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[CI/Build] Delete LoRA bias test (#14849)

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Signed-off-by: Jee Jee Li <pandaleefree@gmail.com>
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Jee Jee Li 2025-03-15 13:09:25 +08:00 committed by GitHub
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commit e0fdfa1608
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2 changed files with 0 additions and 68 deletions
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5
tests/lora/conftest.py
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@ -173,11 +173,6 @@ def sql_lora_files(sql_lora_huggingface_id):
return snapshot_download(repo_id=sql_lora_huggingface_id) return snapshot_download(repo_id=sql_lora_huggingface_id)
@pytest.fixture(scope="session")
def lora_bias_files():
return snapshot_download(repo_id="followumesh/granite-3b-lora8-bias")
@pytest.fixture(scope="session") @pytest.fixture(scope="session")
def mixtral_lora_files(): def mixtral_lora_files():
# Note: this module has incorrect adapter_config.json to test # Note: this module has incorrect adapter_config.json to test

63
tests/lora/test_lora_bias_e2e.py
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@ -1,63 +0,0 @@
# SPDX-License-Identifier: Apache-2.0
import pytest
import vllm
from vllm.lora.request import LoRARequest
MODEL_PATH = "ibm-granite/granite-3b-code-base"
def do_sample(llm: vllm.LLM, lora_path: str, lora_id: int) -> list[str]:
prompts = [
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE candidate (people_id VARCHAR, unsure_rate INTEGER); CREATE TABLE people (sex VARCHAR, people_id VARCHAR)\n\n question: which gender got the highest average uncertain ratio. [/user] [assistant]", # noqa: E501
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_28138035_4 (womens_doubles VARCHAR, mens_singles VARCHAR)\n\n question: Name the women's doubles for werner schlager [/user] [assistant]" # noqa: E501
]
sampling_params = vllm.SamplingParams(temperature=0,
max_tokens=256,
stop=["[/assistant]"])
outputs = llm.generate(
prompts,
sampling_params,
lora_request=LoRARequest(str(lora_id), lora_id, lora_path)
if lora_id else None)
generated_texts: list[str] = []
for output in outputs:
generated_text = output.outputs[0].text
generated_texts.append(generated_text)
return generated_texts
@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
# Skipping for V1 for now as we are hitting,
# "Head size 80 is not supported by FlashAttention." error.
@pytest.mark.skip_v1
@pytest.mark.parametrize("lora_bias", [True])
@pytest.mark.parametrize("fully_sharded", [True, False])
def test_lora_bias(lora_bias_files: str, lora_bias: bool, fully_sharded: bool):
llm = vllm.LLM(MODEL_PATH,
enable_lora=True,
max_num_seqs=16,
max_lora_rank=8,
max_loras=1,
enable_lora_bias=lora_bias,
tensor_parallel_size=1,
fully_sharded_loras=fully_sharded)
print("lora adapter created")
output1 = do_sample(llm, lora_bias_files, lora_id=0)
print("lora")
output2 = do_sample(llm, lora_bias_files, lora_id=1)
if lora_bias:
assert output1 != output2
else:
assert output1 == output2