nncf/experimental/torch/nas/bootstrapNAS/training/scheduler.py
def step(self, next_step: Optional[int] = None) -> None:
        """
        Should be called at the beginning of each training step to prepare
        the compression method to continue training the model in the `next_step`.

        :param next_step: The global step index for which the compression scheduler
            will update the state of the compression method.
        """
        self._training_ctrl.step()

        Should be called at the beginning of each training step to prepare
        the compression method to continue training the model in the `next_step`.

        :param next_step: The global step index for which the compression scheduler
            will update the state of the compression method.
        
Should be called at the beginning of each training step to prepare
the compression method to continue training the model in the `next_step`.
Should be called at the beginning of each training step to prepare the compression method to continue training the model in the ` next_step ` .
def step(self, next_step: Optional[int] = None) -> None:
        self._training_ctrl.step()
def step ( self , next_step : Optional [ int ] = None ) -> None : self . _training_ctrl . step ( )
Should be called at the beginning of each training step to prepare
the compression method to continue training the model in the `next_step`.
Should be called at the beginning of each training step to prepare the compression method to continue training the model in the ` next_step ` .
"""
        Should be called at the beginning of each training step to prepare
        the compression method to continue training the model in the `next_step`.

        :param next_step: The global step index for which the compression scheduler
            will update the state of the compression method.
        """
self
next_step
Optional[int]
The global step index for which the compression scheduler
will update the state of the compression method.
The global step index for which the compression scheduler will update the state of the compression method .