def update_period(self, value: int):
validate_positive_int(value)
self._update_period = value
def hidden_size(self, value: int):
validate_positive_int(value)
self._network_params.hidden_size = value
def sy(self, value: int):
validate_positive_int(value)
self._params.sy = value
def learning_period(self, value: int):
validate_positive_int(value)
self._node_params.learning_period = value
def batch_size(self, value: int):
validate_positive_int(value)
validate_predicate(lambda: value < self._node_params.buffer_size)
self._node_params.batch_size = value
def flock_size(self, value: int):
validate_positive_int(value)
self._node_params.flock_size = value
self._network_params.flock_size = value
def validate(self):
validate_positive_int(self._node_params.flock_size)
validate_predicate(lambda: self.inputs.learning_coefficients.tensor.dim() == 1)
validate_predicate(lambda: self._node_params.flock_size == self.inputs.learning_coefficients.tensor.shape[0])
def fixed_region_size(self, value: int):
validate_positive_int(value)
self._fixed_region_size = value
self._salient_region.fixed_region_size = value
self._focus_node.trim_output_size = value