code: def repvit_m1_5(pretrained=False, **kwargs):
      """
      Constructs a RepViT-M1.5 model
      """
      model_args = dict(
          embed_dim=(64, 128, 256, 512), depth=(4, 4, 24, 4)
      )
      return _create_repvit(
          "repvit_m1_5",
          pretrained=pretrained,
          **dict(model_args, **kwargs),
      )
  
imports: import torch.nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from ._registry import register_model, generate_default_cfgs
  from ._builder import build_model_with_cfg
  from timm.layers import SqueezeExcite, trunc_normal_, to_ntuple, to_2tuple
  from ._manipulate import checkpoint_seq
  import torch
label_desc: Use image node_id 9 for calling a global function with example usage: repvit_m1_5(pretrained) and returns: _create_repvit