message: Correct some tf.contrib references that have recently moved to core in contrib/learn/README.md
diff: @@ -7,12 +7,11 @@ warnings. A high-level overview is below.
  ## Canned Estimators
  -Many canned estimators (subclasses of `Estimator`) have equivalents in core:
  +Many canned estimators (subclasses of `Estimator`) have equivalents in core
  +exposed under `tf.estimator`:
  `DNNClassifier`, `DNNRegressor`, `DNNEstimator`, `LinearClassifier`,
  -`LinearRegressor`, `DNNLinearCombinedClassifier` and
  -`DNNLinearCombinedRegressor`. They are exposed under `tf.estimator`.
  -`DNNEstimator`, `LinearEstimator` and `DNNLinearCombinedEstimator`
  -are exposed under `tf.contrib.estimator`.
  +`LinearRegressor`, `LinearEstimator`, `DNNLinearCombinedClassifier`,
  +`DNNLinearCombinedRegressor` and `DNNLinearCombinedEstimator`.
  To migrate to the new api, users need to take the following steps:
  @@ -45,7 +44,7 @@ To migrate to the new api, users need to take the following steps:
  `tf.contrib.learn` classifiers and regressors supported labels with shape
  `[batch_size]`.
  * If you pass custom metrics from the `evaluate()` method call, use
  - `tf.contrib.estimator.add_metrics`.
  + `tf.estimator.add_metrics`.
  * Replace your `serving_input_fn` with a `serving_input_receiver_fn`.
  Note this should be entirely distinct from your training `input_fn`, so if you
  previously had one `input_fn` with different "modes", you should now factor
  @@ -66,7 +65,7 @@ Some remaining estimators/classes:
  * `LinearComposableModel` and `DNNComposableModel`: Not supported.
  Consider `tf.contrib.estimator.DNNEstimator`, or write a custom model_fn.
  * `MetricSpec`: Deprecated. For adding custom metrics to canned Estimators, use
  - `tf.contrib.estimator.add_metrics`.
  + `tf.estimator.add_metrics`.
  ## Estimator
  `tf.contrib.learn.Estimator` is migrated to `tf.estimator.Estimator`.
  