def plot_performance_acc(hist, hist_second): plt.rcParams['figure.figsize'] = (15, 7) hist_ = hist.history epochs = hist.epoch hist_01 = hist_second.history # epochs_01 = hist_01.epoch epochs_01 = hist_second.epoch plt.subplot(1, 2, 1) # row 1, col 2 index 1 plt.plot(epochs, hist_['accuracy'], label='Training Accuracy') plt.plot(epochs, hist_['val_accuracy'], label='Validation Accuracy') plt.plot(epochs_01, hist_01['accuracy'], label='Training Accuracy_01') plt.plot(epochs_01, hist_01['val_accuracy'], label='Validation Accuracy_01') plt.xlabel('Epochs') plt.ylabel('Accuracy') # plt.ylim([-0.001, 2.0]) # plt.title('Training and validation accuracy') plt.legend(loc = 'lower right') plt.title('Training and validation Accuracy') # plt.savefig('foo.jpg') plt.subplot(1, 2, 2) # row 1, col 2 index 1 plt.plot(epochs, hist_['loss'], label='Training loss') plt.plot(epochs, hist_['val_loss'], label='Validation loss') plt.plot(epochs_01, hist_01['loss'], label='Training loss_01') plt.plot(epochs_01, hist_01['val_loss'], label='Validation loss') plt.xlabel('Epochs') plt.ylabel('Loss') # plt.ylim([-0.001, 2.0]) plt.legend(loc = 'upper right') plt.title('Training and validation loss') plt.tight_layout(2) fig1 = plt.gcf() plt.show() plt.draw() fig1.savefig('tessstttyyy.png', dpi=100)
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