code: def inject_ls_enc_layer(model, config):
      for i in range(config.num_hidden_layers):
          vit_config = gen_vit_config(config)
          model.vit.encoder.layer[i] = LSVITTransformerEncoderLayer(
              vit_config
          ).cuda()
          model.vit.encoder.layer[i].apply(qat_mode)
  
imports: import time
  import requests
  from PIL import Image
  import torch
  from transformers import ViTFeatureExtractor, ViTForImageClassification, ViTConfig
  import lightseq.inference
  from lightseq.training.ops.pytorch.quantization import qat_mode
  from lightseq.training.ops.pytorch.torch_transformer_layers import TransformerEncoderLayer
  from export.util import parse_args
label_desc: Use image node_id 7 for calling a global function with example usage: inject_ls_enc_layer(model, config) without return types