Amend notes on eager compatibility for Estimator

PiperOrigin-RevId: 200581494

tensorflow/python/estimator/canned/baseline.py

@@ -215,6 +215,13 @@ def input_fn_eval: # returns x, y (where y represents label's class index).
 
   * if `weight_column` is not `None`, a feature with
      `key=weight_column` whose value is a `Tensor`.
+
+  @compatibility(eager)
+  Estimators can be used while eager execution is enabled. Note that `input_fn`
+  and all hooks are executed inside a graph context, so they have to be written
+  to be compatible with graph mode. Note that `input_fn` code using `tf.data`
+  generally works in both graph and eager modes.
+  @end_compatibility
   """
 
   def __init__(self,
@@ -313,6 +320,13 @@ def input_fn_eval: # returns x, y (where y is the label).
 
   * if `weight_column` is not `None`, a feature with
      `key=weight_column` whose value is a `Tensor`.
+
+  @compatibility(eager)
+  Estimators can be used while eager execution is enabled. Note that `input_fn`
+  and all hooks are executed inside a graph context, so they have to be written
+  to be compatible with graph mode. Note that `input_fn` code using `tf.data`
+  generally works in both graph and eager modes.
+  @end_compatibility
   """
 
   def __init__(self,

tensorflow/python/estimator/canned/boosted_trees.py

@@ -714,7 +714,15 @@ def _create_regression_head(label_dimension, weight_column=None):
 
 @estimator_export('estimator.BoostedTreesClassifier')
 class BoostedTreesClassifier(estimator.Estimator):
-  """A Classifier for Tensorflow Boosted Trees models."""
+  """A Classifier for Tensorflow Boosted Trees models.
+
+  @compatibility(eager)
+  Estimators can be used while eager execution is enabled. Note that `input_fn`
+  and all hooks are executed inside a graph context, so they have to be written
+  to be compatible with graph mode. Note that `input_fn` code using `tf.data`
+  generally works in both graph and eager modes.
+  @end_compatibility
+  """
 
   def __init__(self,
                feature_columns,
@@ -832,7 +840,15 @@ def _model_fn(features, labels, mode, config):
 
 @estimator_export('estimator.BoostedTreesRegressor')
 class BoostedTreesRegressor(estimator.Estimator):
-  """A Regressor for Tensorflow Boosted Trees models."""
+  """A Regressor for Tensorflow Boosted Trees models.
+
+  @compatibility(eager)
+  Estimators can be used while eager execution is enabled. Note that `input_fn`
+  and all hooks are executed inside a graph context, so they have to be written
+  to be compatible with graph mode. Note that `input_fn` code using `tf.data`
+  generally works in both graph and eager modes.
+  @end_compatibility
+  """
 
   def __init__(self,
                feature_columns,

tensorflow/python/estimator/canned/dnn.py

@@ -266,7 +266,10 @@ def input_fn_predict: # returns x, None
   Loss is calculated by using softmax cross entropy.
 
   @compatibility(eager)
-  Estimators are not compatible with eager execution.
+  Estimators can be used while eager execution is enabled. Note that `input_fn`
+  and all hooks are executed inside a graph context, so they have to be written
+  to be compatible with graph mode. Note that `input_fn` code using `tf.data`
+  generally works in both graph and eager modes.
   @end_compatibility
   """
 
@@ -418,7 +421,10 @@ def input_fn_predict: # returns x, None
   Loss is calculated by using mean squared error.
 
   @compatibility(eager)
-  Estimators are not compatible with eager execution.
+  Estimators can be used while eager execution is enabled. Note that `input_fn`
+  and all hooks are executed inside a graph context, so they have to be written
+  to be compatible with graph mode. Note that `input_fn` code using `tf.data`
+  generally works in both graph and eager modes.
   @end_compatibility
   """
 

tensorflow/python/estimator/canned/dnn_linear_combined.py

@@ -292,7 +292,10 @@ def input_fn_predict: # returns x, None
   Loss is calculated by using softmax cross entropy.
 
   @compatibility(eager)
-  Estimators are not compatible with eager execution.
+  Estimators can be used while eager execution is enabled. Note that `input_fn`
+  and all hooks are executed inside a graph context, so they have to be written
+  to be compatible with graph mode. Note that `input_fn` code using `tf.data`
+  generally works in both graph and eager modes.
   @end_compatibility
   """
 
@@ -473,7 +476,10 @@ def input_fn_predict: # returns x, None
   Loss is calculated by using mean squared error.
 
   @compatibility(eager)
-  Estimators are not compatible with eager execution.
+  Estimators can be used while eager execution is enabled. Note that `input_fn`
+  and all hooks are executed inside a graph context, so they have to be written
+  to be compatible with graph mode. Note that `input_fn` code using `tf.data`
+  generally works in both graph and eager modes.
   @end_compatibility
   """
 

tensorflow/python/estimator/canned/linear.py

@@ -227,7 +227,10 @@ def input_fn_eval: # returns x, y (where y represents label's class index).
   Loss is calculated by using softmax cross entropy.
 
   @compatibility(eager)
-  Estimators are not compatible with eager execution.
+  Estimators can be used while eager execution is enabled. Note that `input_fn`
+  and all hooks are executed inside a graph context, so they have to be written
+  to be compatible with graph mode. Note that `input_fn` code using `tf.data`
+  generally works in both graph and eager modes.
   @end_compatibility
   """
 
@@ -370,7 +373,10 @@ def input_fn_eval: # returns x, y
   Loss is calculated by using mean squared error.
 
   @compatibility(eager)
-  Estimators are not compatible with eager execution.
+  Estimators can be used while eager execution is enabled. Note that `input_fn`
+  and all hooks are executed inside a graph context, so they have to be written
+  to be compatible with graph mode. Note that `input_fn` code using `tf.data`
+  generally works in both graph and eager modes.
   @end_compatibility
   """
 

tensorflow/python/estimator/estimator.py

@@ -103,6 +103,15 @@ class Estimator(object):
   None of `Estimator`'s methods can be overridden in subclasses (its
   constructor enforces this). Subclasses should use `model_fn` to configure
   the base class, and may add methods implementing specialized functionality.
+
+  @compatbility(eager)
+  Calling methods of `Estimator` will work while eager execution is enabled.
+  However, the `model_fn` and `input_fn` is not executed eagerly, `Estimator`
+  will switch to graph model before calling all user-provided functions (incl.
+  hooks), so their code has to be compatible with graph mode execution. Note
+  that `input_fn` code using `tf.data` generally works in both graph and eager
+  modes.
+  @end_compatibility
   """
 
   def __init__(self, model_fn, model_dir=None, config=None, params=None,