[CodeStyle][W605] Add escape symbols to some strings (#46752)

* Fix W605 in tools folder by adding escape symbols

* Fix W605 in incubate and some other folders

* Fix W605 in /fluid/test folders

* Update tools/analysisPyXml.py
Co-authored-by: NNyakku Shigure <sigure.qaq@gmail.com>

* Add some changes to manual and auto escape symbols

* revert changes in transformer.py

* Fix new code with W605 error: add escape symbols

* revert changes in transformer.py

* revert changes in transformer.py
Co-authored-by: NNyakku Shigure <sigure.qaq@gmail.com>

paddle/fluid/eager/auto_code_generator/generator/codegen_utils.py

@@ -295,7 +295,7 @@ def ParseYamlForwardFromBackward(string):
     wspace = r'\s*'
     fargs = r'(.*?)'
     frets = r'(.*)'
-    pattern = f'{fname}{wspace}\({wspace}{fargs}{wspace}\){wspace}->{wspace}{frets}'
+    pattern = fr'{fname}{wspace}\({wspace}{fargs}{wspace}\){wspace}->{wspace}{frets}'
 
     m = re.search(pattern, string)
     function_name = m.group(1)
@@ -314,7 +314,7 @@ def ParseYamlForward(args_str, returns_str):
 
     fargs = r'(.*?)'
     wspace = r'\s*'
-    args_pattern = f'^\({fargs}\)$'
+    args_pattern = fr'^\({fargs}\)$'
     args_str = re.search(args_pattern, args_str.strip()).group(1)
 
     inputs_list, attrs_list = ParseYamlArgs(args_str)
@@ -329,7 +329,7 @@ def ParseYamlBackward(args_str, returns_str):
 
     fargs = r'(.*?)'
     wspace = r'\s*'
-    args_pattern = f'\({fargs}\)'
+    args_pattern = fr'\({fargs}\)'
     args_str = re.search(args_pattern, args_str).group(1)
 
     inputs_list, attrs_list = ParseYamlArgs(args_str)

python/paddle/dataset/common.py

@@ -32,7 +32,7 @@ HOME = os.path.expanduser('~')
 # If the default HOME dir does not support writing, we
 # will create a temporary folder to store the cache files.
 if not os.access(HOME, os.W_OK):
-    """
+    r"""
     gettempdir() return the name of the directory used for temporary files.
     On Windows, the directories C:\TEMP, C:\TMP, \TEMP, and \TMP, in that order.
     On all other platforms, the directories /tmp, /var/tmp, and /usr/tmp, in that order.

python/paddle/distributed/fleet/meta_parallel/sharding/group_sharded_optimizer_stage2.py

@@ -211,7 +211,7 @@ class GroupShardedOptimizerStage2(Optimizer):
             if self._broadcast_order_params is None:
                 # Params' names should be like column_linear_32.w_0 patter to get the best performance.
                 warnings.warn(
-                    "The param name passed to the optimizer doesn't follow .+_[0-9]+\..+ patter, "
+                    r"The param name passed to the optimizer doesn't follow .+_[0-9]+\..+ patter, "
                     "overlap broadcast may harm the performance.")
                 self._broadcast_order_params = self._local_params
 

python/paddle/distribution/gumbel.py

@@ -98,7 +98,7 @@ class Gumbel(TransformedDistribution):
 
     @property
     def mean(self):
-        """Mean of distribution
+        r"""Mean of distribution
 
         The mean is
 
@@ -120,7 +120,7 @@ class Gumbel(TransformedDistribution):
 
     @property
     def variance(self):
-        """Variance of distribution.
+        r"""Variance of distribution.
 
         The variance is
 
@@ -144,7 +144,7 @@ class Gumbel(TransformedDistribution):
 
     @property
     def stddev(self):
-        """Standard deviation of distribution
+        r"""Standard deviation of distribution
 
         The standard deviation is
 

python/paddle/distribution/laplace.py

@@ -105,7 +105,7 @@ class Laplace(distribution.Distribution):
 
     @property
     def variance(self):
-        """Variance of distribution.
+        r"""Variance of distribution.
 
