Why do Pil_to_image() and read_image() functions give me different tensors?

Question

So I have an image in JPG format and I read this image as a tensor using two different ways:

1. with

from torchvision.io import read_image

read_image(image_path)

and it gives me the tensor:

tensor([[[255, 255, 255,  ..., 191, 191, 191],
         [255, 255, 255,  ..., 191, 191, 191],
         [255, 255, 255,  ..., 191, 191, 191],
         ...,
         [255, 255, 255,  ..., 191, 191, 191],
         [255, 255, 255,  ..., 191, 191, 191],
         [255, 255, 255,  ..., 191, 191, 191]],

        [[255, 255, 255,  ..., 255, 255, 255],
         [255, 255, 255,  ..., 255, 255, 255],
         [255, 255, 255,  ..., 255, 255, 255],
         ...,
         [255, 255, 255,  ..., 255, 255, 255],
         [255, 255, 255,  ..., 255, 255, 255],
         [255, 255, 255,  ..., 255, 255, 255]],

        [[255, 255, 255,  ..., 255, 255, 255],
         [255, 255, 255,  ..., 255, 255, 255],
         [255, 255, 255,  ..., 255, 255, 255],
         ...,
         [255, 255, 255,  ..., 255, 255, 255],
         [255, 255, 255,  ..., 255, 255, 255],
         [255, 255, 255,  ..., 255, 255, 255]],

        [[129, 143, 143,  ..., 255, 255, 255],
         [143, 255, 254,  ..., 255, 255, 255],
         [143, 254, 255,  ..., 255, 255, 255],
         ...,
         [143, 255, 255,  ..., 255, 255, 255],
         [144, 254, 255,  ..., 255, 255, 255],
         [129, 144, 143,  ..., 255, 255, 255]]], dtype=torch.uint8)

2. when I use

from torchvision.transforms.functional import pil_to_tensor

img = PIL.Image.open(image_path) 
pil_to_tensor(img)

it gives me the tensor

tensor([[[  0,   0,   0,  ...,  64,  64,  64],
         [  0,   0,   0,  ...,  64,  64,  64],
         [  0,   0,   0,  ...,  64,  64,  64],
         ...,
         [  0,   0,   0,  ...,  64,  64,  64],
         [  0,   0,   0,  ...,  64,  64,  64],
         [  0,   0,   0,  ...,  64,  64,  64]],

        [[  0,   0,   0,  ...,   0,   0,   0],
         [  0,   0,   0,  ...,   0,   0,   0],
         [  0,   0,   0,  ...,   0,   0,   0],
         ...,
         [  0,   0,   0,  ...,   0,   0,   0],
         [  0,   0,   0,  ...,   0,   0,   0],
         [  0,   0,   0,  ...,   0,   0,   0]],

        [[  0,   0,   0,  ...,   0,   0,   0],
         [  0,   0,   0,  ...,   0,   0,   0],
         [  0,   0,   0,  ...,   0,   0,   0],
         ...,
         [  0,   0,   0,  ...,   0,   0,   0],
         [  0,   0,   0,  ...,   0,   0,   0],
         [  0,   0,   0,  ...,   0,   0,   0]],

        [[126, 112, 112,  ...,   0,   0,   0],
         [112,   0,   1,  ...,   0,   0,   0],
         [112,   1,   0,  ...,   0,   0,   0],
         ...,
         [112,   0,   0,  ...,   0,   0,   0],
         [111,   1,   0,  ...,   0,   0,   0],
         [126, 111, 112,  ...,   0,   0,   0]]], dtype=torch.uint8)

I get the correct and the original image when I use the first tensor not the second one. Also I observed that I can get the second tensor by subtracting each value in the first tensor from 255. Then my questions are:

1. Why does the second way invert the original image?
2. If I use the conversion formula 255 + second_tensor = first_tensor, do I always get the right result?

Thanks!