class_docstr: Provides a simple interface for splitting datasets task-wise.
  
  For some learning problems, the training and test datasets should
  have different tasks entirely. This is a different paradigm from the
  usual Splitter, which ensures that split datasets have different
  datapoints, not different tasks.
docstr: Creates Task Splitter object.
docstr_tok: ["Creates","Task","Splitter","object","."]
code: def __init__(self):
      "Creates Task Splitter object."
      pass
  
file_path: deepchem/deepchem/splits/task_splitter.py
imports: import numpy
  from deepchem.data import NumpyDataset
  from deepchem.splits import Splitter
label_desc: Use image node_id 1 to create a new TaskSplitter object from inherited base classes: Splitter with example: obj = TaskSplitter()