class_docstr: Abstract base clase which all transduction problems inherit from.
    
class_docstr_tok: ["Abstract","base","clase","which","all","transduction","problems","inherit","from","."]
docstr: Determine the minimum sequence length given a dataset_split.
  
  Args:
    dataset_split: A problem.DatasetSplit.
  
  Returns:
    The minimum length that a sequence can be for this dataset_split.
docstr_tok: ["Determine","the","minimum","sequence","length","given","a","dataset_split",".","Args",":","dataset_split",":","A","problem.DatasetSplit",".","Returns",":","The","minimum","length","that","a","sequence","can","be","for","this","dataset_split","."]
code: def min_sequence_length(self, dataset_split):
      """Determine the minimum sequence length given a dataset_split.
  
      Args:
        dataset_split: A problem.DatasetSplit.
  
      Returns:
        The minimum length that a sequence can be for this dataset_split.
      """
      return {
          problem.DatasetSplit.TRAIN: 8,
          problem.DatasetSplit.EVAL: 65,
          problem.DatasetSplit.TEST: 65,
      }[dataset_split]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import random
  from six.moves import range
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.data_generators import text_problems
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling the TransductionProblem obj's underlying member method code with example usage: obj.min_sequence_length(dataset_split) and returns: dict