def plot_lr(self):
        '''Plots learning rate in jupyter notebook or console, depending on the enviroment of the learner.'''
        if not in_ipynb():
            plt.switch_backend('agg')
        if self.record_mom:
            fig, axs = plt.subplots(1,2,figsize=(12,4))
            for i in range(0,2): axs[i].set_xlabel('iterations')
            axs[0].set_ylabel('learning rate')
            axs[1].set_ylabel('momentum')
            axs[0].plot(self.iterations,self.lrs)
            axs[1].plot(self.iterations,self.momentums)   
        else:
            plt.xlabel("iterations")
            plt.ylabel("learning rate")
            plt.plot(self.iterations, self.lrs)
        if not in_ipynb():
            plt.savefig(os.path.join(self.save_path, 'lr_plot.png'))
def plot_lr ( self ) : if not in_ipynb ( ) : plt . switch_backend ( 'agg' ) if self . record_mom : fig , axs = plt . subplots ( 1 , 2 , figsize = ( 12 , 4 ) ) for i in range ( 0 , 2 ) : axs [ i ] . set_xlabel ( 'iterations' ) axs [ 0 ] . set_ylabel ( 'learning rate' ) axs [ 1 ] . set_ylabel ( 'momentum' ) axs [ 0 ] . plot ( self . iterations , self . lrs ) axs [ 1 ] . plot ( self . iterations , self . momentums ) else : plt . xlabel ( "iterations" ) plt . ylabel ( "learning rate" ) plt . plot ( self . iterations , self . lrs ) if not in_ipynb ( ) : plt . savefig ( os . path . join ( self . save_path , 'lr_plot.png' ) )
Plots learning rate in jupyter notebook or console, depending on the enviroment of the learner.