Internal change

PiperOrigin-RevId: 342803522

Author: tensorflower-gardener

orbit/runner.py

@@ -32,14 +32,14 @@ class AbstractTrainer(tf.Module, metaclass=abc.ABCMeta):
   def train(self, num_steps: tf.Tensor) -> Optional[Output]:
     """Implements `num_steps` steps of training.
 
-    This method will by called the `Controller` to perform the "inner loop" of
-    training. This inner loop amortizes the cost of bookkeeping associated with
-    checkpointing, evaluation, and writing summaries. Additionally, the inner
-    loop can be implemented (if desired) using TensorFlow's looping constructs
-    (e.g. a `for` loop over a `tf.range` inside a `tf.function`), which can be
-    necessary for getting optimal performance when running on TPU. For cases
-    that don't require peak performance, a simple Python loop can be used
-    instead for simplicity.
+    This method will be called by the `Controller` to perform the "inner loop"
+    of training. This inner loop amortizes the cost of bookkeeping associated
+    with checkpointing, evaluation, and writing summaries. Additionally, the
+    inner loop can be implemented (if desired) using TensorFlow's looping
+    constructs (e.g. a `for` loop over a `tf.range` inside a `tf.function`),
+    which can be necessary for getting optimal performance when running on TPU.
+    For cases that don't require peak performance, a simple Python loop can be
+    used instead for simplicity.
 
     Args:
       num_steps: The number of training steps to run. Note that it is up to the