[Enhancement] upgrade isort in pre-commit config (#141)

* [Enhancement] upgrade isort in pre-commit config by refering to mmflow pr #87

* fix lint

* remove .isort.cfg and put its known_third_party to setup.cfg

Author: lvhan028

.isort.cfg

@@ -3,12 +3,8 @@ repos:
     rev: 4.0.1
     hooks:
       - id: flake8
-  - repo: https://github.com/asottile/seed-isort-config
-    rev: v2.2.0
-    hooks:
-      - id: seed-isort-config
-  - repo: https://github.com/timothycrosley/isort
-    rev: 4.3.21
+  - repo: https://github.com/PyCQA/isort
+    rev: 5.10.1
     hooks:
       - id: isort
   - repo: https://github.com/pre-commit/mirrors-yapf

.pre-commit-config.yaml

@@ -4,6 +4,6 @@
 __all__ = ['is_available', 'is_plugin_available']
 
 if is_available():
-    from mmdeploy.backend.ncnn.onnx2ncnn import (onnx2ncnn,
-                                                 get_output_model_file)
+    from mmdeploy.backend.ncnn.onnx2ncnn import (get_output_model_file,
+                                                 onnx2ncnn)
     __all__ += ['onnx2ncnn', 'get_output_model_file']

mmdeploy/apis/ncnn/__init__.py

@@ -4,8 +4,8 @@
 __all__ = ['is_available']
 
 if is_available():
-    from mmdeploy.backend.openvino.onnx2openvino \
-        import onnx2openvino, get_output_model_file
+    from mmdeploy.backend.openvino.onnx2openvino import (get_output_model_file,
+                                                         onnx2openvino)
     from .utils import get_input_info_from_cfg
     __all__ += [
         'onnx2openvino', 'get_output_model_file', 'get_input_info_from_cfg'

mmdeploy/apis/openvino/__init__.py

@@ -12,6 +12,6 @@ def is_available() -> bool:
 
 
 if is_available():
-    from .wrapper import OpenVINOWrapper
     from .onnx2openvino import get_output_model_file
+    from .wrapper import OpenVINOWrapper
     __all__ = ['OpenVINOWrapper', 'get_output_model_file']

mmdeploy/backend/openvino/__init__.py

@@ -230,6 +230,7 @@ def evaluate_outputs(model_cfg: mmcv.Config,
                 Defaults to `None` and the results will only print on stdout.
         """
         import warnings
+
         from mmcv.utils import get_logger
         logger = get_logger('test', log_file=log_file, log_level=logging.INFO)
 

mmdeploy/codebase/mmcls/deploy/classification.py

@@ -109,8 +109,8 @@ def create_input(self,
         Returns:
             tuple: (data, img), meta information for the input image and input.
         """
-        from mmdet.datasets.pipelines import Compose
         from mmcv.parallel import collate, scatter
+        from mmdet.datasets.pipelines import Compose
         if not isinstance(imgs, (list, tuple)):
             imgs = [imgs]
         dynamic_flag = is_dynamic_shape(self.deploy_cfg)

mmdeploy/codebase/mmdet/deploy/object_detection.py

@@ -399,6 +399,7 @@ def __init__(self, backend: Backend, backend_files: Sequence[str],
         super().__init__(backend, backend_files, device, class_names,
                          deploy_cfg, **kwargs)
         from mmdet.models.builder import build_head, build_roi_extractor
+
         from ..models.roi_heads.bbox_head import bbox_head__get_bboxes
 
         self.bbox_roi_extractor = build_roi_extractor(

mmdeploy/codebase/mmdet/deploy/object_detection_model.py

@@ -139,8 +139,8 @@ def yolox_head__get_bboxes__ncnn(ctx,
         output__ncnn (Tensor): outputs, shape is [N, num_det, 6].
     """
     from mmdeploy.codebase.mmdet.core.ops import ncnn_detection_output_forward
-    from mmdeploy.utils.config_utils import is_dynamic_shape
     from mmdeploy.utils import get_root_logger
+    from mmdeploy.utils.config_utils import is_dynamic_shape
     dynamic_flag = is_dynamic_shape(ctx.cfg)
     if dynamic_flag:
         logger = get_root_logger()

mmdeploy/codebase/mmdet/models/dense_heads/yolox_head.py

@@ -55,6 +55,7 @@ def build_dataset(dataset_cfg: Union[str, mmcv.Config], *args,
             Dataset: A PyTorch dataset.
         """
         from mmedit.datasets import build_dataset as build_dataset_mmedit
+
         from mmdeploy.utils import load_config
         dataset_cfg = load_config(dataset_cfg)[0]
         data = dataset_cfg.data