[CodeStyle][ruff] clean some I001 step: 15 (#63794)

pyproject.toml

@@ -130,7 +130,3 @@ known-first-party = ["paddle"]
 "test/dygraph_to_static/test_loop.py" = ["C416", "F821"]
 # Ignore unnecessary lambda in dy2st unittest test_lambda
 "test/dygraph_to_static/test_lambda.py" = ["PLC3002"]
-
-
-# temp ignore isort
-"python/paddle/distributed/__init__.py" = ["I001"]

python/paddle/distributed/__init__.py

@@ -13,107 +13,99 @@
 # limitations under the License.
 
 import atexit  # noqa: F401
-from . import io
-from .spawn import spawn
-from .launch.main import launch
-from .parallel import (  # noqa: F401
-    init_parallel_env,
-    get_rank,
-    get_world_size,
-    ParallelEnv,
-    DataParallel,
-)
-from .parallel_with_gloo import (
-    gloo_init_parallel_env,
-    gloo_barrier,
-    gloo_release,
-)
 
-from paddle.distributed.fleet.dataset import InMemoryDataset, QueueDataset
+from paddle.base.core import Placement, ReduceType
 from paddle.distributed.fleet.base.topology import ParallelMode
+from paddle.distributed.fleet.dataset import InMemoryDataset, QueueDataset
 
+from . import (
+    cloud_utils,  # noqa: F401
+    io,
+    rpc,  # noqa: F401
+)
+from .auto_parallel import shard_op  # noqa: F401
+from .auto_parallel.api import (
+    DistAttr,
+    DistModel,
+    ShardingStage1,
+    ShardingStage2,
+    ShardingStage3,
+    Strategy,
+    dtensor_from_fn,
+    reshard,
+    shard_dataloader,
+    shard_layer,
+    shard_optimizer,
+    shard_scaler,
+    shard_tensor,
+    to_static,
+    unshard_dtensor,
+)
+from .auto_parallel.placement_type import (
+    Partial,
+    Replicate,
+    Shard,
+)
+from .auto_parallel.process_mesh import ProcessMesh
+from .checkpoint.load_state_dict import load_state_dict
+from .checkpoint.save_state_dict import save_state_dict
 from .collective import (
-    split,
-    new_group,
     is_available,
+    new_group,
+    split,
 )
 from .communication import (  # noqa: F401
-    stream,
+    P2POp,
     ReduceOp,
     all_gather,
     all_gather_object,
     all_reduce,
     alltoall,
     alltoall_single,
+    barrier,
+    batch_isend_irecv,
     broadcast,
     broadcast_object_list,
-    reduce,
-    send,
-    scatter,
+    destroy_process_group,
     gather,
-    scatter_object_list,
+    get_backend,
+    get_group,
+    irecv,
+    is_initialized,
     isend,
     recv,
-    irecv,
-    batch_isend_irecv,
-    P2POp,
+    reduce,
     reduce_scatter,
-    is_initialized,
-    destroy_process_group,
-    get_group,
+    scatter,
+    scatter_object_list,
+    send,
+    stream,
     wait,
-    barrier,
-    get_backend,
-)
-
-from .auto_parallel.process_mesh import ProcessMesh
-
-from paddle.base.core import ReduceType, Placement
-from .auto_parallel.placement_type import (
-    Shard,
-    Replicate,
-    Partial,
 )
-
-from .auto_parallel import shard_op  # noqa: F401
-
-from .auto_parallel.api import (
-    DistAttr,
-    shard_tensor,
-    dtensor_from_fn,
-    reshard,
-    shard_dataloader,
-    shard_layer,
-    shard_optimizer,
-    shard_scaler,
-    ShardingStage1,
-    ShardingStage2,
-    ShardingStage3,
-    to_static,
-    Strategy,
-    DistModel,
-    unshard_dtensor,
-)
-
-from .fleet import BoxPSDataset  # noqa: F401
-
 from .entry_attr import (
-    ProbabilityEntry,
     CountFilterEntry,
+    ProbabilityEntry,
     ShowClickEntry,
 )
-
-from . import cloud_utils  # noqa: F401
-
+from .fleet import BoxPSDataset  # noqa: F401
+from .launch.main import launch
+from .parallel import (  # noqa: F401
+    DataParallel,
+    ParallelEnv,
+    get_rank,
+    get_world_size,
+    init_parallel_env,
+)
+from .parallel_with_gloo import (
+    gloo_barrier,
+    gloo_init_parallel_env,
+    gloo_release,
+)
 from .sharding import (  # noqa: F401
     group_sharded_parallel,
     save_group_sharded_model,
 )
-
-from . import rpc  # noqa: F401
-
-from .checkpoint.save_state_dict import save_state_dict
-from .checkpoint.load_state_dict import load_state_dict
+from .spawn import spawn
 
