fix: correct typos in codebase

setup.py

@@ -113,7 +113,7 @@ def main(_):
       # Sets all GPUs to 1GB of memory. The process running the bulk of the unit
       # tests allocates all GPU memory because by default TensorFlow allocates
       # all GPU memory during initialization. This causes tests in
-      # run_seperately to fail with out of memory errors because they are run as
+      # run_separately to fail with out of memory errors because they are run as
       # a subprocess of the process holding the GPU memory.
       gpus = tf.config.experimental.list_physical_devices('GPU')
       for gpu in gpus:

tf_agents/policies/async_policy_saver.py

@@ -64,7 +64,7 @@ def _assert_save_thread_is_alive(self):
     if self._join_save_thread or not self._save_thread.is_alive():
       raise ValueError(
           "Saving thread in AsyncPolicySaver is not alive. Either "
-          "an exception has occured while saving, or the saver "
+          "an exception has occurred while saving, or the saver "
           "was closed."
       )
 

tf_agents/policies/tf_policy.py

@@ -42,7 +42,7 @@
 class TFPolicy(tf.Module):
   """Abstract base class for TF Policies.
 
-  The Policy represents a mapping from `time_steps` recieved from the
+  The Policy represents a mapping from `time_steps` received from the
   environment to `actions` that can be applied to the environment.
 
   Agents expose two policies. A `policy` meant for deployment and evaluation,