class_docstr: Generates (support, test) pairs for episodic training.
  
  Precomputes all (support, test) pairs at construction. Allows to reduce
  overhead from computation.
class_docstr_tok: ["Generates","(","support",",","test",")","pairs","for","episodic","training",".","Precomputes","all","(","support",",","test",")","pairs","at","construction",".","Allows","to","reduce","overhead","from","computation","."]
code: def __iter__(self):
      return self
  
imports: import logging
  import time
  import numpy
  from deepchem.data import NumpyDataset
label_desc: Use image node_id 2 for calling the EpisodeGenerator obj's underlying member method code with example usage: obj.__iter__() and returns: self