[CodeStyle][task 1] enable Ruff UP032 rule with . except python/paddle/base

paddle/phi/api/yaml/generator/api_gen.py

@@ -305,9 +305,7 @@ def gene_output(
                         )
         else:
             raise ValueError(
-                "{} : Output error: the output should not be empty.".format(
-                    self.api
-                )
+                f"{self.api} : Output error: the output should not be empty."
             )
 
         return kernel_output, output_names, output_create

paddle/phi/api/yaml/generator/backward_api_gen.py

@@ -237,9 +237,7 @@ def gene_output(
 
         else:
             raise ValueError(
-                "{} : Output error: the output should not be empty.".format(
-                    self.api
-                )
+                f"{self.api} : Output error: the output should not be empty."
             )
 
         return kernel_output, output_names, output_create

paddle/phi/api/yaml/generator/dist_api_gen.py

@@ -521,9 +521,7 @@ def generate_output_creation_code(self) -> str:
                         )
         else:
             raise ValueError(
-                "{} : Output error: the output should not be empty.".format(
-                    self.api
-                )
+                f"{self.api} : Output error: the output should not be empty."
             )
 
         return output_creation_code
@@ -984,9 +982,7 @@ def generate_reshard_partial_out_to_replicated_code(self) -> str:
                         self.vector_output_size_assertion_check()
             else:
                 raise ValueError(
-                    "{} : Output error: the output should not be empty.".format(
-                        self.api
-                    )
+                    f"{self.api} : Output error: the output should not be empty."
                 )
         else:
             # do nothing

paddle/phi/api/yaml/generator/dist_bw_api_gen.py

@@ -155,9 +155,7 @@ def generate_output_creation_code(self) -> str:
                     self.vector_output_size_assertion_check()
         else:
             raise ValueError(
-                "{} : Output error: the output should not be empty.".format(
-                    self.api
-                )
+                f"{self.api} : Output error: the output should not be empty."
             )
 
         return output_creation_code
@@ -231,9 +229,7 @@ def generate_reshard_output_code(self):
                         self.vector_output_size_assertion_check()
             else:
                 raise ValueError(
-                    "{} : Output error: the output should not be empty.".format(
-                        self.api
-                    )
+                    f"{self.api} : Output error: the output should not be empty."
                 )
         else:
             # do nothing

paddle/phi/api/yaml/generator/sparse_api_gen.py

@@ -88,9 +88,7 @@ def gene_output(
 
         else:
             raise ValueError(
-                "{} : Output error: the output should not be empty.".format(
-                    self.api
-                )
+                f"{self.api} : Output error: the output should not be empty."
             )
 
         return kernel_output, output_names, output_create

paddle/phi/api/yaml/generator/sparse_bw_api_gen.py

@@ -98,9 +98,7 @@ def gene_output(
 
         else:
             raise ValueError(
-                "{} : Output error: the output should not be empty.".format(
-                    self.api
-                )
+                f"{self.api} : Output error: the output should not be empty."
             )
 
         return kernel_output, output_names, output_create

paddle/phi/api/yaml/generator/strings_api_gen.py

@@ -107,9 +107,7 @@ def gene_output(
 
         else:
             raise ValueError(
-                "{} : Output error: the output should not be empty.".format(
-                    self.api
-                )
+                f"{self.api} : Output error: the output should not be empty."
             )
 
         return kernel_output, output_names, output_create

paddle/phi/kernels/fusion/cutlass/memory_efficient_attention/generate_kernels.py

@@ -445,13 +445,13 @@ def write_decl_impl(
 
 
 def write_main_header(forward_impl, backward_impl):
-    main_header_content = '''
+    main_header_content = f'''
 #pragma once
 
-#ifdef {}
+#ifdef {ENABLE_MACRO}
 
-#include "{}"
-#include "{}"
+#include "{forward_impl}"
+#include "{backward_impl}"
 #include "paddle/phi/common/data_type.h"
 #include "paddle/phi/core/dense_tensor.h"
 #include "paddle/phi/backends/gpu/gpu_context.h"
@@ -528,11 +528,7 @@ def write_main_header(forward_impl, backward_impl):
 #include "./cutlass_backward.h"
 
