text: import types
  
  import torch
  
  import timm as outlet
  
  
  def feature_strides():
  	return [8, 16, 32]
  
  def feature_channels(self):
  	return self.feature_info.channels()
  
  
  def Timm(**kwargs):
  	model_name = kwargs.pop('model')
  	pretrained = kwargs.pop('pretrained')
  	print(
  		"Loading \"%s\" model from `pytorch-image-models` collection..." %
  		model_name)
  	m = outlet.create_model(
  		model_name,
  		pretrained=pretrained,
  		features_only=True,
  		out_indices=(2, 3, 4),
  		#  feature_location="bottleneck",
  		**kwargs)
  
  	m.feature_strides = feature_strides
  	m.feature_channels = types.MethodType(feature_channels, m)
  
  	return m
  