NAME
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assert served_model.parent is None
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assert all(lora_model.root == zephyr_lora_files
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for lora_model in lora_models)
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assert all(lora_model.parent == MODEL_NAME for lora_model in lora_models)
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assert lora_models[0].id == "zephyr-lora"
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assert lora_models[1].id == "zephyr-lora2"
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@pytest.mark.asyncio
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async def test_dynamic_lora_lineage(
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client_for_lora_lineage: openai.AsyncOpenAI, zephyr_lora_files):
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response = await client_for_lora_lineage.post("load_lora_adapter",
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cast_to=str,
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body={
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"lora_name":
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"zephyr-lora-3",
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"lora_path":
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zephyr_lora_files
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})
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# Ensure adapter loads before querying /models
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assert "success" in response
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models = await client_for_lora_lineage.models.list()
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models = models.data
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dynamic_lora_model = models[-1]
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assert dynamic_lora_model.root == zephyr_lora_files
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assert dynamic_lora_model.parent == MODEL_NAME
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assert dynamic_lora_model.id == "zephyr-lora-3"
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