[CodeStyle][UP031] fix /{python, test, tools}/* - part 19 (PaddlePa…

…ddle#65585)

paddle/fluid/operators/generator/templates/operator_utils.c.j2

@@ -423,7 +423,7 @@ class {{op["op_name"] | to_pascal_case}}Op : public framework::OperatorWithKerne
   {% set kernel = op["kernel"] %}
   {% if kernel["data_type"] is not none or kernel["backend"] is not none
       or kernel["force_backend"] is not none
-      or "complex_promote" in op or "data_transform" in op 
+      or "complex_promote" in op or "data_transform" in op
       or "get_expected_kernel_type" in op%}
  protected:
     {% if kernel["data_type"] is not none or kernel["backend"] is not none
@@ -629,7 +629,7 @@ class {{name | to_pascal_case}}OpMaker : public framework::SingleGradOpMaker<T>
       grad_op->SetInput("{{attr | to_int_array_tensors_name}}", this->Input("{{attr | to_int_array_tensors_name}}"));
     }
         {% endif %}
-      {% elif attr["typename"] is scalar and 
+      {% elif attr["typename"] is scalar and
       ("is_support_tensor" not in attr or attr["is_support_tensor"] is false)%}
     if (this->HasInput("{{attr | to_scalar_tensor_name}}")) {
       grad_op->SetInput("{{attr | to_scalar_tensor_name}}", this->Input("{{attr | to_scalar_tensor_name}}"));
@@ -848,7 +848,7 @@ class {{op_name | to_composite_grad_opmaker_name}} : public prim::CompositeGradO
     auto {{outputs[i] + "_t"}} = this->GetSingleInputGrad({{name_in_forward_orig | to_opmaker_name}});
     {% elif output_typename == "Tensor[]" %}
     auto {{outputs[i] + "_t"}} = this->GetMultiInputGrad({{name_in_forward_orig | to_opmaker_name}});
-    {%- endif %}    
+    {%- endif %}
   {%- endfor %}
 {%- endmacro %}
 
@@ -864,7 +864,7 @@ class {{op_name | to_composite_grad_opmaker_name}} : public prim::CompositeGradO
       {{outputs[i]}}[i] = &{{outputs[i] + "_t"}}[i];
     }
     {{outputs[i]}} = this->GetOutputPtr({{outputs[i]}});
-    {%- endif %}    
+    {%- endif %}
   {%- endfor %}
 {%- endmacro %}
 
@@ -876,7 +876,7 @@ class {{op_name | to_composite_grad_opmaker_name}} : public prim::CompositeGradO
     auto {{outputs[i] + "_name"}} = this->GetOutputName({{outputs[i] + "_t"}});
     {% elif output_typename == "Tensor[]" %}
     auto {{outputs[i] + "_name"}} = this->GetOutputName({{outputs[i] + "_t"}});
-    {%- endif %}    
+    {%- endif %}
   {%- endfor %}
 {%- endmacro %}
 

paddle/phi/api/generator/tensor_operants_gen.py

@@ -489,9 +489,9 @@ def gene_operants_base(self):
     def get_declare_args_without_first_tensor(self, inplace_flag=False):
         func_name = self.get_api_func_name()
         declare_args = self.get_input_tensor_args(inplace_flag)
-        assert len(declare_args) >= 1, (
-            "Error! Api %s has no Tensor inputs" % func_name
-        )
+        assert (
+            len(declare_args) >= 1
+        ), f"Error! Api {func_name} has no Tensor inputs"
         first_input_type = " ".join(declare_args[0].split(" ")[:-1])
         # NOTE(HongyuJia): Do not consider "const paddle::optional<Tensor>&"
         assert (
@@ -510,9 +510,9 @@ def get_declare_args_without_first_tensor(self, inplace_flag=False):
     def get_define_args_without_first_tensor(self, inplace_flag=False):
         func_name = self.get_api_func_name()
         define_args = self.get_input_tensor_args(inplace_flag)
-        assert len(define_args) >= 1, (
-            "Error! Api %s has no Tensor inputs" % func_name
-        )
+        assert (
+            len(define_args) >= 1
+        ), f"Error! Api {func_name} has no Tensor inputs"
         first_input_type = " ".join(define_args[0].split(" ")[:-1])
         # NOTE(HongyuJia): Do not consider "const paddle::optional<Tensor>&"
         assert (
@@ -525,9 +525,9 @@ def get_define_args_without_first_tensor(self, inplace_flag=False):
 
     def gene_tensor_api_implementation(self):
         func_name = self.get_api_func_name()
-        assert len(self.inputs['names']) >= 1, (
-            "Error! Api %s has no Tensor inputs" % func_name
-        )
+        assert (
+            len(self.inputs['names']) >= 1
+        ), f"Error! Api {func_name} has no Tensor inputs"
         # remove first Tensor argument
         func_args = self.inputs['names'][1:] + self.attrs['names']
         if len(func_args) > 0:

python/paddle/autograd/backward_utils.py

@@ -450,7 +450,7 @@ def remove_op(block, op, state):
 
             if value in state.sumvaluegrad_to_value:
                 raise ValueError(
-                    'input_grad in [%s] is value which need to sum ', op.name()
+                    f'input_grad in [%s] is value which need to sum {op.name()}'
                 )
     # NOTE(SigureMo): Ensure access to the op's results before removing it.
     # Otherwise, the op will be deconstructed and access the num_results

