message: Update TrainingSpec and EvalSpec pydoc
  Bring TrainingSpec and EvalSpec pydoc in line with pydoc of estimator.train() and evaluate()
diff: @@ -128,9 +128,16 @@ class TrainSpec(
  """Creates a validated `TrainSpec` instance.
  Args:
  - input_fn: Training 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 @{$get_started/premade_estimators#create_input_functions} for more
  + information. The function should construct and return one of
  + the following:
  + * A 'tf.data.Dataset' object: Outputs of `Dataset` object must be a
  + tuple (features, labels) with same constraints as below.
  + * A tuple (features, labels): Where features is a `Tensor` or a
  + dictionary of string feature name to `Tensor` and labels is a
  + `Tensor` or a dictionary of string label name to `Tensor`.
  +
  max_steps: Int. Positive number of total steps for which to train model.
  If `None`, train forever. The training `input_fn` is not expected to
  generate `OutOfRangeError` or `StopIteration` exceptions. See the
  @@ -185,9 +192,16 @@ class EvalSpec(
  """Creates a validated `EvalSpec` instance.
  Args:
  - input_fn: Evaluation input function returning a tuple of:
  - features - `Tensor` or dictionary of string feature name to `Tensor`.
  - labels - `Tensor` or dictionary of `Tensor` with labels.
  + input_fn: A function that constructs the input data for evaluation.
  + See @{$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`.
  +
  steps: Int. Positive number of steps for which to evaluate model. If
  `None`, evaluates until `input_fn` raises an end-of-input exception.
  See `Estimator.evaluate` for details.
  