Optmize unit test

Signed-off-by: Jee Jee Li <[email protected]>

Author: jeejeelee

tests/lora/test_ultravox.py

@@ -9,8 +9,6 @@
 
 from vllm.lora.request import LoRARequest
 
-from ..models.utils import check_outputs_equal
-
 ULTRAVOX_MODEL_NAME = "fixie-ai/ultravox-v0_3"
 LLMA_MODEL_NAME = "meta-llama/Llama-3.1-8B-Instruct"
 
@@ -61,6 +59,9 @@ def _get_prompt(audio_count, question, placeholder, model_name) -> str:
 
 
 def test_ultravox_lora(vllm_runner):
+    """
+    TODO: Train an Ultravox LoRA instead of using a Llama LoRA.
+    """
     llama3_1_8b_chess_lora = llama3_1_8b_chess_lora_path()
     with TemporaryDirectory() as temp_ultravox_lora_dir:
         llama3_1_8b_ultravox_chess_lora = mk_llama3_1_8b_ultravox_chess_lora(
@@ -97,34 +98,11 @@ def test_ultravox_lora(vllm_runner):
             dtype="bfloat16",
             max_model_len=4096,
     ) as vllm_model:
-        llama_outputs_no_lora: List[Tuple[List[int],
-                                          str]] = vllm_model.generate_greedy(
-                                              [
-                                                  _get_prompt(
-                                                      0, PROMPT,
-                                                      VLLM_PLACEHOLDER,
-                                                      LLMA_MODEL_NAME)
-                                              ],
-                                              256,
-                                          )
-        llama_outputs: List[Tuple[List[int],
-                                  str]] = vllm_model.generate_greedy(
-                                      [
-                                          _get_prompt(0, PROMPT,
-                                                      VLLM_PLACEHOLDER,
-                                                      LLMA_MODEL_NAME)
-                                      ],
-                                      256,
-                                      lora_request=LoRARequest(
-                                          str(1), 1, llama3_1_8b_chess_lora),
-                                  )
-
-    check_outputs_equal(
-        outputs_0_lst=ultravox_outputs,
-        outputs_1_lst=llama_outputs,
-        name_0="ultravox",
-        name_1="llama",
-    )
+        llama_outputs_no_lora: List[Tuple[List[int], str]] = (
+            vllm_model.generate_greedy(
+                [_get_prompt(0, PROMPT, VLLM_PLACEHOLDER, LLMA_MODEL_NAME)],
+                256,
+            ))
 
     _, llama_no_lora_str = llama_outputs_no_lora[0]
     _, ultravox_str = ultravox_outputs[0]