code: def create_body(model, n_in=3, pretrained=True, cut=None):
      "Cut off the body of a typically pretrained `arch` as determined by `cut`"
      _update_first_layer(model, n_in, pretrained)
      if cut is None:
          ll = list(enumerate(model.children()))
          cut = next(i for i, o in reversed(ll) if has_pool_type(o))
      return cut_model(model, cut)
  
imports: from __future__ import annotations
  from packaging.version import parse
  from ..basics import *
  from .core import *
  from .data import *
  from .augment import *
  from .None import models
  import torchvision
  from ..callback.hook import num_features_model
label_desc: Use image node_id 7 for calling a global function with example usage: create_body(model, n_in, pretrained, cut) and returns: cut_model