         The variance is
 

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

@@ -20,7 +20,7 @@ import hypothesis.strategies as st
 
 
 class TestConvActMkldnnFusePass(PassAutoScanTest):
-    """
+    r"""
     x_var   f_var(persistable)
       \       /
         conv2d

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

@@ -20,7 +20,7 @@ import hypothesis.strategies as st
 
 
 class TestConvBiasMkldnnFusePass(PassAutoScanTest):
-    """
+    r"""
     x_var   f_var(persistable)
       \       /
         conv2d

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

@@ -23,7 +23,7 @@ os.environ['NVIDIA_TF32_OVERRIDE'] = '0'
 
 
 class TestConvElementwiseAdd2ActPass(PassAutoScanTest):
-    """
+    r"""
         x_var   f_var(persistable)
             \       /
                 conv2d

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

@@ -22,7 +22,7 @@ os.environ['NVIDIA_TF32_OVERRIDE'] = '0'
 
 
 class TestConvElementwiseAddActPass(PassAutoScanTest):
-    """
+    r"""
     x_var   f_var(persistable)
       \       /
          conv2d

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

@@ -24,7 +24,7 @@ os.environ['NVIDIA_TF32_OVERRIDE'] = '0'
 
 
 class TestConvEltwiseaddBnFusePass(PassAutoScanTest):
-    """
+    r"""
           x_var   f_var(persistable)
             \       /
                 conv2d

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

@@ -21,7 +21,7 @@ import hypothesis.strategies as st
 
 
 class TestConvTransposeBnFusePass(PassAutoScanTest):
-    '''
+    r'''
     conv_input   conv_weight_var(persistable)
       \       /
          conv_op

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

@@ -21,7 +21,7 @@ import hypothesis.strategies as st
 
 
 class TestConvTransposeEltwiseaddBnFusePass(PassAutoScanTest):
-    '''
+    r'''
     conv_input   conv_weight_var(persistable)
       \       /
          conv_op

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

@@ -23,7 +23,7 @@ import hypothesis.strategies as st
 
 
 class TestEmbeddingEltwiseLayerNormFusePass(PassAutoScanTest):
-    '''
+    r'''
   in_var1  emb_var   in_var2   emb_var   in_var3   emb_var   in_var   emb_var
     |        |        |         |        |         |           |         |
    lookup_table      lookup_table       lookup_table   ...    lookup_table

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

@@ -34,7 +34,7 @@ class FcElementLayernormFusePassDataGen:
 
 
 class TestFCElementwiseLayerNormFusePass(PassAutoScanTest):
-    """
+    r"""
     x_var   w(persistable) bias_var(persistable)
       \     |              /
           fc

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

@@ -22,7 +22,7 @@ import hypothesis.strategies as st
 
 
 class TestFcFusePass(PassAutoScanTest):
-    """
+    r"""
     x_var   y_var(persistable)
       \       /
          mul     bias_var(persistable)

python/paddle/fluid/tests/unittests/ir/inference/test_flatten2_matmul_fuse_pass.py

@@ -20,7 +20,7 @@ import hypothesis.strategies as st
 
 
 class TestFlatten2MatmulFusePass(PassAutoScanTest):
-    """
+    r"""
         x_var
           |
        flatten2

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

@@ -21,7 +21,7 @@ import hypothesis.strategies as st
 
 
 class TestFcFusePass(PassAutoScanTest):
-    """
+    r"""
              x_var
               / \
              /   reduce_mean "u(x)"

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

@@ -20,7 +20,7 @@ import hypothesis.strategies as st
 
 
 class TestMapMatmulToMulPass(PassAutoScanTest):
-    """
+    r"""
      x_var    y_var(persistable)
        \       /
          matmul

python/paddle/fluid/tests/unittests/ir/inference/test_map_matmul_v2_to_matmul_pass.py

