class_docstr: A data generator for use with the Watch Your Step algorithm [1]. It calculates and returns the first ``num_powers``
  of the adjacency matrix row by row.
  
  .. seealso::
  
     Model using this generator: :class:`.WatchYourStep`.
  
     Example using this generator: `unsupervised representation learning <https://stellargraph.readthedocs.io/en/stable/demos/embeddings/watch-your-step-embeddings.html>`__
  
  Args:
      G (StellarGraph): a machine-learning StellarGraph-type graph
      num_powers (int): the number of adjacency powers to calculate. Defaults
          to 10 as this value was found to perform well by the authors of the paper.
      weighted (bool, optional): if True, use the edge weights from ``G``; if False, treat the
          graph as unweighted.
code: def num_batch_dims(self):
      return 1
  
file_path: stellargraph/stellargraph/mapper/adjacency_generators.py
imports: import tensorflow
  from tensorflow.keras import backend
  import numpy
  from ..core import StellarGraph
  from ..core.validation import require_integer_in_range
  from ..core.utils import normalize_adj
  from .base import Generator
label_desc: Use image node_id 2 for calling the AdjacencyPowerGenerator obj's underlying member method code with example usage: obj.num_batch_dims() and returns: int