@deprecated_arg_values('2016-09-23', "The signature of the input_fn accepted by export is changing to be consistent with what's used by tf.Learn Estimator's train/evaluate. input_fn (and in most cases, input_feature_key) will both become required args.", input_fn=None)
def __init__(self, every_n_steps, export_dir, input_fn=None, input_feature_key=None, exports_to_keep=5, signature_fn=None, default_batch_size=1):
    "Initializes ExportMonitor.\n\n    Args:\n      every_n_steps: Run monitor every N steps.\n      export_dir: str, folder to export.\n      input_fn: A function that takes no argument and returns a tuple of\n        (features, targets), where features is a dict of string key to `Tensor`\n        and targets is a `Tensor` that's currently not used (and so can be\n        `None`).\n      input_feature_key: String key into the features dict returned by\n        `input_fn` that corresponds to the raw `Example` strings `Tensor` that\n        the exported model will take as input. Can only be `None` if you're\n        using a custom `signature_fn` that does not use the first arg\n        (examples).\n      exports_to_keep: int, number of exports to keep.\n      signature_fn: Function that returns a default signature and a named\n        signature map, given `Tensor` of `Example` strings, `dict` of `Tensor`s\n        for features and `dict` of `Tensor`s for predictions.\n      default_batch_size: Default batch size of the `Example` placeholder.\n\n    Raises:\n      ValueError: If `input_fn` and `input_feature_key` are not both defined or\n        are not both `None`.\n    "
    super(ExportMonitor, self).__init__(every_n_steps=every_n_steps)
    self._export_dir = export_dir
    self._input_fn = input_fn
    self._input_feature_key = input_feature_key
    self._use_deprecated_input_fn = (input_fn is None)
    self._exports_to_keep = exports_to_keep
    self._signature_fn = signature_fn
    self._default_batch_size = default_batch_size
    self._last_export_dir = None
Initializes ExportMonitor.

Args:
  every_n_steps: Run monitor every N steps.
  export_dir: str, folder to export.
  input_fn: A function that takes no argument and returns a tuple of
    (features, targets), where features is a dict of string key to `Tensor`
    and targets is a `Tensor` that's currently not used (and so can be
    `None`).
  input_feature_key: String key into the features dict returned by
    `input_fn` that corresponds to the raw `Example` strings `Tensor` that
    the exported model will take as input. Can only be `None` if you're
    using a custom `signature_fn` that does not use the first arg
    (examples).
  exports_to_keep: int, number of exports to keep.
  signature_fn: Function that returns a default signature and a named
    signature map, given `Tensor` of `Example` strings, `dict` of `Tensor`s
    for features and `dict` of `Tensor`s for predictions.
  default_batch_size: Default batch size of the `Example` placeholder.

Raises:
  ValueError: If `input_fn` and `input_feature_key` are not both defined or
    are not both `None`.
@deprecated_arg_values('2016-09-23', "The signature of the input_fn accepted by export is changing to be consistent with what's used by tf.Learn Estimator's train/evaluate. input_fn (and in most cases, input_feature_key) will both become required args.", input_fn=None)
def __init__(self, every_n_steps, export_dir, input_fn=None, input_feature_key=None, exports_to_keep=5, signature_fn=None, default_batch_size=1):
    "Initializes ExportMonitor.\n\n    Args:\n      every_n_steps: Run monitor every N steps.\n      export_dir: str, folder to export.\n      input_fn: A function that takes no argument and returns a tuple of\n        (features, targets), where features is a dict of string key to `Tensor`\n        and targets is a `Tensor` that's currently not used (and so can be\n        `None`).\n      input_feature_key: String key into the features dict returned by\n        `input_fn` that corresponds to the raw `Example` strings `Tensor` that\n        the exported model will take as input. Can only be `None` if you're\n        using a custom `signature_fn` that does not use the first arg\n        (examples).\n      exports_to_keep: int, number of exports to keep.\n      signature_fn: Function that returns a default signature and a named\n        signature map, given `Tensor` of `Example` strings, `dict` of `Tensor`s\n        for features and `dict` of `Tensor`s for predictions.\n      default_batch_size: Default batch size of the `Example` placeholder.\n\n    Raises:\n      ValueError: If `input_fn` and `input_feature_key` are not both defined or\n        are not both `None`.\n    "
    super(ExportMonitor, self).__init__(every_n_steps=every_n_steps)
    self._export_dir = export_dir
    self._input_fn = input_fn
    self._input_feature_key = input_feature_key
    self._use_deprecated_input_fn = (input_fn is None)
    self._exports_to_keep = exports_to_keep
    self._signature_fn = signature_fn
    self._default_batch_size = default_batch_size
    self._last_export_dir = None