Upgrade black to version ~=22.0 (#15565)

* Upgrade black to version ~=22.0

* Check copies

* Fix code

src/transformers/models/yoso/modeling_yoso.py

@@ -175,7 +175,7 @@ class YosoLSHCumulation(torch.autograd.Function):
         use_cuda = query_mask.is_cuda
         num_hash = config["num_hash"]
         hash_code_len = config["hash_code_len"]
-        hashtable_capacity = int(2 ** hash_code_len)
+        hashtable_capacity = int(2**hash_code_len)
 
         if config["use_fast_hash"]:
             query_hash_code, key_hash_code = lsh_cumulation.fast_hash(
@@ -202,7 +202,7 @@ class YosoLSHCumulation(torch.autograd.Function):
 
         use_cuda = grad.is_cuda
         hash_code_len = config["hash_code_len"]
-        hashtable_capacity = int(2 ** hash_code_len)
+        hashtable_capacity = int(2**hash_code_len)
 
         if config["lsh_backward"]:
             grad_value = lsh_cumulation.lsh_cumulation(

src/transformers/optimization.py

@@ -214,7 +214,7 @@ def get_polynomial_decay_schedule_with_warmup(
             lr_range = lr_init - lr_end
             decay_steps = num_training_steps - num_warmup_steps
             pct_remaining = 1 - (current_step - num_warmup_steps) / decay_steps
-            decay = lr_range * pct_remaining ** power + lr_end
+            decay = lr_range * pct_remaining**power + lr_end
             return decay / lr_init  # as LambdaLR multiplies by lr_init
 
     return LambdaLR(optimizer, lr_lambda, last_epoch)
@@ -586,7 +586,7 @@ class Adafactor(Optimizer):
                 lr = self._get_lr(group, state)
 
                 beta2t = 1.0 - math.pow(state["step"], group["decay_rate"])
-                update = (grad ** 2) + group["eps"][0]
+                update = (grad**2) + group["eps"][0]
                 if factored:
                     exp_avg_sq_row = state["exp_avg_sq_row"]
                     exp_avg_sq_col = state["exp_avg_sq_col"]

src/transformers/pipelines/audio_utils.py

@@ -204,7 +204,7 @@ def _ffmpeg_stream(ffmpeg_command, buflen: int):
     """
     Internal function to create the generator of data through ffmpeg
     """
-    bufsize = 2 ** 24  # 16Mo
+    bufsize = 2**24  # 16Mo
     try:
         with subprocess.Popen(ffmpeg_command, stdout=subprocess.PIPE, bufsize=bufsize) as ffmpeg_process:
             while True:

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)

utils/check_copies.py

@@ -88,7 +88,7 @@ def find_code_in_transformers(object_name):
     line_index = 0
     for name in parts[i + 1 :]:
         while (
-            line_index < len(lines) and re.search(fr"^{indent}(class|def)\s+{name}(\(|\:)", lines[line_index]) is None
+            line_index < len(lines) and re.search(rf"^{indent}(class|def)\s+{name}(\(|\:)", lines[line_index]) is None
         ):
             line_index += 1
         indent += "    "
@@ -130,7 +130,8 @@ def blackify(code):
     has_indent = len(get_indent(code)) > 0
     if has_indent:
         code = f"class Bla:\n{code}"
-    result = black.format_str(code, mode=black.FileMode([black.TargetVersion.PY35], line_length=119))
+    mode = black.Mode(target_versions={black.TargetVersion.PY35}, line_length=119)
+    result = black.format_str(code, mode=mode)
     result, _ = style_docstrings_in_code(result)
     return result[len("class Bla:\n") :] if has_indent else result
 

utils/get_modified_files.py

@@ -28,7 +28,7 @@ fork_point_sha = subprocess.check_output("git merge-base master HEAD".split()).d
 modified_files = subprocess.check_output(f"git diff --name-only {fork_point_sha}".split()).decode("utf-8").split()
 
 joined_dirs = "|".join(sys.argv[1:])
-regex = re.compile(fr"^({joined_dirs}).*?\.py$")
+regex = re.compile(rf"^({joined_dirs}).*?\.py$")
 
 relevant_modified_files = [x for x in modified_files if regex.match(x)]
 print(" ".join(relevant_modified_files), end="")

utils/style_doc.py

@@ -147,9 +147,8 @@ def format_code_example(code: str, max_len: int, in_docstring: bool = False):
     for k, v in BLACK_AVOID_PATTERNS.items():
         full_code = full_code.replace(k, v)
     try:
-        formatted_code = black.format_str(
-            full_code, mode=black.FileMode([black.TargetVersion.PY37], line_length=line_length)
-        )
+        mode = black.Mode(target_versions={black.TargetVersion.PY37}, line_length=line_length)
+        formatted_code = black.format_str(full_code, mode=mode)
         error = ""
     except Exception as e:
         formatted_code = full_code