85 lines
2.7 KiB
Python
85 lines
2.7 KiB
Python
import asyncio
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from typing import List, Union
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from sglang.srt.managers.multimodal_processors.base_processor import (
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BaseMultimodalProcessor,
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MultimodalSpecialTokens,
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get_global_processor,
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)
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from sglang.srt.models.deepseek_janus_pro import MultiModalityCausalLM
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class JanusProImageProcessor(BaseMultimodalProcessor):
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models = [MultiModalityCausalLM]
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def __init__(self, hf_config, server_args, _processor):
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super().__init__(hf_config, server_args, _processor)
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@staticmethod
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def _process_images_task(images, input_text):
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processor = get_global_processor()
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result = processor.__call__(
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prompt=input_text, images=images, return_tensors="pt"
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)
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return {
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"input_ids": result["input_ids"],
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"pixel_values": result["pixel_values"],
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"images_emb_mask": result["images_emb_mask"],
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"im_start_id": processor.image_start_id,
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"im_end_id": processor.image_end_id,
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"im_token_id": processor.image_id,
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}
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async def _process_images(self, images, input_text):
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if self.executor is not None:
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loop = asyncio.get_event_loop()
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image_inputs = await loop.run_in_executor(
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self.executor,
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JanusProImageProcessor._process_images_task,
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images,
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input_text,
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)
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else:
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image_inputs = self._processor(
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images=images, text=input_text, return_tensors="pt"
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)
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return image_inputs
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async def process_mm_data_async(
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self,
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image_data: List[Union[str, bytes]],
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input_ids,
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request_obj,
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max_req_input_len,
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**kwargs,
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):
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if not image_data:
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return None
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if not isinstance(image_data, list):
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image_data = [image_data]
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base_out = self.load_mm_data(
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input_ids=input_ids,
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image_data=image_data,
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multimodal_tokens=MultimodalSpecialTokens(
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image_token="<image_placeholder>"
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),
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max_req_input_len=max_req_input_len,
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)
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images = base_out.images
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res = await self._process_images(images=images, input_text=base_out.input_text)
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# print(res)
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# print(base_out)
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# print("", res["images_emb_mask"].shape)
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return {
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"input_ids": res["input_ids"].flatten().tolist(),
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"pixel_values": res["pixel_values"],
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"images_emb_mask": res["images_emb_mask"],
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"data_hashes": base_out.mm_data_hashes,
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"im_start_id": res["im_start_id"],
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"im_end_id": res["im_end_id"],
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"im_token_id": res["im_token_id"],
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}
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