class_docstr: Dataset to partition a given dataset.
  
  Partition a given `dataset`, according to the specified `partitions`. Use
  the method `select()` to select the current partition in use.
  
  The `partitions` is a dictionary where a key is a user-chosen string
  naming the partition, and value is a number representing the weight (as a
  number between 0 and 1) or the size (in number of samples) of the
  corresponding partition.
  
  Partioning is achieved linearly (no shuffling). See `ShuffleDataset` if you
  want to shuffle the dataset before partitioning.
  
  Args:
      dataset (Dataset): Dataset to be split.
      partitions (dict): Dictionary where key is a user-chosen string
          naming the partition, and value is a number representing the weight
          (as a number between 0 and 1) or the size (in number of samples)
          of the corresponding partition.
      initial_partition (str, optional): Initial parition to be selected.
docstr: Select the parition.
  
  Args:
      partition (str): Partition to be selected.
docstr_tok: ["Select","the","parition",".","Args",":","partition","(","str",")",":","Partition","to","be","selected","."]
code: def select(self, partition):
      """
      Select the parition.
  
      Args:
          partition (str): Partition to be selected.
      """
      self.current_partition_idx = self.partition_index[partition]
  
imports: from .dataset import Dataset
  import numpy
label_desc: Use image node_id 2 for calling the SplitDataset obj's underlying member method code with example usage: obj.select(partition) without return types