 #endif
-'''.format(
-        ENABLE_MACRO,
-        forward_impl,
-        backward_impl,
-    )
+'''
 
     path = Path(args.dst_path) / "autogen"
     os.makedirs(path, exist_ok=True)

python/paddle/amp/accuracy_compare.py

@@ -705,35 +705,23 @@ def compare_accuracy(
     )
 
     for filename in sorted(workerlog_filenames):
-        print(
-            "-- [Step 1/4] Parsing FP32 logs under {}/{}".format(
-                dump_path, filename
-            )
-        )
+        print(f"-- [Step 1/4] Parsing FP32 logs under {dump_path}/{filename}")
         fp32_tensor_info_list, fp32_has_tensor_name = parse_log(
             dump_path, filename, None
         )
         print(
-            "-- [Step 2/4] Parsing FP16 logs under {}/{}".format(
-                another_dump_path, filename
-            )
+            f"-- [Step 2/4] Parsing FP16 logs under {another_dump_path}/{filename}"
         )
         fp16_tensor_info_list, fp16_has_tensor_name = parse_log(
             another_dump_path, filename, None
         )
 
-        print(
-            "-- [Step 3/4] Merge FP32 and FP16 tensor info for {}".format(
-                filename
-            )
-        )
+        print(f"-- [Step 3/4] Merge FP32 and FP16 tensor info for {filename}")
         mp_tensor_info_list = merge_tensor_info_list(
             fp32_tensor_info_list, fp16_tensor_info_list, grad_scale
         )
         print(
-            "-- [Step 4/4] Add worksheet for mixed precision tensor info of {}".format(
-                filename
-            )
+            f"-- [Step 4/4] Add worksheet for mixed precision tensor info of {filename}"
         )
         excel_writer.add_worksheet(
             mp_tensor_info_list,

python/paddle/audio/backends/init_backend.py

@@ -83,9 +83,9 @@ def list_available_backends() -> List[str]:
         version = paddleaudio.__version__
         if not _check_version(version):
             err_msg = (
-                "the version of paddleaudio installed is {},\n"
+                f"the version of paddleaudio installed is {version},\n"
                 "please ensure the paddleaudio >= 1.0.2."
-            ).format(version)
+            )
             raise ImportError(err_msg)
         backends = paddleaudio.backends.list_audio_backends()
     backends.append("wave_backend")

python/paddle/audio/backends/wave_backend.py

@@ -28,9 +28,9 @@ def _error_message():
     warn_msg = (
         "only PCM16 WAV supportted. \n"
         "if want support more other audio types, please "
-        "manually installed (usually with `pip install {}`). \n "
+        f"manually installed (usually with `pip install {package}`). \n "
         "and use paddle.audio.backends.set_backend('soundfile') to set audio backend"
-    ).format(package)
+    )
     return warn_msg
 
 

python/paddle/batch.py

@@ -67,7 +67,7 @@ def batch_reader():
     if batch_size <= 0:
         raise ValueError(
             "batch_size should be a positive integer value, "
-            "but got batch_size={}".format(batch_size)
+            f"but got batch_size={batch_size}"
         )
 
     return batch_reader

python/paddle/dataset/common.py

@@ -91,9 +91,7 @@ def download(url, module_name, md5sum, save_name=None):
             retry += 1
         else:
             raise RuntimeError(
-                "Cannot download {} within retry limit {}".format(
-                    url, retry_limit
-                )
+                f"Cannot download {url} within retry limit {retry_limit}"
             )
         sys.stderr.write(
             f"Cache file {filename} not found, downloading {url} \n"

python/paddle/device/cuda/__init__.py

@@ -476,9 +476,9 @@ def get_device_properties(device=None):
                 )
         else:
             raise ValueError(
-                "The device type {} is not expected. Because paddle.device.cuda."
+                f"The device type {device} is not expected. Because paddle.device.cuda."
                 "get_device_properties only support int, str or paddle.CUDAPlace. "
-                "Please input appropriate device again!".format(device)
+                "Please input appropriate device again!"
             )
     else:
         device_id = -1

