Delete visulization.py

visulization.py

-import matplotlib.pyplot as plt
-import numpy as np
-
-
-def plot_model_history(model_history):
-    fig, axs = plt.subplots(1, 2, figsize=(15, 5))
-    # summarize history for accuracy
-    axs[0].plot(range(1, len(model_history.history['acc']) + 1),
-                model_history.history['acc'])
-    axs[0].plot(range(1, len(model_history.history['val_acc']) + 1),
-                model_history.history['val_acc'])
-    axs[0].set_title('Model Accuracy')
-    axs[0].set_ylabel('Accuracy')
-    axs[0].set_xlabel('Epoch')
-    axs[0].set_xticks(np.arange(1, len(model_history.history[
-                      'acc']) + 1), len(model_history.history['acc']) / 10)
-    axs[0].legend(['train', 'val'], loc='best')
-    # summarize history for loss
-    axs[1].plot(range(1, len(model_history.history['loss']) + 1),
-                model_history.history['loss'])
-    axs[1].plot(range(1, len(model_history.history['val_loss']) + 1),
-                model_history.history['val_loss'])
-    axs[1].set_title('Model Loss')
-    axs[1].set_ylabel('Loss')
-    axs[1].set_xlabel('Epoch')
-    axs[1].set_xticks(np.arange(1, len(model_history.history[
-                      'loss']) + 1), len(model_history.history['loss']) / 10)
-    axs[1].legend(['train', 'val'], loc='best')
-    plt.show()