code: def _get_agg_mat(agg_multiples: List[int]):
      num_leaves = agg_multiples[0]
  
      rows = []
      for agg_multiple in agg_multiples:
          num_rows = num_leaves // agg_multiple
          for i in range(num_rows):
              row = np.zeros(num_leaves)
              row[i * agg_multiple : (i + 1) * agg_multiple] = 1
              rows.append(row)
  
      return np.vstack(rows)
  
imports: from typing import Iterator, List
  import numpy
  import pandas
  from gluonts.core.component import validated
  from gluonts.model.forecast import SampleForecast
  from gluonts.mx import Tensor
label_desc: Use image node_id 7 for calling the TemporalHierarchy obj's underlying member method code with example usage: obj._get_agg_mat(agg_multiples) and returns: np