tzhouam
efda9369a8
Reuse upstream weight mapping and multimodal processing, consolidate Omni processor bridges, and trim unused Hunyuan internals. Route no-media kwargs through the active renderer and preserve GLM generation prompt formatting. Validation: 453 CPU tests passed, 7 skipped; processor imports, Ruff, and diff checks passed. GPU and end-to-end CI not rerun. Signed-off-by: tzhouam <tzhouam@connect.ust.hk>
64 lines
2.7 KiB
Python
64 lines
2.7 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
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from typing import Any
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from vllm.renderers import BaseRenderer
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class OmniRenderer:
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"""Delegate tokenization/chat rendering while extending engine-input routing.
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Keep the original renderer's tokenizer, executors, and multimodal caches.
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The upstream pipeline methods run on this adapter so both sync and async
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entrypoints reach the Omni singleton processing below.
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"""
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render_cmpl = BaseRenderer.render_cmpl
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render_cmpl_async = BaseRenderer.render_cmpl_async
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render_chat = BaseRenderer.render_chat
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render_chat_async = BaseRenderer.render_chat_async
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process_for_engine = BaseRenderer.process_for_engine
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process_for_engine_async = BaseRenderer.process_for_engine_async
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_process_enc_dec = BaseRenderer._process_enc_dec
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_process_enc_dec_async = BaseRenderer._process_enc_dec_async
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def __init__(self, renderer: BaseRenderer) -> None:
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self._renderer = renderer
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def __getattr__(self, name: str) -> Any:
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return getattr(self._renderer, name)
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@staticmethod
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def _with_omni_extras(inputs, prompt):
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for key in ("prompt", "cache_salt", "additional_information", "model_intermediate_buffer"):
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if key in prompt:
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inputs[key] = prompt[key]
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return inputs
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def _process_singleton(self, prompt, *, skip_mm_cache: bool = False):
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if "prompt_embeds" not in prompt and "mm_processor_kwargs" in prompt and not prompt.get("multi_modal_data"):
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inputs = self._renderer._process_multimodal(
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prompt["prompt_token_ids"],
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{},
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mm_processor_kwargs=prompt["mm_processor_kwargs"],
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mm_uuids=prompt.get("multi_modal_uuids"),
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skip_mm_cache=skip_mm_cache,
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)
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else:
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inputs = self._renderer._process_singleton(prompt, skip_mm_cache=skip_mm_cache)
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return self._with_omni_extras(inputs, prompt)
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async def _process_singleton_async(self, prompt, *, skip_mm_cache: bool = False):
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if "prompt_embeds" not in prompt and "mm_processor_kwargs" in prompt and not prompt.get("multi_modal_data"):
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inputs = await self._renderer._process_multimodal_async(
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prompt["prompt_token_ids"],
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{},
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mm_processor_kwargs=prompt["mm_processor_kwargs"],
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mm_uuids=prompt.get("multi_modal_uuids"),
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skip_mm_cache=skip_mm_cache,
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)
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else:
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inputs = await self._renderer._process_singleton_async(prompt, skip_mm_cache=skip_mm_cache)
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return self._with_omni_extras(inputs, prompt)
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