def __init__()

in graphlearn_torch/python/partition/partition_book.py [0:0]

• 9 lines of code
• 6 McCabe index (conditional complexity)

  def __init__(self, partition_ranges: List[Tuple[int, int]], partition_idx: int):
    if not all(r[0] < r[1] for r in partition_ranges):
      raise ValueError("All partition ranges must have start < end")
    if not all(r1[1] == r2[0] for r1, r2 in zip(partition_ranges[:-1], partition_ranges[1:])):
      raise ValueError("Partition ranges must be continuous")

    self.partition_bounds = torch.tensor(
        [end for _, end in partition_ranges], dtype=torch.long)
    self.partition_idx = partition_idx
    self._id2index = OffsetId2Index(partition_ranges[partition_idx][0])