python
import tensorflow as tf
from tensorflow.keras import layers
model = tf.keras.Sequential([
layers.Conv2D(32, 3, activation='relu', input_shape=(32, 32, 3)),
layers.MaxPooling2D(),
layers.Flatten(),
layers.Dense(64, activation='relu'),
layers.Dense(10)
])
model.compile(optimizer='adam',
loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
metrics=['accuracy'])
model.fit(train_images, train_labels, epochs=10)
test_loss, test_acc = model.evaluate(test_images, test_labels, verbose=2)
print('
Test accuracy:', test_acc)
