code: def rename_key(name):
      # vision encoder
      if "img_encoder.pos_embed" in name:
          name = name.replace(
              "img_encoder.pos_embed",
              "vision_model.embeddings.position_embeddings",
          )
      if "img_encoder.patch_embed.proj" in name:
          name = name.replace(
              "img_encoder.patch_embed.proj",
              "vision_model.embeddings.patch_embeddings.projection",
          )
      if "img_encoder.patch_embed.norm" in name:
          name = name.replace(
              "img_encoder.patch_embed.norm",
              "vision_model.embeddings.layernorm",
          )
      if "img_encoder.layers" in name:
          name = name.replace(
              "img_encoder.layers", "vision_model.encoder.stages"
          )
      if "blocks" in name and "res" not in name:
          name = name.replace("blocks", "layers")
      if "attn" in name and "pre_assign" not in name:
          name = name.replace("attn", "self_attn")
      if "proj" in name and "self_attn" in name and "text" not in name:
          name = name.replace("proj", "out_proj")
      if "pre_assign_attn.attn.proj" in name:
          name = name.replace(
              "pre_assign_attn.attn.proj",
              "pre_assign_attn.attn.out_proj",
          )
      if "norm1" in name:
          name = name.replace("norm1", "layer_norm1")
      if "norm2" in name and "pre_assign" not in name:
          name = name.replace("norm2", "layer_norm2")
      if "img_encoder.norm" in name:
          name = name.replace(
              "img_encoder.norm", "vision_model.layernorm"
          )
      # text encoder
      if "text_encoder.token_embedding" in name:
          name = name.replace(
              "text_encoder.token_embedding",
              "text_model.embeddings.token_embedding",
          )
      if "text_encoder.positional_embedding" in name:
          name = name.replace(
              "text_encoder.positional_embedding",
              "text_model.embeddings.position_embedding.weight",
          )
      if "text_encoder.transformer.resblocks." in name:
          name = name.replace(
              "text_encoder.transformer.resblocks.",
              "text_model.encoder.layers.",
          )
      if "ln_1" in name:
          name = name.replace("ln_1", "layer_norm1")
      if "ln_2" in name:
          name = name.replace("ln_2", "layer_norm2")
      if "c_fc" in name:
          name = name.replace("c_fc", "fc1")
      if "c_proj" in name:
          name = name.replace("c_proj", "fc2")
      if "text_encoder" in name:
          name = name.replace("text_encoder", "text_model")
      if "ln_final" in name:
          name = name.replace("ln_final", "final_layer_norm")
      # projection layers
      if "img_projector.linear_hidden." in name:
          name = name.replace(
              "img_projector.linear_hidden.", "visual_projection."
          )
      if "img_projector.linear_out." in name:
          name = name.replace(
              "img_projector.linear_out.", "visual_projection.3."
          )
      if "text_projector.linear_hidden" in name:
          name = name.replace(
              "text_projector.linear_hidden", "text_projection"
          )
      if "text_projector.linear_out" in name:
          name = name.replace(
              "text_projector.linear_out", "text_projection.3"
          )
  
      return name
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/groupvit/convert_groupvit_nvlab_to_hf.py
imports: import argparse
  import torch
  from PIL import Image
  import requests
  from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
label_desc: Use image node_id 1 for calling a global function with example usage: rename_key(name) and returns: name