class_docstr: The class contains methods for iterating over a dataset for ranking in training, validation and test mode.
code: def split(
      self, *args, len_valid=1000, len_test=1000, **kwargs
  ) -> None:
      if len(self.valid) == 0 and len_valid != 0:
          self.random.shuffle(self.train)
          self.valid = self.train[-len_valid:]
          self.train = self.train[:-len_valid]
      if len(self.test) == 0 and len_test != 0:
          self.random.shuffle(self.train)
          self.test = self.train[-len_test:]
          self.train = self.train[:-len_test]
  
imports: from logging import getLogger
  from typing import Dict, List, Tuple
  from deeppavlov.core.common.registry import register
  from deeppavlov.core.data.data_learning_iterator import DataLearningIterator
label_desc: Use image node_id 1 for calling the SiameseIterator obj's underlying member method code with example usage: obj.split() without return types