Как исправить ошибку ApplePersistenceIgnoreState? ⇐ Python

[Anonymous]

Я следую учебнику Neuronnine о том, как классифицировать изображения с помощью нейронных сетей.
Я использую Imac.
Ниже приведен код:

Код: Выделить всё

import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras import datasets, layers, models
#preparing data
(training_images, training_labels), (testing_images, testing_labels) = datasets.cifar10.load_data()
training_images, testing_images = training_images / 255, testing_images / 255

class_names = ['Plane', 'Car', 'Bird', 'Cat', 'Deer', 'Dog', 'Frog', 'Horse', 'Ship', 'Truck']

for i in range(16):
plt.subplot(4,4,i+1)
plt.xticks([])
plt.yticks([])
plt.imshow(training_images[i], cmap=plt.cm.binary)
plt.xlabel(class_names[training_labels[i][0]])

plt.show()

training_images = training_images[:5000] #save time
training_labels = training_labels[:5000]
testing_images = testing_images[:4000]
testing_labels = testing_labels[:4000]

model = models.Sequential()
model.add(layers.Conv2D(32, (3,3), activation='relu', input_shape=(32,32,3)))
model.add(layers.MaxPooling2D((2,2)))
model.add(layers.Conv2D(64, (3,3), activation='relu'))
model.add(layers.MaxPooling2D((2,2)))
model.add(layers.Conv2D(64, (3,3), activation='relu'))
model.add(layers.Flatten())
model.add(layers.Dense(64, activation='relu'))
model.add(layers.Dense(10, activation='softmax'))

model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])

model.fit(training_images, training_labels, epochs=10, validation_data=(testing_images, testing_labels))

Я получаю следующее сообщение на своем терминале:

Код: Выделить всё

ApplePersistenceIgnoreState: Existing state will not be touched. New state will be written to /var/folders/2g/.../T/org.python.python.savedState
2024-08-02 16:29:19.788 Python[48146:6869495] WARNING: Secure coding is not enabled for restorable state! Enable secure coding by implementing NSApplicationDelegate.applicationSupportsSecureRestorableState: and returning YES.

совершенно не знаю, что делать

Подробнее здесь: https://stackoverflow.com/questions/788 ... tate-error