@@ -20,7 +20,7 @@ import hypothesis.strategies as st
 
 
 class TestMapMatmulToMulPass(PassAutoScanTest):
-    """
+    r"""
      x_var    y_var(persistable)
        \       /
         matmul_v2

python/paddle/fluid/tests/unittests/ir/inference/test_map_matmul_v2_to_mul_pass.py

@@ -20,7 +20,7 @@ import hypothesis.strategies as st
 
 
 class TestMapMatmulToMulPass(PassAutoScanTest):
-    """
+    r"""
      x_var    y_var(persistable)
        \       /
        matmul_v2

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

@@ -20,7 +20,7 @@ import hypothesis.strategies as st
 
 
 class TestMatmulScaleFusePass(PassAutoScanTest):
-    """
+    r"""
      x_var    y_var(persistable)
        \       /
         matmul

python/paddle/fluid/tests/unittests/ir/inference/test_matmul_v2_scale_fuse_pass.py

@@ -20,7 +20,7 @@ import hypothesis.strategies as st
 
 
 class TestMatmulV2ScaleFusePass(PassAutoScanTest):
-    """
+    r"""
      x_var    y_var(persistable)        x_var    y_var*scale(persistable)
        \       /                           \       /
         matmul_v2                          matmul_v2

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

@@ -21,7 +21,7 @@ import hypothesis.strategies as st
 
 
 class DepthwiseConvMKLDNNPass(PassAutoScanTest):
-    '''
+    r'''
     conv_input   conv_weight_var(persistable)
       \       /
          conv_op

python/paddle/fluid/tests/unittests/ir/inference/test_reshape2_matmul_fuse_pass.py

@@ -20,7 +20,7 @@ import hypothesis.strategies as st
 
 
 class TestReshape2MatmulFusePass(PassAutoScanTest):
-    """
+    r"""
         x_var
           |
        reshape2

python/paddle/fluid/tests/unittests/ir/inference/test_squeeze2_matmul_fuse_pass.py

@@ -20,7 +20,7 @@ import hypothesis.strategies as st
 
 
 class TestSqueeze2MatmulFusePass(PassAutoScanTest):
-    """
+    r"""
         x_var
           |
        squeeze2

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

@@ -20,7 +20,7 @@ import hypothesis.strategies as st
 
 
 class TestTransposeFlattenConcatFusePass(PassAutoScanTest):
-    """
+    r"""
         x_1_var              x_2_var
           |                     |
       transpose2            transpose2

python/paddle/fluid/tests/unittests/ir/inference/test_trt_flatten2_matmul_fuse_pass.py

@@ -21,7 +21,7 @@ import hypothesis.strategies as st
 
 
 class TestFlatten2MatmulFusePass(PassAutoScanTest):
-    """
+    r"""
         x_var
           |
        flatten2

python/paddle/fluid/tests/unittests/ir/inference/test_trt_squeeze2_matmul_fuse_pass.py

@@ -21,7 +21,7 @@ import hypothesis.strategies as st
 
 
 class TestSqueeze2MatmulFusePass(PassAutoScanTest):
-    """
+    r"""
         x_var
           |
        squeeze2

python/paddle/fluid/tests/unittests/ir/inference/test_unsqueeze2_eltwise_fuse_pass.py

@@ -21,7 +21,7 @@ import hypothesis.strategies as st
 
 
 class TestUnsqueezeEltwiseFusePass(PassAutoScanTest):
-    """
+    r"""
         y_var
           |
        unsqueeze2

python/paddle/incubate/nn/layer/fused_linear.py

@@ -17,7 +17,7 @@ from paddle.incubate.nn import functional as F
 
 
 class FusedLinear(Layer):
-    """
+    r"""
     Linear layer takes only one multi-dimensional tensor as input with the
     shape :math:`[batch\_size, *, in\_features]` , where :math:`*` means any
     number of additional dimensions. It multiplies input tensor with the weight

python/paddle/incubate/nn/layer/fused_transformer.py

@@ -1246,7 +1246,7 @@ class FusedMultiTransformer(Layer):
                 caches=None,
                 pre_caches=None,
                 time_step=None):
-        """
+        r"""
         Applies multi transformer layers on the input.
 
