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

Signed-off-by: Jee Jee Li <pandaleefree@gmail.com>

tests/lora/conftest.py

@@ -173,11 +173,6 @@ def sql_lora_files(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")
 def mixtral_lora_files():
     # Note: this module has incorrect adapter_config.json to test

tests/lora/test_lora_bias_e2e.py

@@ -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