[CodeStyle][Ruff][BUAA][D-[1-6]] Fix ruff RUF015 diagnostic for 6 files in python/paddle/ (#67225)

Author: MufanColin

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

@@ -906,7 +906,7 @@ def _gen_one_impl(
             )
 
             kernel_name = (
-                list(dispatch_kernel.keys())[0]
+                next(iter(dispatch_kernel.keys()))
                 if dispatch_kernel and len(dispatch_kernel.keys()) == 1
                 else op_name
             )

python/paddle/base/dygraph/tensor_patch_methods.py

@@ -763,7 +763,7 @@ def get_device_dtype_from_tensor(other):
         if len(invalid_keys) != 0:
             raise TypeError(
                 "to() got an unexpected keyword argument "
-                + list(invalid_keys)[0]
+                + next(iter(invalid_keys))
             )
         if size_args > 0:
             if isinstance(args[0], paddle.Tensor):

python/paddle/base/dygraph/tracer.py

@@ -174,7 +174,7 @@ def eager_legacy_trace_op(
 
         if op_type == 'load_combine':
             assert len(outputs.keys()) == 1
-            key = list(outputs.keys())[0]
+            key = next(iter(outputs.keys()))
             for j in range(len(returns)):
                 returns[j]._share_underline_tensor_to(outputs[key][j])
             return
@@ -200,12 +200,12 @@ def eager_legacy_trace_op(
                             )
         elif isinstance(returns, list):
             assert len(outputs.keys()) == 1
-            key = list(outputs.keys())[0]
+            key = next(iter(outputs.keys()))
             for j in range(len(returns)):
                 outputs[key][j].reconstruct_from_(returns[j], False)
         else:
             assert len(outputs.keys()) == 1
-            key = list(outputs.keys())[0]
+            key = next(iter(outputs.keys()))
             if isinstance(outputs[key], list):
                 outputs[key][0].reconstruct_from_(returns, False)
             else:
@@ -285,12 +285,12 @@ def eager_trace_op(
                         outputs[retname][0].reconstruct_from_(returns[i], False)
         elif isinstance(returns, list):
             assert len(outputs.keys()) == 1
-            key = list(outputs.keys())[0]
+            key = next(iter(outputs.keys()))
             for j in range(len(returns)):
                 outputs[key][j].reconstruct_from_(returns[j], False)
         else:
             assert len(outputs.keys()) == 1
-            key = list(outputs.keys())[0]
+            key = next(iter(outputs.keys()))
             if isinstance(outputs[key], list):
                 outputs[key][0].reconstruct_from_(returns, False)
             else:

python/paddle/base/framework.py

@@ -3367,8 +3367,8 @@ def find_name(var_list, name):
                     if type in special_op_attrs:
                         attrs = special_op_attrs.get(type, [])
                         for attr in attrs:
-                            a_name = list(attr.keys())[0]
-                            default_value = list(attr.values())[0]
+                            a_name = next(iter(attr.keys()))
+                            default_value = next(iter(attr.values()))
                             if (
                                 a_name in op_attrs.keys()
                                 and default_value != op_attrs[a_name]

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

@@ -1511,7 +1511,7 @@ def find_op_desc_seq(
         if is_union_process_mesh_tensor:
             assert (
                 len(set(source_dims_mapping)) == 1
-                and list(set(source_dims_mapping))[0] == -1
+                and next(iter(set(source_dims_mapping))) == -1
             )
             if set(target_process_group).intersection(
                 set(source_process_group)

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

@@ -273,11 +273,11 @@ def _init_communication_group(self):
         # Create mp rings
         if self.num_mp > 1:
             mp_endpoints = [self.endpoints[mp_idx] for mp_idx in self.mp_group]
-            mp_rank = [
+            mp_rank = next(
                 idx
                 for idx, mp_idx in enumerate(self.mp_group)
                 if mp_idx == self.rank
-            ][0]
+            )
             collective_helper._init_communicator(
                 self._startup_program,
                 self.current_endpoint,