code: def __iter__(self):
      return (
          (
              np.random.rand(self.batch_size, 1).astype(np.float32),
              np.random.rand(self.batch_size, 1).astype(np.float32),
          )
          for _ in range(self.length)
      )
  
imports: import numpy
  import torch
  from poutyne import Metric
label_desc: Use image node_id 2 for calling the SomeDataGeneratorUsingStopIteration obj's underlying member method code with example usage: obj.__iter__() and returns: unknown