code: def apply_colormap(image: np.ndarray) -> np.ndarray:
      """Apply colormap from grayscale (h, w, 1) to colored (h, w, 3) image."""
      image = image.squeeze(axis=-1)  # (h, w, 1) -> (h, w)
      cmap = get_colormap()  # Get the (256, 3) colormap
      # Normalize uint16 and convert each value to a unique color
      return cmap[image % len(cmap)]
  
imports: from __future__ import annotations
  import csv
  import subprocess
  from typing import Any, List, Optional
  import numpy
  from tensorflow_datasets.core import lazy_imports_lib
  from tensorflow_datasets.core.utils import py_utils
  from tensorflow_datasets.core.utils import resource_utils
  from tensorflow_datasets.core.utils import tf_utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 7 for calling a global function with example usage: apply_colormap(image) and returns: cmap