         Parameters:

python/paddle/incubate/sparse/nn/functional/activation.py

@@ -61,7 +61,7 @@ def relu(x, name=None):
 
 @dygraph_only
 def softmax(x, axis=-1, name=None):
-    """
+    r"""
     sparse softmax activation, requiring x to be a SparseCooTensor or SparseCsrTensor.
 
     Note:
@@ -146,7 +146,7 @@ def relu6(x, name=None):
 
 @dygraph_only
 def leaky_relu(x, negative_slope=0.01, name=None):
-    """
+    r"""
     sparse leaky_relu activation, requiring x to be a SparseCooTensor or SparseCsrTensor.
 
     .. math::

python/paddle/incubate/sparse/nn/layer/activation.py

@@ -59,7 +59,7 @@ class ReLU(Layer):
 
 
 class Softmax(Layer):
-    """
+    r"""
     Sparse Softmax Activation, requiring x to be a SparseCooTensor or SparseCsrTensor.
 
     Note:
@@ -164,7 +164,7 @@ class ReLU6(Layer):
 
 
 class LeakyReLU(Layer):
-    """
+    r"""
     Sparse Leaky ReLU Activation, requiring x to be a SparseCooTensor or SparseCsrTensor.
 
     .. math::

python/paddle/incubate/sparse/unary.py

@@ -548,7 +548,7 @@ def coalesce(x):
 
 @dygraph_only
 def rad2deg(x, name=None):
-    """
+    r"""
     Convert each of the elements of input x from radian to degree,
     requiring x to be a SparseCooTensor or SparseCsrTensor.
 
@@ -581,7 +581,7 @@ def rad2deg(x, name=None):
 
 @dygraph_only
 def deg2rad(x, name=None):
-    """
+    r"""
     Convert each of the elements of input x from degree to radian,
     requiring x to be a SparseCooTensor or SparseCsrTensor.
 

python/paddle/nn/functional/pooling.py

@@ -1381,7 +1381,7 @@ def adaptive_avg_pool1d(x, output_size, name=None):
 
 
 def adaptive_avg_pool2d(x, output_size, data_format='NCHW', name=None):
-    """
+    r"""
     Applies 2D adaptive avg pooling on input tensor. The h and w dimensions
     of the output tensor are determined by the parameter output_size.
 
@@ -1502,7 +1502,7 @@ def adaptive_avg_pool2d(x, output_size, data_format='NCHW', name=None):
 
 
 def adaptive_avg_pool3d(x, output_size, data_format='NCDHW', name=None):
-    """
+    r"""
     This operation applies 3D adaptive avg pooling on input tensor. The h and w dimensions
     of the output tensor are determined by the parameter output_size.
 

python/paddle/profiler/profiler_statistic.py

@@ -1399,7 +1399,7 @@ def _build_table(statistic_data,
             append(header_sep)
             append(row_format.format(*headers))
             append(header_sep)
-            kernel_name_pattern = re.compile('(.+?)(<.*>)(\(.*\))')
+            kernel_name_pattern = re.compile(r'(.+?)(<.*>)(\(.*\))')
             for row_values in all_row_values:
                 match = kernel_name_pattern.match(row_values[0])
                 if match:

python/paddle/tensor/random.py

@@ -28,13 +28,13 @@ __all__ = []
 
 
 def bernoulli(x, name=None):
-    """
+    r"""
 
