[Misc] refactor neuron_multimodal and profiling (vllm-project#19397)

Signed-off-by: reidliu41 <reid201711@gmail.com>
Co-authored-by: reidliu41 <reid201711@gmail.com>

Author: reidliu41

examples/offline_inference/neuron_multimodal.py

@@ -64,7 +64,7 @@ def print_outputs(outputs):
         print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
 
 
-if __name__ == "__main__":
+def main():
     assert (
         len(PROMPTS) == len(IMAGES) == len(SAMPLING_PARAMS)
     ), f"""Text, image prompts and sampling parameters should have the 
@@ -104,3 +104,7 @@ def print_outputs(outputs):
     # test batch-size = 4
     outputs = llm.generate(batched_inputs, batched_sample_params)
     print_outputs(outputs)
+
+
+if __name__ == "__main__":
+    main()

examples/offline_inference/profiling_tpu/profiling.py

@@ -70,7 +70,7 @@ def run_to_completion():
     return
 
 
-if __name__ == "__main__":
+def parse_args():
     parser = FlexibleArgumentParser(
         description="Benchmark the latency of processing a single batch of "
         "requests till completion."
@@ -102,5 +102,9 @@ def run_to_completion():
     )
 
     parser = EngineArgs.add_cli_args(parser)
-    args = parser.parse_args()
+    return parser.parse_args()
+
+
+if __name__ == "__main__":
+    args = parse_args()
     main(args)