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bed9ad54cb |
@@ -23,7 +23,6 @@ from vllm import PromptType, RequestOutput
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from vllm.inputs import TextPrompt
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from vllm.inputs.preprocess import InputPreprocessor
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from vllm.logger import init_logger
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from vllm.outputs import RequestOutput
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from vllm.sampling_params import SamplingParams
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from vllm.tokenizers import TokenizerLike
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from vllm.usage.usage_lib import UsageContext
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@@ -1424,7 +1423,7 @@ async def _stage_worker_async(
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batch_request_ids, batch_request_outputs, _gen_ms_list, batch_metrics
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):
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try:
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r_outputs = [output_strip(output, omni_stage)]
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r_outputs = [output]
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use_shm, payload = maybe_dump_to_shm(r_outputs, shm_threshold_bytes)
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if use_shm:
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out_q.put(
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@@ -1510,23 +1509,3 @@ def make_stage_stats(_agg_total_tokens: int, _agg_total_gen_time_ms: float):
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from vllm_omni.entrypoints.log_utils import StageStats
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return StageStats(total_token=_agg_total_tokens, total_gen_time=_agg_total_gen_time_ms)
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def output_strip(r_output: RequestOutput, omni_stage: OmniStage):
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if omni_stage.final_output and omni_stage.final_output_type != "text":
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return r_output
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if getattr(r_output, "finished", False):
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return r_output
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mm_output = getattr(r_output, "multimodal_output", None)
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if mm_output is not None:
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r_output.multimodal_output = {}
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outputs = getattr(r_output, "outputs", None)
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if outputs is not None:
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for out in outputs:
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if getattr(out, "multimodal_output", None):
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out.multimodal_output = {}
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return r_output
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