[CodeStyle][Ruff][BUAA][K-[1-10]] Fix Ruff RUF019 diagnostic for 10 files in paddle/ and test/

paddle/fluid/operators/generator/generate_op.py

@@ -106,10 +106,7 @@ def process_scalar(op_item, scalar_configs):
 
                 scalar_config = scalar_configs[attr_item['name']]
                 attr_item['is_support_tensor'] = (
-                    True
-                    if 'support_tensor' in scalar_config
-                    and scalar_config['support_tensor']
-                    else False
+                    True if scalar_config.get('support_tensor') else False
                 )
                 attr_item['data_type'] = (
                     scalar_config['data_type']
@@ -144,10 +141,7 @@ def process_int_array(op_item, int_array_configs):
 
                 int_array_config = int_array_configs[attr_item['name']]
                 attr_item['is_support_tensor'] = (
-                    True
-                    if 'support_tensor' in int_array_config
-                    and int_array_config['support_tensor']
-                    else False
+                    True if int_array_config.get('support_tensor') else False
                 )
                 attr_item['data_type'] = (
                     data_type_map[int_array_config['data_type']]
@@ -235,7 +229,7 @@ def get_param_list_alias(param_list, args_map):
     def update_common_params_name(
         op_item, args_name_map, scalar_configs, int_array_configs
     ):
-        if 'inplace' in op_item and op_item['inplace']:
+        if op_item.get('inplace'):
             inplace_map = {}
             for key, val in op_item['inplace'].items():
                 if key in args_map:
@@ -244,11 +238,11 @@ def update_common_params_name(
                     val = args_map[val]
                 inplace_map[key] = val
             op_item['inplace'] = inplace_map
-        if 'no_need_buffer' in op_item and op_item['no_need_buffer']:
+        if op_item.get('no_need_buffer'):
             op_item['no_need_buffer'] = get_param_list_alias(
                 op_item['no_need_buffer'], args_map
             )
-        if 'data_transform' in op_item and op_item['data_transform']:
+        if op_item.get('data_transform'):
             data_trans_item = op_item['data_transform']
             if 'skip_transform' in data_trans_item:
                 data_trans_item['skip_transform'] = get_param_list_alias(

paddle/fluid/pir/dialect/op_generator/op_gen.py

@@ -1041,10 +1041,7 @@ def parse_invoke_map(self):
             return None
 
     def parse_data_transform_info(self):
-        if (
-            'data_transform' in self.op_yaml_item
-            and self.op_yaml_item['data_transform']
-        ):
+        if self.op_yaml_item.get('data_transform'):
             data_trans_item = self.op_yaml_item['data_transform']
             return data_trans_item
         return None
@@ -1775,10 +1772,7 @@ def AutoCodeGen(
                 if op_kernel_map is not None:
                     kernel_func_str = kernel_func_name
                     kernel_param_str = '", "'.join(op_kernel_map['param'])
-                    if (
-                        'data_type' in op_kernel_map
-                        and op_kernel_map['data_type']
-                    ):
+                    if op_kernel_map.get('data_type'):
                         for idx in range(
                             len(op_kernel_map['data_type']['candidates'])
                         ):
@@ -1804,7 +1798,7 @@ def AutoCodeGen(
                                 )
                         if kernel_key_dtype != "":
                             kernel_key_dtype = '"' + kernel_key_dtype[:-3]
-                    if 'backend' in op_kernel_map and op_kernel_map['backend']:
+                    if op_kernel_map.get('backend'):
                         kernel_key_backend = '", "'.join(
                             op_kernel_map['backend']['candidates']
                         )

python/paddle/base/executor.py

@@ -2885,10 +2885,7 @@ def _run_using_fleet_executor(
             self._add_scope_cache(cache_key, cached_scope)
         if micro_cached_scopes is None:
             micro_cached_scopes = []
-            if (
-                "inference_generation" in fleet_opt
-                and fleet_opt["inference_generation"]
-            ):
+            if fleet_opt.get("inference_generation"):
                 for _ in range(int(fleet_opt["num_micro_batches"])):
                     micro_cached_scopes.append(cached_scope.new_scope())
                 self._add_micro_scopes_cache(cache_key, micro_cached_scopes)
@@ -2957,10 +2954,7 @@ def _run_using_fleet_executor(
                 fetch_task.set_program(fetch_program)
 
             micro_scope_list = []
-            if (
-                "inference_generation" in fleet_opt
-                and fleet_opt["inference_generation"]
-            ):
+            if fleet_opt.get("inference_generation"):
                 for i in range(int(fleet_opt["num_micro_batches"])):
                     micro_scope_list.append(cached_scope.new_scope())
 

