code: def _sample_actions(self,
              state: Sequence[tf.Tensor]) -> Tuple[Sequence[tf.Tensor], tf.Tensor, tf.Tensor]:
          '''Returns sampled action fluents and tensors related to the sampling.
  
          Args:
              state (Sequence[tf.Tensor]): A list of state fluents.
  
          Returns:
              Tuple[Sequence[tf.Tensor], tf.Tensor, tf.Tensor]: A tuple with
              action fluents, an integer tensor for the number of samples, and
              a boolean tensor for checking all action preconditions.
          '''
          default = self.compiler.compile_default_action(self.batch_size)
          bound_constraints = self.compiler.compile_action_bound_constraints(state)
          action = self._sample_action(bound_constraints, default)
          n, action, checking = self._check_preconditions(state, action, bound_constraints, default)
          return action, n, checkinf _sample_actions(self,
              state: Sequence[tf.Tensor]) -> Tuple[Sequence[tf.Tensor], tf.Tensor, tf.Tensor]:
          '''Returns sampled action fluents and tensors related to the sampling.
  
          Args:
              state (Sequence[tf.Tensor]): A list of state fluents.
  
          Returns:
              Tuple[Sequence[tf.Tensor], tf.Tensor, tf.Tensor]: A tuple with
              action fluents, an integer tensor for the number of samples, and
              a boolean tensor for checking all action preconditions.
          '''
          default = self.compiler.compile_default_action(self.batch_size)
          bound_constraints = self.compiler.compile_action_bound_constraints(state)
          action = self._sample_action(bound_constraints, default)
          n, action, checking = self._check_preconditions(state, action, bound_constraints, default)
          return action, n, checking
docs: Returns sampled action fluents and tensors related to the sampling.
  
          Args:
              state (Sequence[tf.Tensor]): A list of state fluents.
  
          Returns:
              Tuple[Sequence[tf.Tensor], tf.Tensor, tf.Tensor]: A tuple with
              action fluents, an integer tensor for the number of samples, and
              a boolean tensor for checking all action preconditions.