modify for vllm 0.12.0

Author: wangyu31577

vllm_omni/benchmarks/datasets.py

@@ -21,7 +21,7 @@
 import numpy as np
 import torch
 import torchaudio
-from vllm.benchmarks.datasets import RandomMultiModalDataset, get_samples
+from vllm.benchmarks.datasets import RandomMultiModalDataset, get_samples, process_image
 
 logger = logging.getLogger(__name__)
 
@@ -207,7 +207,7 @@ def map_config_to_modality(self, config: tuple[int, int, int]) -> str:
             raise ValueError(f"Invalid multimodal item configuration: {config}")
 
 
-def get_omni_samples(args, tokenizer) -> list[SampleRequest]:
+def get_omni_samples(args, tokenizer):
     if args.dataset_name == "random-mm":
         if args.backend not in [
             "openai-chat"]:

vllm_omni/benchmarks/serve.py

@@ -225,6 +225,7 @@ def calculate_metrics(
 
     # Find the time range across all successful requests
     successful_outputs = [output for output in outputs if output.success]
+    failed_outputs = [output for output in outputs if not output.success]
     if successful_outputs:
         min_start_time = min(output.start_time
                              for output in successful_outputs)
@@ -281,6 +282,7 @@ def calculate_metrics(
 
     metrics = MixBenchmarkMetrics(
         completed=completed,
+        failed=len(failed_outputs),
         total_input=total_input,
         total_text_input=total_text_input,
         total_output=sum(actual_output_lens),
@@ -343,13 +345,9 @@ async def benchmark(
     ramp_up_end_rps: Optional[int] = None,
     ready_check_timeout_sec: int = 600,
 ):
-    task_type = (TaskType.EMBEDDING if api_url.endswith("/v1/embeddings") else
-                 TaskType.GENERATION)
+    task_type = TaskType.GENERATION
     if endpoint_type in ASYNC_REQUEST_FUNCS:
-        if task_type == TaskType.EMBEDDING:
-            request_func = ASYNC_REQUEST_FUNCS["openai-embeddings"]
-        else:
-            request_func = ASYNC_REQUEST_FUNCS[endpoint_type]
+        request_func = ASYNC_REQUEST_FUNCS[endpoint_type]
     else:
         raise ValueError(f"Unknown backend: {endpoint_type}")