plotter.py

class Plotter(botCallback):
    def __init__(self,access_token):
        super().__init__(access_token)

    def on_train_begin(self,logs=None):
        self.batch = 0
        self.epoch = []
        self.train_loss = []
        self.val_loss = []
        self.train_acc = []
        self.val_acc = []
        self.fig = plt.figure(figsize=(200,100))
        self.logs = []
    
    def on_epoch_end(self, epoch, logs=None):

        self.logs.append(logs)
        self.epoch.append(epoch)
        self.train_loss.append(logs['loss'])
        self.val_loss.append(logs['val_loss'])
        self.train_acc.append(logs['accuracy'])
        self.val_acc.append(logs['val_accuracy'])

        f,(ax1,ax2) = plt.subplots(1,2,sharex=True)

        clear_output(wait=True)

        ax1.plot(self.epoch, self.train_loss, label='Training Loss')
        ax1.plot(self.epoch, self.val_loss, label='Validation Loss')
        ax1.legend()

        ax2.plot(self.epoch, self.train_acc, label='Training Accuracy')
        ax2.plot(self.epoch, self.val_acc, label='Validation Accuracy')
        ax2.legend()

        plt.savefig('Accuracy and Loss plot.jpg')
        self.send_photo('/content/Accuracy and Loss plot.jpg')