python/paddle/distributed/auto_parallel/interface.py

@@ -70,9 +70,7 @@ def shard_tensor(x, process_mesh=None, shard_spec=None):
     if process_mesh is not None:
         assert isinstance(
             process_mesh, core.ProcessMesh
-        ), "Argument process_mesh {} is not an instance of ProcessMesh".format(
-            process_mesh
-        )
+        ), f"Argument process_mesh {process_mesh} is not an instance of ProcessMesh"
     else:
         process_mesh = get_current_process_mesh()
         assert (
@@ -163,9 +161,7 @@ def shard_op(op, process_mesh=None, in_shard_specs=None, out_shard_specs=None):
     if process_mesh is not None:
         assert isinstance(
             process_mesh, ProcessMesh
-        ), "Argument process_mesh {} is not an instance of ProcessMesh".format(
-            process_mesh
-        )
+        ), f"Argument process_mesh {process_mesh} is not an instance of ProcessMesh"
     else:
         process_mesh = get_current_process_mesh()
         assert (
@@ -176,9 +172,7 @@ def shard_op(op, process_mesh=None, in_shard_specs=None, out_shard_specs=None):
         assert all(
             (isinstance(shard_spec, list) or shard_spec is None)
             for shard_spec in in_shard_specs
-        ), "in_shard_spec {} is not a list of list or None".format(
-            in_shard_specs
-        )
+        ), f"in_shard_spec {in_shard_specs} is not a list of list or None"
         for shard_spec in in_shard_specs:
             if shard_spec is not None:
                 in_dims_mappings.append(
@@ -191,9 +185,7 @@ def shard_op(op, process_mesh=None, in_shard_specs=None, out_shard_specs=None):
         assert all(
             (isinstance(shard_spec, list) or shard_spec is None)
             for shard_spec in out_shard_specs
-        ), "out_shard_spec {} is not a list of list or None".format(
-            out_shard_specs
-        )
+        ), f"out_shard_spec {out_shard_specs} is not a list of list or None"
         for shard_spec in out_shard_specs:
             if shard_spec is not None:
                 out_dims_mappings.append(

python/paddle/distributed/auto_parallel/static/completion.py

@@ -1211,9 +1211,7 @@ def _get_op_by_id(ops, id):
                     output_name = grad_op.output_arg_names[0]
                     assert (
                         output_name in grad_var_to_var[appended_grad_times]
-                    ), "sum op's output '{}' has no corresponding var".format(
-                        output_name
-                    )
+                    ), f"sum op's output '{output_name}' has no corresponding var"
                     ref_fwd_var_name = grad_var_to_var[appended_grad_times][
                         output_name
                     ]
@@ -1513,9 +1511,7 @@ def _get_op_by_id(ops, id):
                     output_name = grad_op.output_arg_names[0]
                     assert (
                         output_name in grad_var_to_var
-                    ), "sum op's output '{}' has no corresponding var".format(
-                        output_name
-                    )
+                    ), f"sum op's output '{output_name}' has no corresponding var"
                     ref_fwd_var_name = grad_var_to_var[output_name]
                     ref_fwd_var = vars[ref_fwd_var_name]
                     ref_fwd_dist_attr = (

python/paddle/distributed/auto_parallel/static/converter.py

@@ -69,7 +69,7 @@ def _check_pre_strategy(self, pre_strategy):
         if not isinstance(pre_strategy, dict):
             raise TypeError(
                 "The type of 'pre_strategy' should be 'dict', "
-                "but got '{}'.".format(str(type(pre_strategy)))
+                f"but got '{str(type(pre_strategy))}'."
             )
         return pre_strategy
 