 __all__ = [
     "io",

python/paddle/distributed/auto_parallel/api.py

@@ -37,6 +37,7 @@
 from paddle.distributed.auto_parallel.placement_type import (
     to_placements,
 )
+from paddle.distributed.auto_parallel.process_mesh import ProcessMesh
 from paddle.distributed.auto_parallel.static.completion import (
     mark_as_sharding_propagation_skip_op,
 )
@@ -443,7 +444,7 @@ def reshard(dist_tensor, mesh, placements):
 
 def shard_layer(
     layer: nn.Layer,
-    process_mesh: dist.ProcessMesh,
+    process_mesh: ProcessMesh,
     shard_fn: Callable = None,
     input_fn: Callable = None,
     output_fn: Callable = None,
@@ -523,13 +524,13 @@ def output_fn(outputs, process_mesh) -> list(paddle.Tensor)
         raise ValueError("The argument `process_mesh` cannot be empty.")
 
     # Check the legality of process_mesh
-    if not isinstance(process_mesh, dist.ProcessMesh):
+    if not isinstance(process_mesh, ProcessMesh):
         raise ValueError(
             "The argument `process_mesh` is not `dist.ProcessMesh` type."
         )
 
     def replicate_layer_params_and_buffers(
-        layer: nn.Layer, mesh: dist.ProcessMesh
+        layer: nn.Layer, mesh: ProcessMesh
     ) -> None:
         for key, param in layer._parameters.items():
             if param is not None and not param.is_dist():
@@ -2046,7 +2047,7 @@ def build_distributed_tensor(local_tensor, dist_attr):
                     )
                 else:
                     raise ValueError(f"dim {dim} is not supported.")
-            mesh = dist.ProcessMesh(
+            mesh = ProcessMesh(
                 np.array(dist_attr["process_group"]).reshape(
                     dist_attr["process_shape"]
                 )
@@ -2346,9 +2347,7 @@ class ShardDataloader:
     def __init__(
         self,
         dataloader: paddle.io.DataLoader,
-        meshes: Union[
-            dist.ProcessMesh, List[dist.ProcessMesh], Tuple[dist.ProcessMesh]
-        ],
+        meshes: Union[ProcessMesh, List[ProcessMesh], Tuple[ProcessMesh]],
         input_keys: Union[List[str], Tuple[str]] = None,
         shard_dims: Union[list, tuple, str, int] = None,
         is_dataset_splitted: bool = False,
@@ -2597,9 +2596,7 @@ def __call__(self):
 
 def shard_dataloader(
     dataloader: paddle.io.DataLoader,
-    meshes: Union[
-        dist.ProcessMesh, List[dist.ProcessMesh], Tuple[dist.ProcessMesh]
-    ],
+    meshes: Union[ProcessMesh, List[ProcessMesh], Tuple[ProcessMesh]],
     input_keys: Union[List[str], Tuple[str]] = None,
     shard_dims: Union[list, tuple, str, int] = None,
     is_dataset_splitted: bool = False,