C4_W4A2 is normalization a img dosen't affect it's show?

In the assignment , I came to two code segment below:
seg1

content_image = np.array(Image.open("images/louvre_small.jpg").resize((img_size, img_size)))
content_image = tf.constant(np.reshape(content_image, ((1,) + content_image.shape)))

print(content_image.shape)
imshow(content_image[0])
plt.show()

seg2

generated_image = tf.Variable(tf.image.convert_image_dtype(content_image, tf.float32))
noise = tf.random.uniform(tf.shape(generated_image), -0.25, 0.25)
generated_image = tf.add(generated_image, noise)
generated_image = tf.clip_by_value(generated_image, clip_value_min=0.0, clip_value_max=1.0)

print(generated_image.shape)
imshow(generated_image.numpy()[0])
plt.show()

The element of content_image is range between 0-255 while generated_image 's between 0-1.
But they all show well.
So is imshow can auto adjust the value range it’s going to output to keep it correct to be shown?

That is correct

(M, N, 3): an image with RGB values (0-1 float or 0-255 int).