code: def __init__(self, config, **kwargs):
      self.feature_extractor = None
      self.config = config
  
      if config.center_crop:
          self.image_processor = Compose(
              [
                  Resize(256, interpolation=InterpolationMode.BICUBIC),
                  CenterCrop(config.image_size),
                  convert_to_rgb,
                  ToTensor(),
                  Normalize(
                      mean=IMAGENET_MEAN,
                      std=IMAGENET_STD,
                  ),
              ]
          )
      else:
          self.image_processor = Compose(
              [
                  RandomResizedCrop(
                      config.image_size,
                      scale=(0.8, 1),
                      interpolation=InterpolationMode.BICUBIC,
                  ),
                  convert_to_rgb,
                  ToTensor(),
                  Normalize(
                      mean=IMAGENET_MEAN,
                      std=IMAGENET_STD,
                  ),
              ]
          )
  
      self.tokenizer = AutoTokenizer.from_pretrained(
          config.tokenizer_name_or_path,
          additional_special_tokens=["<|im_end|>"],
      )
      self.num_image_latents = config.image_pooler_num_latents
  
imports: from typing import List, Optional, Tuple, Union
  import torch
  import torch.nn.functional
  from torch import nn
  from torchvision.transforms import *
  from transformers import AutoConfig, AutoTokenizer
  from transformers.configuration_utils import PretrainedConfig
  from transformers.modeling_outputs import CausalLMOutputWithPast
  from transformers.modeling_utils import PreTrainedModel
  from transformers.models.auto.modeling_auto import AutoModel, AutoModelForCausalLM
  from transformers.processing_utils import ProcessorMixin
  from transformers.tokenization_utils_base import BatchEncoding
  from uform.models import VisualEncoder
label_desc: Use image node_id 1 to create a new VLMProcessor object from inherited base classes: ProcessorMixin with example: obj = VLMProcessor(config)