[CodeStyle][UP034] remove (()) cases (#52060)

* add up34

* modify var name in loop

* revert changes in test_slice

* Revert "modify var name in loop"

This reverts commit 6d748e3.

* temporarily ignore test_slice.py

* add comment

* empty commit, re-trigger all ci

* fix inc

---------

Co-authored-by: SigureMo <sigure.qaq@gmail.com>

paddle/fluid/operators/generator/cross_validate.py

@@ -26,7 +26,7 @@ def main(forward_op_yaml_paths, backward_op_yaml_paths):
         with open(op_yaml_path, "rt", encoding="utf-8") as f:
             op_list = yaml.safe_load(f)
             if op_list is not None:
-                ops.update(to_named_dict((op_list)))
+                ops.update(to_named_dict(op_list))
 
     cross_validate(ops)
 

pyproject.toml

@@ -80,7 +80,7 @@ select = [
     # "UP031",
     # "UP032",
     "UP033",
-    # "UP034",
+    "UP034",
     "UP035",
     "UP036",
 
@@ -168,6 +168,11 @@ unfixable = [
 ]
 
 [tool.ruff.per-file-ignores]
+# Ignore unused imports in __init__.py
 "__init__.py" = ["F401"]
+# Temporarily ignore test_slice.py to avoid PR-CI-CINN failure, please fix!
+"python/paddle/fluid/tests/unittests/dygraph_to_static/test_slice.py" = ["UP034"]
+# Ignore version check in setup.py
 "setup.py" = ["UP036"]
+# Ignore unnecessary lambda in dy2st unittest test_lambda
 "python/paddle/fluid/tests/unittests/dygraph_to_static/test_lambda.py" = ["PLC3002"]

python/paddle/distributed/auto_parallel/tuner/profiler.py

@@ -270,7 +270,7 @@ def profiler(args):
             with open(result_path, 'w') as fp:
                 json.dump(result_dict, fp)
 
-        print("profile done! avg speed : {} step / s.".format((avg_tput)))
+        print("profile done! avg speed : {} step / s.".format(avg_tput))
 
     except paddle.framework.core.EOFException:
         data_loader._inner_dataloader.reset()

python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_parser.py

@@ -219,7 +219,7 @@ def _create_ge_tensor(self, shape, dtype, value):
         tensor = core.GETensor(tensor_desc)
 
         data = (
-            (value * np.ones((shape)))
+            (value * np.ones(shape))
             .reshape(shape)
             .astype(self.ascend_helper.dtype2np(dtype))
         )
@@ -282,7 +282,7 @@ def _create_shape_tensor(self):
         )
         tensor = core.GETensor(tensor_desc)
 
-        data = np.ones((2)).astype("int32").reshape([2])
+        data = np.ones(2).astype("int32").reshape([2])
         data[0] = 64
         buf = data.tobytes()
         data_8 = np.frombuffer(buf, dtype=np.uint8)

python/paddle/distribution/normal.py

@@ -241,7 +241,7 @@ def entropy(self):
         )
         return paddle.add(
             0.5 + zero_tmp,
-            0.5 * math.log(2 * math.pi) + paddle.log((self.scale + zero_tmp)),
+            0.5 * math.log(2 * math.pi) + paddle.log(self.scale + zero_tmp),
             name=name,
         )
 

python/paddle/fluid/tests/unittests/distribution/test_distribution_transform.py

@@ -1185,7 +1185,7 @@ def test_domain(self):
     def test_codomain(self):
         self.assertTrue(isinstance(self._t._codomain, variable.Variable))
 
-    @param.param_func(((np.random.random((10)),),))
+    @param.param_func(((np.random.random(10),),))
     def test_forward(self, input):
         np.testing.assert_allclose(
             self._t.inverse(self._t.forward(paddle.to_tensor(input))),
@@ -1202,7 +1202,7 @@ def test_forward_shape(self, shape, expected_shape):
     def test_inverse_shape(self, shape, expected_shape):
         self.assertEqual(self._t.inverse_shape(shape), expected_shape)
 
