def initial_state(self):
"""Initial state for a learning process."""
value_dict = self.loss_module.initial_state()
shapes = [v.shape.as_list() for v in value_dict.values()]
b = super(Learner, self).initial_state()
return base_arch.merged_namedtuple(
LearnerState,
b,
rolling_features=self.rolling_features.initial_state(shapes))
def current_state(self):
"""State stored on local tf.Variable for this Learner."""
var_dict = self.loss_module.current_state()
shapes = [v.shape.as_list() for v in var_dict.values()]
b = super(Learner, self).current_state()
return base_arch.merged_namedtuple(
LearnerState,
b,
rolling_features=self.rolling_features.current_state(shapes),
)