[codestyle][ruff] enable PGH004 (#57941)

* [codestyle] enable PGH004

* Update pyproject.toml

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

---------

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

pyproject.toml

@@ -72,6 +72,9 @@ select = [
     "PLR1711",
     "PLR1722",
     "PLW3301",
+
+    # Pygrep-hooks
+    "PGH004",
 ]
 unfixable = [
     "NPY001"

python/paddle/distributed/fleet/utils/__init__.py

@@ -26,7 +26,7 @@
 from . import sequence_parallel_utils
 
 
-__all__ = ["LocalFS", "recompute", "DistributedInfer", "HDFSClient"]  # noqa
+__all__ = ["LocalFS", "recompute", "DistributedInfer", "HDFSClient"]
 
 
 def recompute(function, *args, **kwargs):

python/paddle/distribution/__init__.py

@@ -32,7 +32,7 @@
 from paddle.distribution.laplace import Laplace
 from paddle.distribution.geometric import Geometric
 
-__all__ = [  # noqa
+__all__ = [
     'Bernoulli',
     'Beta',
     'Categorical',

python/paddle/distribution/transform.py

@@ -25,7 +25,7 @@
     variable,
 )
 
-__all__ = [  # noqa
+__all__ = [
     'Transform',
     'AbsTransform',
     'AffineTransform',

python/paddle/incubate/asp/__init__.py

@@ -34,7 +34,7 @@
 from .supported_layer_list import add_supported_layer  # noqa: F401
 
 
-__all__ = [  # noqa
+__all__ = [
     'calculate_density',
     'decorate',
     'prune_model',

python/paddle/incubate/autograd/__init__.py

@@ -16,7 +16,7 @@
 from .primx import prim2orig
 from .utils import disable_prim, enable_prim, prim_enabled
 
-__all__ = [  # noqa
+__all__ = [
     'vjp',
     'jvp',
     'Jacobian',

python/paddle/incubate/nn/__init__.py

@@ -24,7 +24,7 @@
 from .layer.fused_dropout_add import FusedDropoutAdd  # noqa: F401
 from .layer.fused_dropout_nd import FusedDropout  # noqa: F401
 
-__all__ = [  # noqa
+__all__ = [
     'FusedMultiHeadAttention',
     'FusedFeedForward',
     'FusedTransformerEncoderLayer',

python/paddle/inference/__init__.py

@@ -33,7 +33,7 @@
     XpuConfig,
 )
 
-__all__ = [  # noqa
+__all__ = [
     'Config',
     'DataType',
     'PlaceType',

python/paddle/io/__init__.py

@@ -30,7 +30,7 @@
 from .dataloader import Subset  # noqa: F401
 from .dataloader import random_split  # noqa: F401
 
-__all__ = [  # noqa
+__all__ = [
     'Dataset',
     'IterableDataset',
     'TensorDataset',

python/paddle/jit/__init__.py

@@ -23,7 +23,7 @@
 from .dy2static.logging_utils import set_code_level, set_verbosity
 from .translated_layer import TranslatedLayer
 
-__all__ = [  # noqa
+__all__ = [
     'save',
     'load',
     'to_static',

python/paddle/metric/__init__.py

@@ -19,7 +19,7 @@
 from .metrics import Auc  # noqa: F401
 from .metrics import accuracy  # noqa: F401
 
-__all__ = [  # noqa
+__all__ = [
     'Metric',
     'Accuracy',
     'Precision',

python/paddle/nn/__init__.py

@@ -207,7 +207,7 @@ def weight_norm(*args):
     return utils.weight_norm(*args)
 
 
-__all__ = [  # noqa
+__all__ = [
     'BatchNorm',
     'CELU',
     'GroupNorm',

python/paddle/nn/functional/__init__.py

@@ -140,7 +140,7 @@
 from .flash_attention import scaled_dot_product_attention
 from .flash_attention import sdp_kernel
 
-__all__ = [  # noqa
+__all__ = [
     'celu',
     'conv1d',
     'conv1d_transpose',

python/paddle/nn/initializer/__init__.py

@@ -45,7 +45,7 @@
 from .kaiming import MSRAInitializer  # noqa: F401
 from .assign import NumpyArrayInitializer  # noqa: F401
 
-__all__ = [  # noqa
+__all__ = [
     'Bilinear',
     'Constant',
     'KaimingUniform',

python/paddle/nn/layer/layers.py

@@ -26,7 +26,7 @@
 from paddle.base import core, framework, unique_name
 from paddle.base.core import VarDesc
 from paddle.base.dygraph import no_grad
-from paddle.base.dygraph.base import in_declarative_mode  # noqa F401
+from paddle.base.dygraph.base import in_declarative_mode  # noqa: F401
 from paddle.base.dygraph.base import (
     _convert_into_variable,
     in_to_static_mode,

python/paddle/nn/utils/__init__.py

@@ -22,7 +22,7 @@
 from .clip_grad_norm_ import clip_grad_norm_  # noqa: F401
 from .clip_grad_value_ import clip_grad_value_  # noqa: F401
 
