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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:

def fit_one_cycle(learn:Learner, cyc_len:int, max_lr:Union[Floats,slice]=defaults.lr,
                  moms:Tuple[float,float]=(0.95,0.85), div_factor:float=25., pct_start:float=0.3, final_div:float=None,
                  wd:float=None, callbacks:Optional[CallbackList]=None, tot_epochs:int=None, start_epoch:int=None)->None:
    "Fit a model following the 1cycle policy."
    max_lr = learn.lr_range(max_lr)
    callbacks = listify(callbacks)
    callbacks.append(OneCycleScheduler(learn, max_lr, moms=moms, div_factor=div_factor, pct_start=pct_start,
                                       final_div=final_div, tot_epochs=tot_epochs, start_epoch=start_epoch))
    learn.fit(cyc_len, max_lr, wd=wd, callbacks=callbacks)