     For each element :math:`x_i` in input ``x``, take a sample from the Bernoulli distribution, also called two-point distribution, with success probability :math:`x_i`. The Bernoulli distribution with success probability :math:`x_i` is a discrete probability distribution with probability mass function
 
     .. math::
-        p(y)=\\begin{cases}
-            x_i,&y=1\\\\
+        p(y)=\begin{cases}
+            x_i,&y=1\\
             1-x_i,&y=0
         \end{cases}.
 

tools/analysisPyXml.py

@@ -45,7 +45,7 @@ def analysisPyXml(rootPath, ut):
                          '@', '\'\'\'', 'logger', '_logger', 'logging', 'r"""',
                          'pass', 'try', 'except',
                          'if __name__ == "__main__"')) == False:
-                        pattern = "(.*) = ('*')|(.*) = (\"*\")|(.*) = (\d)|(.*) = (-\d)|(.*) = (None)|(.*) = (True)|(.*) = (False)|(.*) = (URL_PREFIX*)|(.*) = (\[)|(.*) = (\{)|(.*) = (\()"  #a='b'/a="b"/a=0
+                        pattern = r"""(.*) = ('*')|(.*) = ("*")|(.*) = (\d)|(.*) = (-\d)|(.*) = (None)|(.*) = (True)|(.*) = (False)|(.*) = (URL_PREFIX*)|(.*) = (\[)|(.*) = (\{)|(.*) = (\()"""  #a='b'/a="b"/a=0
                         if re.match(pattern, output.strip()) == None:
                             pyCov_file.append(clazz_filename)
                             coverageMessage = 'RELATED'

tools/get_pr_ut.py

@@ -36,12 +36,12 @@ class PRChecker(object):
     def __init__(self):
         self.github = Github(os.getenv('GITHUB_API_TOKEN'), timeout=60)
         self.repo = self.github.get_repo('PaddlePaddle/Paddle')
-        self.py_prog_oneline = re.compile('\d+\|\s*#.*')
+        self.py_prog_oneline = re.compile(r'\d+\|\s*#.*')
         self.py_prog_multiline_a = re.compile('"""(.*?)"""', re.DOTALL)
         self.py_prog_multiline_b = re.compile("'''(.*?)'''", re.DOTALL)
-        self.cc_prog_online = re.compile('\d+\|\s*//.*')
-        self.cc_prog_multiline = re.compile('\d+\|\s*/\*.*?\*/', re.DOTALL)
-        self.lineno_prog = re.compile('@@ \-\d+,\d+ \+(\d+),(\d+) @@')
+        self.cc_prog_online = re.compile(r'\d+\|\s*//.*')
+        self.cc_prog_multiline = re.compile(r'\d+\|\s*/\*.*?\*/', re.DOTALL)
+        self.lineno_prog = re.compile(r'@@ \-\d+,\d+ \+(\d+),(\d+) @@')
         self.pr = None
         self.suffix = ''
         self.full_case = False

tools/get_ut_file_map.py

@@ -34,7 +34,7 @@ def get_all_paddle_file(rootPath):
 def get_all_uts(rootPath):
     all_uts_paddle = '%s/build/all_uts_paddle' % rootPath
     os.system(
-        'cd %s/build && ctest -N -V | grep -Ei "Test[ \t]+#" | grep -oEi "\w+$" > %s'
+        r'cd %s/build && ctest -N -V | grep -Ei "Test[ \t]+#" | grep -oEi "\w+$" > %s'
         % (rootPath, all_uts_paddle))
 
