[keras/estimator/__init__.py] Standardise docstring usage of "Default…

… to"

keras/estimator/__init__.py

@@ -114,18 +114,17 @@ def input_fn():
         `tempfile.mkdtemp`
       config: `RunConfig` to config `Estimator`. Allows setting up things in
         `model_fn` based on configuration such as `num_ps_replicas`, or
-        `model_dir`. Defaults to `None`. If both `config.model_dir` and the
+        `model_dir`. If both `config.model_dir` and the
         `model_dir` argument (above) are specified the `model_dir` **argument**
-        takes precedence.
+        takes precedence. Defaults to `None`.
       checkpoint_format: Sets the format of the checkpoint saved by the
         estimator when training. May be `saver` or `checkpoint`, depending on
         whether to save checkpoints from `tf.train.Saver` or
-        `tf.train.Checkpoint`. This argument currently defaults to `saver`. When
-        2.0 is released, the default will be `checkpoint`. Estimators use
-        name-based `tf.train.Saver` checkpoints, while Keras models use
-        object-based checkpoints from `tf.train.Checkpoint`. Currently, saving
-        object-based checkpoints from `model_to_estimator` is only supported by
-        Functional and Sequential models. Defaults to 'saver'.
+        `tf.train.Checkpoint`. Estimators use name-based `tf.train.Saver`
+        checkpoints, while Keras models use object-based checkpoints from
+        `tf.train.Checkpoint`. Currently, saving object-based checkpoints
+        from `model_to_estimator` is only supported by Functional and
+        Sequential models. Defaults to 'saver'.
       metric_names_map: Optional dictionary mapping Keras model output metric
         names to custom names. This can be used to override the default Keras
         model output metrics names in a multi IO model use case and provide
@@ -312,9 +311,9 @@ def input_fn():
         `tempfile.mkdtemp`
       config: `RunConfig` to config `Estimator`. Allows setting up things in
         `model_fn` based on configuration such as `num_ps_replicas`, or
-        `model_dir`. Defaults to `None`. If both `config.model_dir` and the
+        `model_dir`. If both `config.model_dir` and the
         `model_dir` argument (above) are specified the `model_dir` **argument**
-        takes precedence.
+        takes precedence. Defaults to `None`.
       checkpoint_format: Sets the format of the checkpoint saved by the
         estimator when training. May be `saver` or `checkpoint`, depending on
         whether to save checkpoints from `tf.compat.v1.train.Saver` or