-    @param.param_func(((np.random.random((10)),),))
+    @param.param_func(((np.random.random(10),),))
     def test_forward_log_det_jacobian(self, x):
         self.assertEqual(
             self._t.forward_log_det_jacobian(paddle.to_tensor(x)).shape, [1]

python/paddle/fluid/tests/unittests/dygraph_to_static/test_basic_api_transformation.py

@@ -456,7 +456,7 @@ def _dygraph_fn():
     x = np.random.random((1, 3)).astype('float32')
     with fluid.dygraph.guard():
         fluid.dygraph.to_variable(x)
-        np.random.random((1))
+        np.random.random(1)
 
 
 class TestDygraphApiRecognition(unittest.TestCase):

python/paddle/fluid/tests/unittests/dygraph_to_static/test_break_continue.py

@@ -204,7 +204,7 @@ def test_optim_break_in_while(x):
 
 class TestContinueInFor(unittest.TestCase):
     def setUp(self):
-        self.input = np.zeros((1)).astype('int64')
+        self.input = np.zeros(1).astype('int64')
         self.place = (
             fluid.CUDAPlace(0)
             if fluid.is_compiled_with_cuda()

python/paddle/fluid/tests/unittests/dygraph_to_static/test_cache_program.py

@@ -138,7 +138,7 @@ def test_cache(self):
 
 @to_static
 def sum_even_until_limit(max_len, limit):
-    ret_sum = fluid.dygraph.to_variable(np.zeros((1)).astype('int32'))
+    ret_sum = fluid.dygraph.to_variable(np.zeros(1).astype('int32'))
     for i in range(max_len):
         if i % 2 > 0:
             continue
@@ -150,8 +150,8 @@ def sum_even_until_limit(max_len, limit):
 
 
 def sum_under_while(limit):
-    i = fluid.dygraph.to_variable(np.zeros((1)).astype('int32'))
-    ret_sum = fluid.dygraph.to_variable(np.zeros((1)).astype('int32'))
+    i = fluid.dygraph.to_variable(np.zeros(1).astype('int32'))
+    ret_sum = fluid.dygraph.to_variable(np.zeros(1).astype('int32'))
     while i <= limit:
         ret_sum += i
         i += 1

python/paddle/fluid/tests/unittests/dygraph_to_static/test_dict.py

@@ -171,7 +171,7 @@ def test_dic_pop_2(x):
 
 class TestDictPop(unittest.TestCase):
     def setUp(self):
-        self.input = np.random.random((3)).astype('int32')
+        self.input = np.random.random(3).astype('int32')
         self.place = (
             paddle.CUDAPlace(0)
             if paddle.is_compiled_with_cuda()

python/paddle/fluid/tests/unittests/dygraph_to_static/test_list.py

@@ -219,7 +219,7 @@ def setUp(self):
         self.init_dygraph_func()
 
     def init_data(self):
-        self.input = np.random.random((3)).astype('int32')
+        self.input = np.random.random(3).astype('int32')
 
     def init_dygraph_func(self):
         self.all_dygraph_funcs = [
@@ -275,7 +275,7 @@ def init_dygraph_func(self):
 
 class TestListInWhileLoop(TestListWithoutControlFlow):
     def init_data(self):
-        self.input = np.random.random((3)).astype('int32')
+        self.input = np.random.random(3).astype('int32')
         self.iter_num = 3
 
     def init_dygraph_func(self):

python/paddle/fluid/tests/unittests/dygraph_to_static/test_return.py

@@ -265,7 +265,7 @@ def func():
 
 class TestReturnBase(unittest.TestCase):
     def setUp(self):
-        self.input = np.ones((1)).astype('int32')
+        self.input = np.ones(1).astype('int32')
         self.place = (
             fluid.CUDAPlace(0)
             if fluid.is_compiled_with_cuda()

