Upgrade black to version ~=22.0 (#15565)

* Upgrade black to version ~=22.0

* Check copies

* Fix code

tests/test_generation_beam_search.py

@@ -102,7 +102,7 @@ class BeamSearchTester:
             beam_hyp.add(input_ids[beam_idx], -10.0 + float(beam_idx))
 
         # -10.0 is removed => -9.0 is worst score
-        self.parent.assertAlmostEqual(beam_hyp.worst_score, -9.0 / (self.sequence_length ** beam_hyp.length_penalty))
+        self.parent.assertAlmostEqual(beam_hyp.worst_score, -9.0 / (self.sequence_length**beam_hyp.length_penalty))
 
         # -5.0 is better than worst score => should not be finished
         self.parent.assertFalse(beam_hyp.is_done(-5.0, self.sequence_length))

tests/test_modeling_ibert.py

@@ -544,7 +544,7 @@ class IBertModelIntegrationTest(unittest.TestCase):
             self.assertTrue(torch.allclose(q_int, q_int.round(), atol=1e-4))
 
             # Output of the quantize Softmax should not exceed the output_bit
-            self.assertTrue(q.abs().max() < 2 ** output_bit)
+            self.assertTrue(q.abs().max() < 2**output_bit)
 
         array = [[i + j for j in range(10)] for i in range(-10, 10)]
         _test(array)

tests/test_modeling_swin.py

@@ -252,7 +252,7 @@ class SwinModelTest(ModelTesterMixin, unittest.TestCase):
             # check that output_attentions also work using config
             del inputs_dict["output_attentions"]
             config.output_attentions = True
-            window_size_squared = config.window_size ** 2
+            window_size_squared = config.window_size**2
             model = model_class(config)
             model.to(torch_device)
             model.eval()

tests/test_modeling_vit_mae.py

@@ -134,7 +134,7 @@ class ViTMAEModelTester:
         patch_size = to_2tuple(self.patch_size)
         num_patches = (image_size[1] // patch_size[1]) * (image_size[0] // patch_size[0])
         expected_seq_len = num_patches
-        expected_num_channels = self.patch_size ** 2 * self.num_channels
+        expected_num_channels = self.patch_size**2 * self.num_channels
         self.parent.assertEqual(result.logits.shape, (self.batch_size, expected_seq_len, expected_num_channels))
 
     def prepare_config_and_inputs_for_common(self):

tests/test_utils_check_copies.py

@@ -68,7 +68,8 @@ class CopyCheckTester(unittest.TestCase):
         code = comment + f"\nclass {class_name}(nn.Module):\n" + class_code
         if overwrite_result is not None:
             expected = comment + f"\nclass {class_name}(nn.Module):\n" + overwrite_result
-        code = black.format_str(code, mode=black.FileMode([black.TargetVersion.PY35], line_length=119))
+        mode = black.Mode(target_versions={black.TargetVersion.PY35}, line_length=119)
+        code = black.format_str(code, mode=mode)
         fname = os.path.join(self.transformer_dir, "new_code.py")
         with open(fname, "w", newline="\n") as f:
             f.write(code)