 

tools/infrt/generate_pd_op_dialect_from_paddle_op_maker.py

@@ -217,7 +217,7 @@ def convert_op_proto_into_mlir(op_descs):
 |* Automatically generated file, do not edit!                                 *|\n\
 |* Generated by tools/infrt/generate_pd_op_dialect_from_paddle_op_maker.py    *|\n\
 |*                                                                            *|\n\
-\*===----------------------------------------------------------------------===*/\n"
+\\*===----------------------------------------------------------------------===*/\n"
 
     lines = [
         "#ifndef PD_OPS",

tools/infrt/generate_phi_kernel_dialect.py

@@ -261,7 +261,7 @@ def generate_dialect_head():
 |* Automatically generated file, do not edit!                                 *|\n\
 |* Generated by tools/infrt/generate_pten_kernel_dialect.py                   *|\n\
 |*                                                                            *|\n\
-\*===----------------------------------------------------------------------===*/\n"
+\\*===----------------------------------------------------------------------===*/\n"
 
     includes_ = "#ifndef PTEN_KERNELS\n\
 #define PTEN_KERNELS\n\

tools/infrt/get_compat_kernel_signature.py

@@ -65,7 +65,7 @@ def get_compat_kernels_info():
                     data = content.replace("\n", "").replace(
                         " ",
                         "").strip("return").strip("KernelSignature(").strip(
-                            "\);").replace("\"", "").replace("\\", "")
+                            r"\);").replace("\"", "").replace("\\", "")
                     registry = False
                     if is_grad_kernel(data):
                         continue

tools/jetson_infer_op.py

@@ -155,7 +155,7 @@ def set_diff_value(file, atol="1e-5", inplace_atol="1e-7"):
     :param inplace_atol:
     :return:
     """
-    os.system("sed -i 's/self.check_output(/self\.check_output\(atol=" + atol +
+    os.system(r"sed -i 's/self.check_output(/self\.check_output\(atol=" + atol +
               ",inplace_atol=" + inplace_atol + ",/g\' " + file)
 
 
@@ -179,8 +179,8 @@ def change_op_file(start=0, end=0, op_list_file='list_op.txt', path='.'):
         file_with_path = file_path[0]
         # pattern
         pattern_import = ".*import OpTest.*"
-        pattern_skip = "^class .*\(OpTest\):$"
-        pattern_return = "def test.*grad.*\):$"
+        pattern_skip = r"^class .*\(OpTest\):$"
+        pattern_return = r"def test.*grad.*\):$"
         # change file
         add_import_skip_return(file_with_path, pattern_import, pattern_skip,
                                pattern_return)

tools/prune_for_jetson.py

@@ -77,7 +77,7 @@ def prune_phi_kernels():
         all_matches = []
         with open(op_file, 'r', encoding='utf-8') as f:
             content = ''.join(f.readlines())
-            op_pattern = 'PD_REGISTER_KERNEL\(.*?\).*?\{.*?\}'
+            op_pattern = r'PD_REGISTER_KERNEL\(.*?\).*?\{.*?\}'
             op, op_count = find_kernel(content, op_pattern)
             register_op_count += op_count
             all_matches.extend(op)
@@ -143,11 +143,12 @@ def append_fluid_kernels():
 
         for op in op_white_list:
             patterns = {
-                "REGISTER_OPERATOR": "REGISTER_OPERATOR\(\s*%s\s*," % op,
+                "REGISTER_OPERATOR":
+                r"REGISTER_OPERATOR\(\s*%s\s*," % op,
                 "REGISTER_OP_CPU_KERNEL":
-                "REGISTER_OP_CPU_KERNEL\(\s*%s\s*," % op,
+                r"REGISTER_OP_CPU_KERNEL\(\s*%s\s*," % op,
                 "REGISTER_OP_CUDA_KERNEL":
-                "REGISTER_OP_CUDA_KERNEL\(\s*%s\s*," % op
+                r"REGISTER_OP_CUDA_KERNEL\(\s*%s\s*," % op
             }
             for k, p in patterns.items():
                 matches = re.findall(p, content, flags=re.DOTALL)

tools/remove_grad_op_and_kernel.py

@@ -43,7 +43,7 @@ def remove_grad_op_and_kernel(content, pattern1, pattern2):
 