python/paddle/fluid/tests/unittests/dygraph_to_static/test_transformer.py

@@ -108,7 +108,7 @@ def train_static(args, batch_generator):
             # the best cross-entropy value with label smoothing
             loss_normalizer = -(
                 (1.0 - args.label_smooth_eps)
-                * np.log((1.0 - args.label_smooth_eps))
+                * np.log(1.0 - args.label_smooth_eps)
                 + args.label_smooth_eps
                 * np.log(
                     args.label_smooth_eps / (args.trg_vocab_size - 1) + 1e-20
@@ -221,8 +221,7 @@ def train_dygraph(args, batch_generator):
         )
         # the best cross-entropy value with label smoothing
         loss_normalizer = -(
-            (1.0 - args.label_smooth_eps)
-            * np.log((1.0 - args.label_smooth_eps))
+            (1.0 - args.label_smooth_eps) * np.log(1.0 - args.label_smooth_eps)
             + args.label_smooth_eps
             * np.log(args.label_smooth_eps / (args.trg_vocab_size - 1) + 1e-20)
         )

python/paddle/fluid/tests/unittests/ipu/test_modelruntime_ipu.py

@@ -123,10 +123,8 @@ def _test(self, use_ipu=False):
                 pad_batch = self.batch_size - dy_batch
                 for k, v in feed.items():
                     pad_size = tuple(
-                        (
-                            (0, 0 if i != 0 else pad_batch)
-                            for i in range(len(v.shape))
-                        )
+                        (0, 0 if i != 0 else pad_batch)
+                        for i in range(len(v.shape))
                     )
                     feed[k] = np.pad(v, pad_size, 'constant', constant_values=0)
 

python/paddle/fluid/tests/unittests/ir/inference/test_conv_elementwise_add2_act_fuse_pass.py

@@ -62,24 +62,20 @@ def is_program_valid(self, prog_config):
             if (
                 int(
                     (
-                        (
-                            input_shape[2]
-                            - (dilations[0] * (filter_shape[2] - 1) + 1)
-                        )
-                        / strides[0]
-                        + 1
+                        input_shape[2]
+                        - (dilations[0] * (filter_shape[2] - 1) + 1)
                     )
+                    / strides[0]
+                    + 1
                 )
                 <= 0
                 or int(
                     (
-                        (
-                            input_shape[3]
-                            - (dilations[1] * (filter_shape[3] - 1) + 1)
-                        )
-                        / strides[1]
-                        + 1
+                        input_shape[3]
+                        - (dilations[1] * (filter_shape[3] - 1) + 1)
                     )
+                    / strides[1]
+                    + 1
                 )
                 <= 0
             ):
@@ -88,28 +84,24 @@ def is_program_valid(self, prog_config):
             if (
                 int(
                     (
-                        (
-                            input_shape[2]
-                            + paddings[0]
-                            + paddings[1]
-                            - (dilations[0] * (filter_shape[2] - 1) + 1)
-                        )
-                        / strides[0]
-                        + 1
+                        input_shape[2]
+                        + paddings[0]
+                        + paddings[1]
+                        - (dilations[0] * (filter_shape[2] - 1) + 1)
                     )
+                    / strides[0]
+                    + 1
                 )
                 <= 0
                 or int(
                     (
-                        (
-                            input_shape[3]
-                            + paddings[2]
-                            + paddings[3]
-                            - (dilations[1] * (filter_shape[3] - 1) + 1)
-                        )
-                        / strides[1]
-                        + 1
+                        input_shape[3]
+                        + paddings[2]
+                        + paddings[3]
+                        - (dilations[1] * (filter_shape[3] - 1) + 1)
                     )
+                    / strides[1]
+                    + 1
                 )
                 <= 0
             ):
@@ -206,27 +198,23 @@ def sample_program_config(self, draw):
                 f_shape[0],
                 int(
                     (
-                        (
-                            x_shape[2]
-                            + padding[0]
-                            + padding[1]
-                            - (dilations[0] * (f_shape[2] - 1) + 1)
-                        )
-                        / strides[0]
-                        + 1
+                        x_shape[2]
+                        + padding[0]
+                        + padding[1]
+                        - (dilations[0] * (f_shape[2] - 1) + 1)
                     )
+                    / strides[0]
+                    + 1
                 ),
                 int(
                     (
-                        (
-                            x_shape[3]
-                            + padding[2]
-                            + padding[3]
-                            - (dilations[1] * (f_shape[3] - 1) + 1)
-                        )
-                        / strides[1]
-                        + 1
+                        x_shape[3]
+                        + padding[2]
+                        + padding[3]
+                        - (dilations[1] * (f_shape[3] - 1) + 1)
                     )
+                    / strides[1]
+                    + 1
                 ),
             ]
 
