Use torch.testing.assert_close in test_image.py (#3877)

Co-authored-by: Philip Meier <github.pmeier@posteo.de>

test/test_image.py

@@ -8,6 +8,7 @@ import numpy as np
 import torch
 from PIL import Image
 from common_utils import get_tmp_dir, needs_cuda
+from _assert_utils import assert_equal
 
 from torchvision.io.image import (
     decode_png, decode_jpeg, encode_jpeg, write_jpeg, decode_image, read_file,
@@ -107,7 +108,7 @@ class ImageTester(unittest.TestCase):
             for src_img in [img, img.contiguous()]:
                 # PIL sets jpeg quality to 75 by default
                 jpeg_bytes = encode_jpeg(src_img, quality=75)
-                self.assertTrue(jpeg_bytes.equal(pil_bytes))
+                assert_equal(jpeg_bytes, pil_bytes)
 
         with self.assertRaisesRegex(
                 RuntimeError, "Input tensor dtype should be uint8"):
@@ -191,7 +192,7 @@ class ImageTester(unittest.TestCase):
             rec_img = torch.from_numpy(np.array(rec_img))
             rec_img = rec_img.permute(2, 0, 1)
 
-            self.assertTrue(img_pil.equal(rec_img))
+            assert_equal(img_pil, rec_img)
 
         with self.assertRaisesRegex(
                 RuntimeError, "Input tensor dtype should be uint8"):
@@ -224,7 +225,7 @@ class ImageTester(unittest.TestCase):
                 saved_image = torch.from_numpy(np.array(Image.open(torch_png)))
                 saved_image = saved_image.permute(2, 0, 1)
 
-                self.assertTrue(img_pil.equal(saved_image))
+                assert_equal(img_pil, saved_image)
 
     def test_read_file(self):
         with get_tmp_dir() as d:
@@ -235,7 +236,7 @@ class ImageTester(unittest.TestCase):
 
             data = read_file(fpath)
             expected = torch.tensor(list(content), dtype=torch.uint8)
-            self.assertTrue(data.equal(expected))
+            assert_equal(data, expected)
             os.unlink(fpath)
 
         with self.assertRaisesRegex(
@@ -251,7 +252,7 @@ class ImageTester(unittest.TestCase):
 
             data = read_file(fpath)
             expected = torch.tensor(list(content), dtype=torch.uint8)
-            self.assertTrue(data.equal(expected))
+            assert_equal(data, expected)
             os.unlink(fpath)
 
     def test_write_file(self):