nncf/experimental/torch/nas/bootstrapNAS/training/scheduler.py
def from_state(cls, state: Dict[str, Any]) -> 'NASSchedulerParams':
        """
        Creates the object from its state.

        :param state: Output of `get_state()` method.
        """
        list_stage_descriptions_state = state[cls._state_names.LIST_STAGE_DESCRIPTIONS]
        list_stage_descriptions = [StageDescriptor.from_state(state) for state in list_stage_descriptions_state]
        return cls(list_stage_descriptions)

        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]) -> 'NASSchedulerParams':
        list_stage_descriptions_state = state[cls._state_names.LIST_STAGE_DESCRIPTIONS]
        list_stage_descriptions = [StageDescriptor.from_state(state) for state in list_stage_descriptions_state]
        return cls(list_stage_descriptions)
def from_state ( cls , state : Dict [ str , Any ] ) -> 'NASSchedulerParams' : list_stage_descriptions_state = state [ cls . _state_names . LIST_STAGE_DESCRIPTIONS ] list_stage_descriptions = [ StageDescriptor . from_state ( state ) for state in list_stage_descriptions_state ] return cls ( list_stage_descriptions )
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 .