@@ -241,18 +229,14 @@ def sample_program_config(self, draw):
                 x_shape[0],
                 f_shape[0],
                 int(
-                    (
-                        (x_shape[2] - (dilations[0] * (f_shape[2] - 1) + 1))
-                        / strides[0]
-                        + 1
-                    )
+                    (x_shape[2] - (dilations[0] * (f_shape[2] - 1) + 1))
+                    / strides[0]
+                    + 1
                 ),
                 int(
-                    (
-                        (x_shape[3] - (dilations[1] * (f_shape[3] - 1) + 1))
-                        / strides[1]
-                        + 1
-                    )
+                    (x_shape[3] - (dilations[1] * (f_shape[3] - 1) + 1))
+                    / strides[1]
+                    + 1
                 ),
             ]
             bias_index = 1

python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_prelu_op.py

@@ -42,7 +42,7 @@ def generate_alpha(*args, **kwargs):
             elif kwargs["mode"] == "channel":
                 if len(kwargs['in_shape']) <= 1:
                     # not valid case, just return 0
-                    return np.zeros((1)).astype(np.float32)
+                    return np.zeros(1).astype(np.float32)
                 if kwargs['data_format'] == 'NCHW':
                     return np.random.random(kwargs['in_shape'][1]).astype(
                         np.float32
@@ -54,7 +54,7 @@ def generate_alpha(*args, **kwargs):
             else:
                 if len(kwargs['in_shape']) <= 1:
                     # not valid case, just return 0
-                    return np.zeros((1)).astype(np.float32)
+                    return np.zeros(1).astype(np.float32)
                 return np.random.random(kwargs['in_shape']).astype(np.float32)
 
         prelu_op = OpConfig(

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_where.py

@@ -35,7 +35,7 @@ def sample_program_configs(self):
 
         def generate_input1(dims, batch):
             if dims == 1:
-                return np.zeros((batch)).astype(np.float32)
+                return np.zeros(batch).astype(np.float32)
             elif dims == 2:
                 return np.ones((batch, 4)).astype(np.float32)
             elif dims == 3:
@@ -45,7 +45,7 @@ def generate_input1(dims, batch):
 
         def generate_input2(dims, batch):
             if dims == 1:
-                return np.zeros((batch)).astype(np.float32)
+                return np.zeros(batch).astype(np.float32)
             elif dims == 2:
                 return np.ones((batch, 4)).astype(np.float32)
             elif dims == 3:
@@ -55,7 +55,7 @@ def generate_input2(dims, batch):
 
         def generate_input3(dims, batch):
             if dims == 1:
-                return np.zeros((batch)).astype(np.float32)
+                return np.zeros(batch).astype(np.float32)
             elif dims == 2:
                 return np.ones((batch, 4)).astype(np.float32)
             elif dims == 3:

python/paddle/fluid/tests/unittests/mkldnn/test_expand_v2_mkldnn_op.py

@@ -90,7 +90,7 @@ def calc_expand_shapes_tensor(self):
         self.expand_shapes_tensor = []
         for index, ele in enumerate(self.expand_shape):
             self.expand_shapes_tensor.append(
-                ("x" + str(index), np.ones((1)).astype('int32') * ele)
+                ("x" + str(index), np.ones(1).astype('int32') * ele)
             )
 
     def set_additional_inputs(self):

python/paddle/fluid/tests/unittests/mkldnn/test_fc_int8_mkldnn_op.py

@@ -64,7 +64,7 @@ def generate_data(self):
 
         self.out_float = np.dot(self.x_float, self.y_float)
         if self.use_bias:
-            self.bias = np.random.random((10)).astype("float32") * 10
+            self.bias = np.random.random(10).astype("float32") * 10
             self.out_float += self.bias
 
         self.out_scale, self.out = self.quantize(self.out_float)