message: Add Dataset support information to pydoc of Estimator functions.
diff: @@ -262,9 +262,19 @@ class Estimator(object):
  """Trains a model given training data input_fn.
  Args:
  - input_fn: Input function returning a tuple of:
  - features - `Tensor` or dictionary of string feature name to `Tensor`.
  - labels - `Tensor` or dictionary of `Tensor` with labels.
  + input_fn: A function that provides input data for training as minibatches.
  + See @{$get_started/premade_estimators#create_input_functions} for more
  + information. The function should construct and return one of
  + the following:
  +
  + * A 'tf.data.Dataset' object: Outputs of `Dataset` object must be a
  + tuple (features, labels) with same constraints as below.
  + * A tuple (features, labels): Where features is a `Tensor` or a
  + dictionary of string feature name to `Tensor` and labels is a
  + `Tensor` or a dictionary of string label name to `Tensor`. Both
  + features and labels are consumed by `model_fn`. They should satisfy
  + the expectation of `model_fn` from inputs.
  +
  hooks: List of `SessionRunHook` subclass instances. Used for callbacks
  inside the training loop.
  steps: Number of steps for which to train model. If `None`, train forever
  @@ -332,10 +342,19 @@ class Estimator(object):
  `StopIteration`).
  Args:
  - input_fn: Input function returning a tuple of:
  - features - Dictionary of string feature name to `Tensor` or
  - `SparseTensor`.
  - labels - `Tensor` or dictionary of `Tensor` with labels.
  + input_fn: A function that constructs the input data for evaluation.
  + See @{$get_started/premade_estimators#create_input_functions} for more
  + information. The function should construct and return one of
  + the following:
  +
  + * A 'tf.data.Dataset' object: Outputs of `Dataset` object must be a
  + tuple (features, labels) with same constraints as below.
  + * A tuple (features, labels): Where features is a `Tensor` or a
  + dictionary of string feature name to `Tensor` and labels is a
  + `Tensor` or a dictionary of string label name to `Tensor`. Both
  + features and labels are consumed by `model_fn`. They should satisfy
  + the expectation of `model_fn` from inputs.
  +
  steps: Number of steps for which to evaluate model. If `None`, evaluates
  until `input_fn` raises an end-of-input exception.
  hooks: List of `SessionRunHook` subclass instances. Used for callbacks
  @@ -382,11 +401,20 @@ class Estimator(object):
  """Yields predictions for given features.
  Args:
  - input_fn: Input function returning features which is a dictionary of
  - string feature name to `Tensor` or `SparseTensor`. If it returns a
  - tuple, first item is extracted as features. Prediction continues until
  - `input_fn` raises an end-of-input exception (`OutOfRangeError` or
  + input_fn: A function that constructs the features. Prediction continues
  + until `input_fn` raises an end-of-input exception (`OutOfRangeError` or
  `StopIteration`).
  + See @{$get_started/premade_estimators#create_input_functions} for more
  + information. The function should construct and return one of
  + the following:
  +
  + * A 'tf.data.Dataset' object: Outputs of `Dataset` object must have
  + same constraints as below.
  + * features: A `Tensor` or a dictionary of string feature name to
  + `Tensor`. features are consumed by `model_fn`. They should satisfy
  + the expectation of `model_fn` from inputs.
  + * A tuple, in which case the first item is extracted as features.
  +
  predict_keys: list of `str`, name of the keys to predict. It is used if
  the `EstimatorSpec.predictions` is a `dict`. If `predict_keys` is used
  then rest of the predictions will be filtered from the dictionary. If
  