 def update_operator_cmake(cmake_file):
     pat1 = 'add_subdirectory(optimizers)'
-    pat2 = 'register_operators\(EXCLUDES.*?py_func_op.*?\)'
+    pat2 = r'register_operators\(EXCLUDES.*?py_func_op.*?\)'
 
     code1 = 'if(ON_INFER)\nadd_subdirectory(optimizers)\nendif()'
     code2 = 'if(ON_INFER)\nfile(GLOB LOSS_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "*loss_op.cc")\nstring(REPLACE ".cc" "" LOSS_OPS "${LOSS_OPS}")\nendif()'
@@ -80,27 +80,27 @@ if __name__ == '__main__':
     # 1. remove all grad op and kernel
     for op_file in all_op:
         # remove all grad op
-        op_pattern1 = 'REGISTER_OPERATOR\(.*?\);?'
-        op_pattern2 = 'REGISTER_OPERATOR\(.*?_grad,.*?\);?'
+        op_pattern1 = r'REGISTER_OPERATOR\(.*?\);?'
+        op_pattern2 = r'REGISTER_OPERATOR\(.*?_grad,.*?\);?'
 
         # remove all cpu grad kernel
-        cpu_kernel_pattern1 = 'REGISTER_OP_CPU_KERNEL\(.*?\);?'
-        cpu_kernel_pattern2 = 'REGISTER_OP_CPU_KERNEL\(.*?_grad,.*?\);?'
+        cpu_kernel_pattern1 = r'REGISTER_OP_CPU_KERNEL\(.*?\);?'
+        cpu_kernel_pattern2 = r'REGISTER_OP_CPU_KERNEL\(.*?_grad,.*?\);?'
 
         # remove all gpu grad kernel
-        gpu_kernel_pattern1 = 'REGISTER_OP_CUDA_KERNEL\(.*?\);?'
-        gpu_kernel_pattern2 = 'REGISTER_OP_CUDA_KERNEL\(.*?_grad,.*?\);?'
+        gpu_kernel_pattern1 = r'REGISTER_OP_CUDA_KERNEL\(.*?\);?'
+        gpu_kernel_pattern2 = r'REGISTER_OP_CUDA_KERNEL\(.*?_grad,.*?\);?'
 
         # remove all xpu grad kernel
-        xpu_kernel_pattern1 = 'REGISTER_OP_XPU_KERNEL\(.*?\);?'
-        xpu_kernel_pattern2 = 'REGISTER_OP_XPU_KERNEL\(.*?_grad,.*?\);?'
+        xpu_kernel_pattern1 = r'REGISTER_OP_XPU_KERNEL\(.*?\);?'
+        xpu_kernel_pattern2 = r'REGISTER_OP_XPU_KERNEL\(.*?_grad,.*?\);?'
 
         # remove custom grad kernel, mkldnn or cudnn etc.
-        op_kernel_pattern1 = 'REGISTER_OP_KERNEL\(.*?\);?'
-        op_kernel_pattern2 = 'REGISTER_OP_KERNEL\(.*?_grad,.*?\);?'
+        op_kernel_pattern1 = r'REGISTER_OP_KERNEL\(.*?\);?'
+        op_kernel_pattern2 = r'REGISTER_OP_KERNEL\(.*?_grad,.*?\);?'
 
-        custom_pattern1 = 'REGISTER_OP_KERNEL_WITH_CUSTOM_TYPE\(.*?\);?'
-        custom_pattern2 = 'REGISTER_OP_KERNEL_WITH_CUSTOM_TYPE\(.*?_grad,.*?\);?'
+        custom_pattern1 = r'REGISTER_OP_KERNEL_WITH_CUSTOM_TYPE\(.*?\);?'
+        custom_pattern2 = r'REGISTER_OP_KERNEL_WITH_CUSTOM_TYPE\(.*?_grad,.*?\);?'
 
         op_name = os.path.split(op_file)[1]
         if op_name in spec_ops: