code: def copy_encoder(hf_encoder, pt_model):
      # copy  embeds
      hf_encoder.embeddings.token_embedding.weight = (
          pt_model.token_embedding.weight
      )
      hf_encoder.embeddings.position_embedding.weight.data = (
          pt_model.positional_embedding
      )
  
      # copy layer norm
      copy_linear(hf_encoder.final_layer_norm, pt_model.ln_final)
  
      # copy hidden layers
      copy_layers(
          hf_encoder.encoder.layers, pt_model.transformer.resblocks
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/clip/convert_clip_original_pytorch_to_hf.py
imports: import argparse
  import torch
  from clip import load
  from transformers import CLIPConfig, CLIPModel
label_desc: Use image node_id 6 for calling a global function with example usage: copy_encoder(hf_encoder, pt_model) without return types