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

@@ -1308,10 +1308,10 @@ def set_var_dist_attr(dist_context, var, dims_mapping, process_mesh, **kwargs):
         raise ValueError(
             f"{process_mesh} must be a instance of ProcessMesh or list, but receive {type(process_mesh)}"
         )
-    if "mark_annotated" in kwargs and kwargs["mark_annotated"]:
+    if kwargs.get("mark_annotated"):
         tensor_dist_attr.mark_annotated("dims_mapping")
         tensor_dist_attr.mark_annotated("process_mesh")
-    if "chunk_id" in kwargs and kwargs["chunk_id"]:
+    if kwargs.get("chunk_id"):
         tensor_dist_attr.chunk_id = kwargs["chunk_id"]
     dist_context.set_tensor_dist_attr_for_program(var, tensor_dist_attr)
     return tensor_dist_attr
@@ -1331,7 +1331,7 @@ def naive_set_dist_op_attr_for_program_by_mesh_and_mapping(
         new_op_dist_attr.set_output_dims_mapping(output_varname, ref_mapping)
 
     new_op_dist_attr.process_mesh = process_mesh
-    if "chunk_id" in kwargs and kwargs["chunk_id"]:
+    if kwargs.get("chunk_id"):
         new_op_dist_attr.chunk_id = kwargs["chunk_id"]
     ctx.set_op_dist_attr_for_program(new_op, new_op_dist_attr)
 

python/paddle/distributed/fleet/base/runtime_factory.py

@@ -23,7 +23,7 @@ def __init__(self):
 
     def _create_runtime(self, context):
         # add collective && pslib mode
-        if "use_fleet_ps" in context and context["use_fleet_ps"]:
+        if context.get("use_fleet_ps"):
             ps_runtime = TheOnePSRuntime()
             ps_runtime._set_basic_info(context)
             return ps_runtime

python/paddle/distributed/launch/main.py

@@ -708,10 +708,7 @@ def launch() -> None:
                     logger.info(
                         "Get best config failed. Currently no config can be run."
                     )
-                if (
-                    "sharding_overlap" in cur_cfg
-                    and cur_cfg["sharding_overlap"]
-                ):
+                if cur_cfg.get("sharding_overlap"):
                     add_overlap_performance(
                         cur_cfg, tuner_cfg, recorder.history
                     )
@@ -811,10 +808,7 @@ def launch() -> None:
                         logger.info(
                             "Get best config failed. Currently no config can be run."
                         )
-                    if (
-                        "sharding_overlap" in cur_cfg
-                        and cur_cfg["sharding_overlap"]
-                    ):
+                    if cur_cfg.get("sharding_overlap"):
                         add_overlap_performance(
                             cur_cfg, tuner_cfg, recorder.history
                         )
@@ -1221,7 +1215,7 @@ def launch() -> None:
                 logger.info("Get best config failed, no config can be run.")
 
             # record history
-            if "sharding_overlap" in cur_cfg and cur_cfg["sharding_overlap"]:
+            if cur_cfg.get("sharding_overlap"):
                 add_overlap_performance(cur_cfg, tuner_cfg, recorder.history)
 
             recorder.store_history(history_file_path)

python/paddle/distributed/ps/utils/ps_factory.py

@@ -42,7 +42,7 @@ def _create_ps_program_builder(self, pass_ctx):
             return globals()['GpuPsProgramBuilder'](pass_ctx)
         elif attrs['is_heter_ps_mode'] and not attrs['is_fl_ps_mode']:
             return globals()['HeterAsyncPsProgramBuilder'](pass_ctx)
-        elif 'is_fl_ps_mode' in attrs and attrs['is_fl_ps_mode']:
+        elif attrs.get('is_fl_ps_mode'):
             return globals()['FlPsProgramBuilder'](pass_ctx)
         elif attrs['ps_mode'] == DistributedMode.SYNC:
             return globals()['CpuSyncPsProgramBuilder'](pass_ctx)

python/paddle/static/quantization/quanter.py

@@ -327,7 +327,7 @@ def quant_aware(
         sub_graphs = list(main_graph.all_sub_graphs())
         transform_pass_ops = []
         quant_dequant_ops = []
-        if 'quant_config' in config and config['quant_config']:
+        if config.get('quant_config'):
             transform_pass_ops = config[
                 'quant_config'
             ].weight_quant_operation_types

python/paddle/static/quantization/quantization_pass.py

@@ -3375,10 +3375,7 @@ def apply(self, graph):
             else:
                 var_names = utils._get_op_input_var_names(op_node)
                 for var_name in var_names:
-                    if (
-                        var_name in dequant_node_map
-                        and dequant_node_map[var_name]
-                    ):
+                    if dequant_node_map.get(var_name):
                         in_node = graph._find_node_by_name(
                             op_node.inputs, var_name
                         )

test/legacy_test/op_test.py

@@ -3394,7 +3394,7 @@ def check_grad_with_place(
 
         # oneDNN numeric gradient should use CPU kernel
         use_onednn = False
-        if "use_mkldnn" in op_attrs and op_attrs["use_mkldnn"]:
+        if op_attrs.get("use_mkldnn"):
             op_attrs["use_mkldnn"] = False
             use_onednn = True
         if hasattr(self, "attrs"):