def get_network_fn(name, num_classes, weight_decay=0.0, is_training=False):
 if (name not in networks_map):
  raise ValueError(('Name of network unknown %s' % name))
 arg_scope = arg_scopes_map[name](weight_decay=weight_decay)
 func = networks_map[name]
 @functools.wraps(func)
 def network_fn(images):
  with slim.arg_scope(arg_scope):
   return func(images, num_classes, is_training=is_training)
 if hasattr(func, 'default_image_size'):
  network_fn.default_image_size = func.default_image_size
 return network_fn

def get_network_fn ( name , num_classes , weight_decay = 0.0 , is_training = False ) : if ( name not in networks_map ) : raise ValueError ( ( 'Name of network unknown %s' % name ) ) arg_scope = arg_scopes_map [ name ] ( weight_decay = weight_decay ) func = networks_map [ name ] @ functools . wraps ( func ) def network_fn ( images ) : with slim . arg_scope ( arg_scope ) : return func ( images , num_classes , is_training = is_training ) if hasattr ( func , 'default_image_size' ) : network_fn . default_image_size = func . default_image_size return network_fn
returns a network_fn such as logits .