nncf/experimental/tensorflow/graph/transformations/commands.py
def from_state(cls, state: Dict[str, Any]) -> 'TFTargetPoint':
        """
        Creates the object from its state.

        :param state: Output of `get_state()` method.
        """
        kwargs = {
            cls._state_names.OP_NAME: state[cls._state_names.OP_NAME],
            cls._state_names.OP_TYPE_NAME: state[cls._state_names.OP_TYPE_NAME],
            cls._state_names.PORT_ID: state[cls._state_names.PORT_ID],
            cls._state_names.TARGET_TYPE: TargetType.from_state(state[cls._state_names.TARGET_TYPE]),
        }
        return cls(**kwargs)

        Creates the object from its state.

        :param state: Output of `get_state()` method.
        
Creates the object from its state.
Creates the object from its state .
def from_state(cls, state: Dict[str, Any]) -> 'TFTargetPoint':
        kwargs = {
            cls._state_names.OP_NAME: state[cls._state_names.OP_NAME],
            cls._state_names.OP_TYPE_NAME: state[cls._state_names.OP_TYPE_NAME],
            cls._state_names.PORT_ID: state[cls._state_names.PORT_ID],
            cls._state_names.TARGET_TYPE: TargetType.from_state(state[cls._state_names.TARGET_TYPE]),
        }
        return cls(**kwargs)
def from_state ( cls , state : Dict [ str , Any ] ) -> 'TFTargetPoint' : kwargs = { cls . _state_names . OP_NAME : state [ cls . _state_names . OP_NAME ] , cls . _state_names . OP_TYPE_NAME : state [ cls . _state_names . OP_TYPE_NAME ] , cls . _state_names . PORT_ID : state [ cls . _state_names . PORT_ID ] , cls . _state_names . TARGET_TYPE : TargetType . from_state ( state [ cls . _state_names . TARGET_TYPE ] ) , } return cls ( ** kwargs )
Creates the object from its state.
Creates the object from its state .
"""
        Creates the object from its state.

        :param state: Output of `get_state()` method.
        """
cls
state
Dict[str, Any]
Output of `get_state()` method.
Output of ` get_state () ` method .