code: def reduce_to_2d(arr):
      """Given a np.npdarray with nDims > 2, reduce it to 2d.
  
      It does this by selecting the zeroth coordinate for every dimension greater
      than two.
  
      Args:
        arr: a numpy ndarray of dimension at least 2.
  
      Returns:
        A two-dimensional subarray from the input array.
  
      Raises:
        ValueError: If the argument is not a numpy ndarray, or the dimensionality
          is too low.
      """
      if not isinstance(arr, np.ndarray):
          raise ValueError("reduce_to_2d requires a numpy.ndarray")
  
      ndims = len(arr.shape)
      if ndims < 2:
          raise ValueError(
              "reduce_to_2d requires an array of dimensionality >=2"
          )
      # slice(None) is equivalent to `:`, so we take arr[0,0,...0,:,:]
      slices = ([0] * (ndims - 2)) + [slice(None), slice(None)]
      return arr[tuple(slices)]
  
imports: import textwrap
  import numpy
  from werkzeug import wrappers
  from tensorboard import plugin_util
  from tensorboard.backend import http_util
  from tensorboard.data import provider
  from tensorboard.plugins import base_plugin
  from tensorboard.plugins.text import metadata
label_desc: Use image node_id 3 for calling a global function with example usage: reduce_to_2d(arr) and returns: arr