-__all__ = [  # noqa
+__all__ = [
     'weight_norm',
     'remove_weight_norm',
     'spectral_norm',

python/paddle/optimizer/__init__.py

@@ -25,7 +25,7 @@
 from .lbfgs import LBFGS  # noqa: F401
 from . import lr  # noqa: F401
 
-__all__ = [  # noqa
+__all__ = [
     'Optimizer',
     'Adagrad',
     'Adam',

python/paddle/optimizer/lr.py

@@ -28,7 +28,7 @@
 )
 from paddle.base.layer_helper import LayerHelper
 
-__all__ = [  # noqa
+__all__ = [
     'LRScheduler',
     'NoamDecay',
     'PiecewiseDecay',

python/paddle/static/__init__.py

@@ -79,7 +79,7 @@
 from ..base.framework import program_guard  # noqa: F401
 from ..base.framework import Program  # noqa: F401
 
-__all__ = [  # noqa
+__all__ = [
     'append_backward',
     'gradients',
     'Executor',

python/paddle/static/nn/__init__.py

@@ -60,7 +60,7 @@
 from .control_flow import cond
 from .static_pylayer import static_pylayer
 
-__all__ = [  # noqa
+__all__ = [
     'fc',
     'batch_norm',
     'bilinear_tensor_product',

python/paddle/tensor/__init__.py

@@ -381,7 +381,7 @@
 from ..signal import stft  # noqa: F401
 
 # this list used in math_op_patch.py for _binary_creator_
-tensor_method_func = [  # noqa
+tensor_method_func = [
     'create_parameter',
     'create_tensor',
     'matmul',

python/paddle/text/__init__.py

@@ -21,7 +21,7 @@
 from .datasets import WMT14  # noqa: F401
 from .datasets import WMT16  # noqa: F401
 
-__all__ = [  # noqa
+__all__ = [
     'Conll05st',
     'Imdb',
     'Imikolov',

python/paddle/utils/__init__.py

@@ -53,4 +53,4 @@
 from .layers_utils import _contain_var  # noqa: F401
 from .layers_utils import _convert_to_tensor_list  # noqa: F401
 
-__all__ = ['deprecated', 'run_check', 'require_version', 'try_import']  # noqa
+__all__ = ['deprecated', 'run_check', 'require_version', 'try_import']

python/paddle/utils/cpp_extension/__init__.py

@@ -22,7 +22,7 @@
 from .extension_utils import get_build_directory  # noqa: F401
 from .extension_utils import load_op_meta_info_and_register_op  # noqa: F401
 
-__all__ = [  # noqa
+__all__ = [
     'CppExtension',
     'CUDAExtension',
     'load',

python/paddle/utils/unique_name.py

@@ -17,4 +17,4 @@
 from ..base.unique_name import guard  # noqa: F401
 from ..base.unique_name import switch  # noqa: F401
 
-__all__ = ['generate', 'switch', 'guard']  # noqa
+__all__ = ['generate', 'switch', 'guard']

python/paddle/vision/__init__.py

@@ -112,4 +112,4 @@
 from .transforms import adjust_hue  # noqa: F401
 from .transforms import normalize  # noqa: F401
 
-__all__ = ['set_image_backend', 'get_image_backend', 'image_load']  # noqa
+__all__ = ['set_image_backend', 'get_image_backend', 'image_load']

python/paddle/vision/datasets/__init__.py

@@ -21,7 +21,7 @@
 from .cifar import Cifar100  # noqa: F401
 from .voc2012 import VOC2012  # noqa: F401
 
-__all__ = [  # noqa
+__all__ = [
     'DatasetFolder',
     'ImageFolder',
     'MNIST',

python/paddle/vision/models/__init__.py

@@ -64,7 +64,7 @@
 from .shufflenetv2 import shufflenet_v2_x2_0  # noqa: F401
 from .shufflenetv2 import shufflenet_v2_swish  # noqa: F401
 
-__all__ = [  # noqa
+__all__ = [
     'ResNet',
     'resnet18',
     'resnet34',

python/paddle/vision/ops.py

@@ -26,7 +26,7 @@
 from ..nn import BatchNorm2D, Conv2D, Layer, ReLU, Sequential
 from ..nn.initializer import Normal
 
-__all__ = [  # noqa
+__all__ = [
     'yolo_loss',
     'yolo_box',
     'prior_box',

python/paddle/vision/transforms/__init__.py

@@ -51,7 +51,7 @@
 from .functional import normalize  # noqa: F401
 from .functional import erase  # noqa: F401
 
