code: 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')f 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'))
docs: Plots learning rate in jupyter notebook or console, depending on the enviroment of the learner.