class_docstr: Base class for input data adapter.
  In order to simplify the training code path, all the input data
  object will be converted to a `generator` if possible.
  The sample usage of this class is like:
  
  ```
  x = list(range(100))
  adapter_cls = [ArrayDataAdapter, ..., ListsOfScalarsDataAdapter]
  applicable_adapters = [cls for cls in adapter_cls if cls.can_handle(x)]
  if len(applicable_adapters) != 1:
    raise ValueError("Expect only one adapter class to handle the input")
  dataset = applicable_adapters[0](x).get_dataset()
  for data in dataset():
    # training
  ```
docstr: Returns whether a new iterator should be created every epoch.
docstr_tok: ["Returns","whether","a","new","iterator","should","be","created","every","epoch","."]
code: def should_recreate_iterator(self):
      """Returns whether a new iterator should be created every epoch."""
      raise NotImplementedError
  
file_path: elegy/elegy/data/data_adapter.py
imports: import abc
  import typing
  import six
label_desc: Use image node_id 9 for calling the DataAdapter obj's underlying member method code with example usage: obj.should_recreate_iterator() without return types