class_docstr: Wraps inputs into a Keras Sequence to allow Keras models to predict on
  arbitrary inputs which may be out of memory.
code: def __len__(self):
      return int(np.ceil(self.X.shape[0] / float(self.batch_size)))
  
file_path: ivis/ivis/data/generators/generators.py
imports: import tensorflow
  import numpy
  from scipy.sparse import issparse
label_desc: Use image node_id 2 for calling the KerasSequence obj's underlying member method code with example usage: obj.__len__() and returns: int