class_docstr: Base class for generating bucket keys.
class_docstr_tok: ["Base","class","for","generating","bucket","keys","."]
docstr: Generate bucket keys based on the lengths of sequences and number of buckets.
  
  Parameters
  ----------
  max_lengths
      Maximum of lengths of sequences.
  min_lengths
      Minimum of lengths of sequences.
  num_buckets
      Number of buckets
  
  Returns
  -------
  bucket_keys
      A list including the keys of the buckets.
docstr_tok: ["Generate","bucket","keys","based","on","the","lengths","of","sequences","and","number","of","buckets",".","Parameters","--","--","--","--","--","max_lengths","Maximum","of","lengths","of","sequences",".","min_lengths","Minimum","of","lengths","of","sequences",".","num_buckets","Number","of","buckets","Returns","--","--","--","-","bucket_keys","A","list","including","the","keys","of","the","buckets","."]
code: def __call__(
      self,
      max_lengths: Union[int, Sequence[int]],
      min_lengths: Union[int, Sequence[int]],
      num_buckets: int,
  ) -> List[int]:
      """Generate bucket keys based on the lengths of sequences and number of buckets.
  
      Parameters
      ----------
      max_lengths
          Maximum of lengths of sequences.
      min_lengths
          Minimum of lengths of sequences.
      num_buckets
          Number of buckets
  
      Returns
      -------
      bucket_keys
          A list including the keys of the buckets.
      """
      raise NotImplementedError
  
imports: import math
  import random
  import warnings
  import numpy
  import abc
  import logging
  from typing import Union, Sequence, Optional, List
  from ..base import INT_TYPES
label_desc: Use image node_id 1 for calling the BucketScheme obj's underlying member method code with example usage: obj.__call__(max_lengths, min_lengths, num_buckets) without return types