78 lines
2.5 KiB
Python
78 lines
2.5 KiB
Python
from functools import lru_cache
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from typing import TYPE_CHECKING, Any, Dict, Optional
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import numpy as np
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from vllm.inputs.registry import InputContext
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from vllm.logger import init_logger
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from vllm.transformers_utils.processor import get_video_processor
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from vllm.transformers_utils.tokenizer import get_tokenizer
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from vllm.utils import is_list_of
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from .base import MultiModalData
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from .image import ImagePlugin
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from .inputs import MultiModalKwargs, VideoItem
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if TYPE_CHECKING:
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from vllm.config import ModelConfig
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logger = init_logger(__name__)
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cached_get_video_processor = lru_cache(get_video_processor)
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cached_get_tokenizer = lru_cache(get_tokenizer)
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class VideoPlugin(ImagePlugin):
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"""Plugin for video data."""
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def get_data_key(self) -> str:
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return "video"
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def _get_hf_video_processor(
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self,
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model_config: "ModelConfig",
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mm_processor_kwargs: Optional[Dict[str, Any]] = None,
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):
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if mm_processor_kwargs is None:
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mm_processor_kwargs = {}
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return cached_get_video_processor(
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model_config.model,
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trust_remote_code=model_config.trust_remote_code,
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**mm_processor_kwargs)
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def _default_input_mapper(
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self,
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ctx: InputContext,
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data: MultiModalData[VideoItem],
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**mm_processor_kwargs,
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) -> MultiModalKwargs:
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model_config = ctx.model_config
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if isinstance(data, list) and len(data) == 1:
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data = data[0] # type: ignore
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if isinstance(data, np.ndarray) or is_list_of(data, np.ndarray):
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video_processor = self._get_hf_video_processor(
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model_config,
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mm_processor_kwargs,
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)
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if video_processor is None:
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raise RuntimeError("No HuggingFace processor is available "
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"to process the video object")
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try:
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# NOTE: Similar to image; it may be a good idea to filter and
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# pass mm_processor_kwargs here too, but for now we don't to
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# avoid extra complexity if the initializer and preprocess
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# signatures of the processor don't align
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batch_data = video_processor(data, return_tensors="pt").data
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except Exception:
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logger.error("Failed to process video (%s)", data)
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raise
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return MultiModalKwargs(batch_data)
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raise TypeError(f"Invalid video type: {type(data)}")
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def _default_max_multimodal_tokens(self, ctx: InputContext) -> int:
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return 4096
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