code: def normalize_minmax(tensor):
      mn = jnp.min(tensor, axis=(-1, -2, -3), keepdims=True)
      mx = jnp.max(tensor, axis=(-1, -2, -3), keepdims=True)
      return (tensor - mn) / jnp.clip(mx - mn, a_min=1e-5)
  
imports: from typing import Tuple, Optional
  import jax
  import jax.numpy
label_desc: Use image node_id 3 for calling a global function with example usage: normalize_minmax(tensor) and returns: unknown