-__all__ = [  # noqa
+__all__ = [
     'BaseTransform',
     'Compose',
     'Resize',

test/autograd/test_autograd_functional_dynamic.py

@@ -145,28 +145,28 @@ def check_results(self, ref, res):
 class TestVJP(TestAutogradFunctional):
     def func_vjp_i1o1(self):
         test_cases = [
-            [reduce, 'A'],  # noqa
-            [reduce_dim, 'A'],  # noqa
-        ]  # noqa
+            [reduce, 'A'],
+            [reduce_dim, 'A'],
+        ]
         for f, inputs in test_cases:
             vjp, grad = self.gen_test_pairs(f, inputs)
             vjp_result, grad_result = vjp(), grad()
             self.check_results(grad_result, vjp_result)
 
     def func_vjp_i2o1(self):
         test_cases = [
-            [matmul, ['A', 'B']],  # noqa
-            [mul, ['b', 'c']],  # noqa
-        ]  # noqa
+            [matmul, ['A', 'B']],
+            [mul, ['b', 'c']],
+        ]
         for f, inputs in test_cases:
             vjp, grad = self.gen_test_pairs(f, inputs)
             vjp_result, grad_result = vjp(), grad()
             self.check_results(grad_result, vjp_result)
 
     def func_vjp_i2o2(self):
         test_cases = [
-            [o2, ['A', 'A']],  # noqa
-        ]  # noqa
+            [o2, ['A', 'A']],
+        ]
         for f, inputs in test_cases:
             inputs = self.gen_inputs(inputs)
             v = make_v(f, inputs)
@@ -176,8 +176,8 @@ def func_vjp_i2o2(self):
 
     def func_vjp_i2o2_omitting_v(self):
         test_cases = [
-            [o2, ['A', 'A']],  # noqa
-        ]  # noqa
+            [o2, ['A', 'A']],
+        ]
         for f, inputs in test_cases:
             inputs = self.gen_inputs(inputs)
             vjp, grad = self.gen_test_pairs(f, inputs)
@@ -187,7 +187,7 @@ def func_vjp_i2o2_omitting_v(self):
     def func_vjp_nested(self):
         x = self.gen_input('a')
         test_cases = [
-            [nested(x), 'a'],  # noqa
+            [nested(x), 'a'],
         ]
         for f, inputs in test_cases:
             vjp, grad = self.gen_test_pairs(f, inputs)
@@ -274,39 +274,39 @@ def jac(grad_fn, f, inputs):
 class TestJVP(TestAutogradFunctional):
     def func_jvp_i1o1(self):
         test_cases = [
-            [reduce, 'A'],  # noqa
-            [reduce_dim, 'A'],  # noqa
-        ]  # noqa
+            [reduce, 'A'],
+            [reduce_dim, 'A'],
+        ]
         for f, inputs in test_cases:
             inputs = self.gen_inputs(inputs)
             forward_jac = jac(paddle.incubate.autograd.jvp, f, inputs)
             reverse_jac = jac(paddle.incubate.autograd.vjp, f, inputs)
             self.check_results(forward_jac, reverse_jac)
 
     def func_jvp_i2o1(self):
-        test_cases = [  # noqa
-            [matmul, ['A', 'B']],  # noqa
-        ]  # noqa
+        test_cases = [
+            [matmul, ['A', 'B']],
+        ]
         for f, inputs in test_cases:
             inputs = self.gen_inputs(inputs)
             forward_jac = jac(paddle.incubate.autograd.jvp, f, inputs)
             reverse_jac = jac(paddle.incubate.autograd.vjp, f, inputs)
             self.check_results(forward_jac, reverse_jac)
 
     def func_jvp_i2o2(self):
-        test_cases = [  # noqa
-            [o2, ['A', 'A']],  # noqa
-        ]  # noqa
+        test_cases = [
+            [o2, ['A', 'A']],
+        ]
         for f, inputs in test_cases:
             inputs = self.gen_inputs(inputs)
             forward_jac = jac(paddle.incubate.autograd.jvp, f, inputs)
             reverse_jac = jac(paddle.incubate.autograd.vjp, f, inputs)
             self.check_results(forward_jac, reverse_jac)
 
     def func_jvp_i2o2_omitting_v(self):
-        test_cases = [  # noqa
-            [o2, ['A', 'A']],  # noqa
-        ]  # noqa
+        test_cases = [
+            [o2, ['A', 'A']],
+        ]
         for f, inputs in test_cases:
             inputs = self.gen_inputs(inputs)
             results_omitting_v = paddle.incubate.autograd.jvp(f, inputs)