class_docstr: An interface for a phase that produces datasets.
class_docstr_tok: ["An","interface","for","a","phase","that","produces","datasets","."]
docstr: Initializes a Phase.
  
  Args:
    storage: A `Storage` instance.
docstr_tok: ["Initializes","a","Phase",".","Args",":","storage",":","A","`","Storage","`","instance","."]
code: def __init__(self, storage: Storage = InMemoryStorage()):
      """Initializes a Phase.
  
      Args:
        storage: A `Storage` instance.
      """
  
      super().__init__(storage)
      self._train_dataset = None
      self._eval_dataset = None
  
imports: import abc
  from typing import Iterable, Iterator, Optional
  from adanet.experimental.storages.in_memory_storage import InMemoryStorage
  from adanet.experimental.storages.storage import Storage
  from adanet.experimental.work_units.work_unit import WorkUnit
  import tensorflow.compat.v2
label_desc: Use image node_id 1 to create a new DatasetProvider object from inherited base classes: Phase, abc with example: obj = DatasetProvider(storage)