code: def normalize_A(A):
      """
      Computes symmetric normalization of A, dealing with sparse A and batch mode
      automatically.
      :param A: Tensor or SparseTensor with rank k = {2, 3}.
      :return: Tensor or SparseTensor of rank k.
      """
      D = degrees(A)
      D = tf.sqrt(D)[:, None] + K.epsilon()
      perm = (0, 2, 1) if K.ndim(A) == 3 else (1, 0)
      output = (A / D) / ops.transpose(D, perm=perm)
  
      return output
  
imports: import tensorflow
  from tensorflow.keras import backend
  from .None import ops
label_desc: Use image node_id 1 for calling a global function with example usage: normalize_A(A) and returns: output