code: def get_tf_augment(augment, size=32):
      aug = dict(
          x=lambda **kw: kw,
          s=lambda image, **kw: dict(
              image=shift(image, size >> 3), **kw
          ),
          sc=lambda image, **kw: dict(
              image=cutout(shift(image, size >> 3), size >> 1), **kw
          ),
          sm=lambda image, **kw: dict(
              image=mirror(shift(image, size >> 3)), **kw
          ),
          smc=lambda image, **kw: dict(
              image=cutout(mirror(shift(image, size >> 3)), size >> 1),
              **kw,
          ),
      )
      return lambda x: aug[augment](**x)
  
imports: import tensorflow
label_desc: Use image node_id 5 for calling a global function with example usage: get_tf_augment(augment, size) and returns: function