def _step_adversary_py(*flattened_actions):
with tf_py_environment._check_not_called_concurrently(self._lock): # pylint:disable=protected-access
packed = tf.nest.pack_sequence_as(
structure=self.adversary_action_spec,
flat_sequence=flattened_actions)
self._time_step = self._env.step_adversary(packed)
return tf.nest.flatten(self._time_step)
def _current_random_time_step_py():
with tf_py_environment._check_not_called_concurrently(self._lock): # pylint:disable=protected-access
if self._time_step is None:
self._time_step = self._env.reset_random()
return tf.nest.flatten(self._time_step)
def _reset_py():
with tf_py_environment._check_not_called_concurrently(self._lock): # pylint:disable=protected-access
self._time_step = self._env.reset_random()
