code: def from_pretrained(
      cls,
      pretrained_model_name_or_path,
      cache_dir=None,
      force_download: bool = False,
      local_files_only: bool = False,
      token=None,
      revision: str = "main",
      **kwargs,
  ):
      config = AutoConfig.from_pretrained(pretrained_model_name_or_path)
      return cls(config)
  
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 5 for calling the VLMProcessor obj's underlying member method code with example usage: obj.from_pretrained(cls, pretrained_model_name_or_path, cache_dir, force_download, local_files_only, token, revision) and returns: cls