@@ -82,7 +82,7 @@ def _check_cur_strategy(self, cur_strategy):
         if not isinstance(cur_strategy, dict):
             raise TypeError(
                 "The type of 'cur_strategy' should be 'dict', "
-                "but got '{}'.".format(str(type(cur_strategy)))
+                f"but got '{str(type(cur_strategy))}'."
             )
         return cur_strategy
 
@@ -229,9 +229,7 @@ def convert_with_prefix_match(
                                 + str(err)
                             )
                         self._logger.info(
-                            "tensor [{}] is matched with tensor [{}]".format(
-                                cur_name, pre_name
-                            )
+                            f"tensor [{cur_name}] is matched with tensor [{pre_name}]"
                         )
                         tensor_match_with_pre.append(cur_name)
                         tensor_match_with_cur.append(pre_name)
@@ -309,9 +307,7 @@ def merge_with_dist_attr(tensor_list, dist_attr):
 
         if len(partition_tensor_list) != 1:
             raise ValueError(
-                "Fail to merge tensor with dist_attr '{}'.".format(
-                    str(dist_attr)
-                )
+                f"Fail to merge tensor with dist_attr '{str(dist_attr)}'."
             )
         complete_tensor = partition_tensor_list[0][0]
         return complete_tensor
@@ -336,9 +332,7 @@ def slice_with_dist_attr(tensor, dist_attr):
         )
         if sliced_tensor_index not in range(len(sliced_tensor_list)):
             raise ValueError(
-                "Fail to slice tensor with dist_attr '{}'.".format(
-                    str(dist_attr)
-                )
+                f"Fail to slice tensor with dist_attr '{str(dist_attr)}'."
             )
         sliced_tensor = sliced_tensor_list[sliced_tensor_index]
         return sliced_tensor

python/paddle/distributed/auto_parallel/static/cost/base_cost.py

@@ -846,9 +846,7 @@ def group_ranks(self):
                 process_group = get_process_group(ring_id)
                 if process_group is None:
                     raise ValueError(
-                        "There not exists process group whose ring_id is {}.".format(
-                            ring_id
-                        )
+                        f"There not exists process group whose ring_id is {ring_id}."
                     )
                 self._group_ranks = process_group.ranks
         return self._group_ranks
@@ -858,9 +856,7 @@ def _check_comm_op_type(cls):
         if cls.OP_TYPE != "COMM":
             if cls.OP_TYPE not in COMM_OP_TYPE:
                 raise TypeError(
-                    "Please Check op type in {}, but got {}.".format(
-                        COMM_OP_TYPE, cls.OP_TYPE
-                    )
+                    f"Please Check op type in {COMM_OP_TYPE}, but got {cls.OP_TYPE}."
                 )
 
 
@@ -931,9 +927,7 @@ def calc_time_by_cost_model(op, cluster=None):
     """Calc op time by cost model and the unit is microsecond."""
     if not isinstance(op, paddle.base.framework.Operator):
         raise TypeError(
-            "OP must be paddle.base.framework.Operator, but got {}.".format(
-                type(op)
-            )
+            f"OP must be paddle.base.framework.Operator, but got {type(op)}."
         )
     if not cluster:
         cluster = get_default_cluster()

python/paddle/distributed/auto_parallel/static/cost/tensor_cost.py

@@ -54,9 +54,7 @@ def _check_args(self, tensor, dist_tensor, shape, dtype):
 
             if not isinstance(tensor, Variable):
                 raise TypeError(
-                    "Please check tensor type is Variable, but got {}".format(
-                        type(tensor)
-                    )
+                    f"Please check tensor type is Variable, but got {type(tensor)}"
                 )
 
         elif dist_tensor is not None:
@@ -72,9 +70,7 @@ def _check_args(self, tensor, dist_tensor, shape, dtype):
             assert tensor is None and dist_tensor is None and dtype is not None
             if not isinstance(shape, (list, set)):
                 raise TypeError(
-                    "Please check shape type is list or set, but got {}".format(
-                        type(shape)
-                    )
+                    f"Please check shape type is list or set, but got {type(shape)}"
                 )
 
         elif dtype is not None: