Internal change

PiperOrigin-RevId: 324919232

orbit/runner.py

@@ -34,7 +34,7 @@ class AbstractTrainer(tf.Module, metaclass=abc.ABCMeta):
     large in Eager mode. It is usually encouraged to create a host training loop
     (e.g. using a `tf.range` wrapping `strategy.run` inside a
     `tf.function`) in the TPU case. For the cases that don't require host
-    training loop to acheive peak performance, users can just implement a simple
+    training loop to achieve peak performance, users can just implement a simple
     python loop to drive each step.
 
     Args:

orbit/utils.py

@@ -432,7 +432,7 @@ def train_function_with_summaries(*args, **kwargs):
   return decorator
 
 
-def get_value(x) -> np.ndarray:
+def get_value(x) -> np.number:
   """Returns the value of a variable/tensor.
 
   Args: