code: def autodetect_mode(x, a):
      """
      Returns a code that identifies the data mode from the given node features
      and adjacency matrix(s).
      The output of this function can be used as follows:
  
      ```py
      from spektral.layers.ops import modes
      mode = modes.autodetect_mode(x, a)
      if mode == modes.SINGLE:
          print('Single!')
      elif mode == modes.BATCH:
          print('Batch!')
      elif mode == modes.MIXED:
          print('Mixed!')
      ```
  
      :param x: Tensor or SparseTensor representing the node features
      :param a: Tensor or SparseTensor representing the adjacency matrix(s)
      :return: mode of operation as an integer code.
      """
      x_ndim = K.ndim(x)
      a_ndim = K.ndim(a)
      if x_ndim == 2 and a_ndim == 2:
          return SINGLE
      elif x_ndim == 3 and a_ndim == 3:
          return BATCH
      elif x_ndim == 3 and a_ndim == 2:
          return MIXED
      else:
          raise ValueError(
              "Unknown mode for inputs x, a with ranks {} and {}"
              "respectively.".format(x_ndim, a_ndim)
          )
  
imports: import tensorflow
  from tensorflow.keras import backend
label_desc: Use image node_id 3 for calling a global function with example usage: autodetect_mode(x, a) and returns: SINGLE, BATCH, MIXED