python/paddle/autograd/ir_backward.py

@@ -1216,7 +1216,7 @@ def append_backward(loss, parameter_list=None, no_grad_set=None):
         for i, param in enumerate(parameter_list):
             check_type(
                 param,
-                'parameter_list[%s]' % i,
+                f'parameter_list[{i}]',
                 paddle.pir.Value,
                 'base.backward.append_backward',
             )

python/paddle/base/backward.py

@@ -160,8 +160,7 @@ def sort_checkpoints(self, checkpoints_name):
         for name in checkpoints_name:
             if name not in self.var_op_deps:
                 _logger.info(
-                    "Recompute Optimizer: deleted %s from checkpoints, because it is not used in paddle program."
-                    % name
+                    f"Recompute Optimizer: deleted {name} from checkpoints, because it is not used in paddle program."
                 )
             elif self.var_op_deps[name]["var_as_output_ops"] == []:
                 # input nodes
@@ -1079,8 +1078,9 @@ def _append_backward_ops_with_checkpoints_(
             if op.has_attr("sub_block"):
                 raise Exception(
                     "Recompute don't support ops with sub_block"
-                    "invoke op: %s"
-                    % _pretty_op_desc_(op.desc, "with_sub_block")
+                    "invoke op: {}".format(
+                        _pretty_op_desc_(op.desc, "with_sub_block")
+                    )
                 )
             grad_op_desc, op_grad_to_var = core.get_grad_op_desc(
                 op.desc, no_grad_dict[block.idx], []
@@ -1109,8 +1109,9 @@ def _append_backward_ops_with_checkpoints_(
             if op.has_attr("sub_block"):
                 raise Exception(
                     "Recompute don't support ops with sub_block"
-                    "invoke op: %s"
-                    % _pretty_op_desc_(op.desc, "with_sub_block")
+                    "invoke op: {}".format(
+                        _pretty_op_desc_(op.desc, "with_sub_block")
+                    )
                 )
             grad_op_desc, op_grad_to_var = core.get_grad_op_desc(
                 op.desc, no_grad_dict[block.idx], []
@@ -1139,8 +1140,9 @@ def _append_backward_ops_with_checkpoints_(
             if op.has_attr("sub_block"):
                 raise Exception(
                     "Recompute don't support ops with sub_block"
-                    "invoke op: %s"
-                    % _pretty_op_desc_(op.desc, "with_sub_block")
+                    "invoke op: {}".format(
+                        _pretty_op_desc_(op.desc, "with_sub_block")
+                    )
                 )
             input_and_output_names = []
             input_and_output_names.extend(op.desc.input_arg_names())
@@ -1922,8 +1924,7 @@ def _get_no_grad_set_name(no_grad_set):
                     no_grad_set_name.add(no_grad_var)
                 else:
                     raise TypeError(
-                        "The type of no_grad_set's member must be paddle.base.Variable or str, but received %s."
-                        % (type(no_grad_var))
+                        f"The type of no_grad_set's member must be paddle.base.Variable or str, but received {type(no_grad_var)}."
                     )
         else:
             raise TypeError(
@@ -1941,8 +1942,7 @@ def _get_no_grad_set_value(no_grad_set):
                     no_grad_set_value.add(no_grad_value)
                 else:
                     raise TypeError(
-                        "The type of no_grad_set's member must be paddle.pir.Value, but received %s."
-                        % (type(no_grad_value))
+                        f"The type of no_grad_set's member must be paddle.pir.Value, but received {type(no_grad_value)}."
                     )
         else:
             raise TypeError(
@@ -2250,7 +2250,7 @@ def append_backward(
         for i, param in enumerate(parameter_list):
             check_type(
                 param,
-                'parameter_list[%s]' % i,
+                f'parameter_list[{i}]',
                 (framework.Variable, str),
                 'base.backward.append_backward',
             )

python/paddle/base/compiler.py

@@ -143,8 +143,7 @@ def __init__(self, program_or_graph, build_strategy=None):
             self._program = program_or_graph
         else:
             raise TypeError(
-                "The type of program_to_graph parameter is wrong, expected Graph or Program, but received %s"
-                % type(program_or_graph)
+                f"The type of program_to_graph parameter is wrong, expected Graph or Program, but received {type(program_or_graph)}"
             )
 
         self._scope = None
@@ -481,8 +480,7 @@ def patch_program_cache(ipu_strategy):
         def patch_getter(self, item):
             if not isinstance(item, CacheKey):
                 raise ValueError(
-                    'type(item) should be CacheKey, but received %s'
-                    % type(item).__name__
+                    f'type(item) should be CacheKey, but received {type(item).__name__}'
                 )
             item_id = hash(item)
             self._recent_key = item_id
@@ -1061,8 +1059,7 @@ def __init__(self, program=None, scope=None, ipu_strategy=None):
 
         if not isinstance(program, framework.Program):
             raise TypeError(
-                "The type of program is wrong, expected Program, but got %s"
-                % type(program)
+                f"The type of program is wrong, expected Program, but got {type(program)}"
             )
 
         self._program = program