vllm/tests/lora/test_mixtral.py
Jee Jee Li 12c29a881f
[Bugfix] Further clean up LoRA test (#14422)
Signed-off-by: Jee Jee Li <pandaleefree@gmail.com>
2025-03-07 10:30:55 +00:00

72 lines
5.1 KiB
Python

# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
import vllm
from vllm.lora.request import LoRARequest
from vllm.platforms import current_platform
MODEL_PATH = "mistralai/Mixtral-8x7B-Instruct-v0.1"
@pytest.fixture(autouse=True)
def v1(run_with_both_engines_lora):
# Simple autouse wrapper to run both engines for each test
# This can be promoted up to conftest.py to run for every
# test in a package
pass
def do_sample(llm: vllm.LLM, lora_path: str, lora_id: int,
prompts: list[str]) -> list[str]:
sampling_params = vllm.SamplingParams(temperature=0, max_tokens=256)
outputs = llm.generate(
prompts,
sampling_params,
lora_request=LoRARequest(str(lora_id), lora_id, lora_path)
if lora_id else None)
# Print the outputs.
generated_texts: list[str] = []
for output in outputs:
prompt = output.prompt
generated_text = output.outputs[0].text.strip()
generated_texts.append(generated_text)
print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
return generated_texts
@pytest.mark.parametrize("tp_size", [4])
def test_mixtral_lora(mixtral_lora_files, tp_size):
"""Original test, the LoRA model has the common target modules, not all"""
if torch.cuda.device_count(
) < tp_size and tp_size > 1 and current_platform.is_cuda_alike():
pytest.skip(f"Not enough GPUs for tensor parallelism {tp_size}")
prompts = [
"[system] Given a target sentence construct the underlying meaning representation\nof the input sentence as a single function with attributes and attribute\nvalues. This function should describe the target string accurately and the\nfunction must be one of the following ['inform', 'request', 'give_opinion',\n'confirm', 'verify_attribute', 'suggest', 'request_explanation',\n'recommend', 'request_attribute'].\n\nThe attributes must be one of the following:\n['name', 'exp_release_date', 'release_year', 'developer', 'esrb', 'rating',\n'genres', 'player_perspective', 'has_multiplayer', 'platforms',\n'available_on_steam', 'has_linux_release', 'has_mac_release', 'specifier'] [/system] [user] Here is the target sentence:\nSpellForce 3 is a pretty bad game. The developer Grimlore Games is clearly a bunch of no-talent hacks, and 2017 was a terrible year for games anyway. [/user] [assistant]", # noqa: E501
"[system] Given a target sentence construct the underlying meaning representation\nof the input sentence as a single function with attributes and attribute\nvalues. This function should describe the target string accurately and the\nfunction must be one of the following ['inform', 'request', 'give_opinion',\n'confirm', 'verify_attribute', 'suggest', 'request_explanation',\n'recommend', 'request_attribute'].\n\nThe attributes must be one of the following:\n['name', 'exp_release_date', 'release_year', 'developer', 'esrb', 'rating',\n'genres', 'player_perspective', 'has_multiplayer', 'platforms',\n'available_on_steam', 'has_linux_release', 'has_mac_release', 'specifier'] [/system] [user] Here is the target sentence:\nI wanted to like Grimlore Games' 2017 entry, but in SpellForce 3 they just didn't get anything right. [/user] [assistant]", # noqa: E501
"[system] Given a target sentence construct the underlying meaning representation\nof the input sentence as a single function with attributes and attribute\nvalues. This function should describe the target string accurately and the\nfunction must be one of the following ['inform', 'request', 'give_opinion',\n'confirm', 'verify_attribute', 'suggest', 'request_explanation',\n'recommend', 'request_attribute'].\n\nThe attributes must be one of the following:\n['name', 'exp_release_date', 'release_year', 'developer', 'esrb', 'rating',\n'genres', 'player_perspective', 'has_multiplayer', 'platforms',\n'available_on_steam', 'has_linux_release', 'has_mac_release', 'specifier'] [/system] [user] Here is the target sentence:\nBioShock is a good role-playing, action-adventure, shooter that released for PlayStation, Xbox, and PC in 2007. It is available on Steam, and it has a Mac release but not a Linux release. [/user] [assistant]", # noqa: E501
]
llm = vllm.LLM(
MODEL_PATH,
enable_lora=True,
max_num_seqs=16,
max_loras=4,
distributed_executor_backend="ray",
tensor_parallel_size=tp_size,
enable_chunked_prefill=True,
)
expected_lora_output = [
"give_opinion(name[SpellForce 3], release_year[2017], developer[Grimlore Games], rating[poor])", # noqa: E501
"give_opinion(name[SpellForce 3], developer[Grimlore Games], release_year[2017], rating[poor])", # noqa: E501
"inform(name[BioShock], release_year[2007], rating[good], genres[action-adventure, role-playing, shooter], platforms[PlayStation, Xbox, PC], available_on_steam[yes], has_linux_release[no], has_mac_release[yes])", # noqa: E501
]
assert do_sample(llm, mixtral_lora_files, lora_id=1,
prompts=prompts) == expected_lora_output
assert do_sample(llm, mixtral_lora_files, lora_id=2,
prompts=prompts) == expected_lora_output