[Enhancement] Upgrade isort in pre-commit hook (#44)

* [Docs] update batch size

* [Enhancement] Upgrade isort in pre-commit hook

* update mmdet version

* update mmcls version

* update ci

.pre-commit-config.yaml

@@ -3,12 +3,8 @@ repos:
     rev: 3.8.3
     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

mmfewshot/__init__.py

@@ -32,7 +32,7 @@ assert (digit_version(mmcv_minimum_version) <= mmcv_version
     f'Please install mmcv>={mmcv_minimum_version}, <={mmcv_maximum_version}.'
 
 mmdet_minimum_version = '2.16.0'
-mmdet_maximum_version = '2.20.0'
+mmdet_maximum_version = '2.21.0'
 mmdet_version = digit_version(mmdet.__version__)
 
 
@@ -43,7 +43,7 @@ assert (digit_version(mmdet_minimum_version) <= mmdet_version
      <={mmdet_maximum_version}.'
 
 mmcls_minimum_version = '0.15.0'
-mmcls_maximum_version = '0.19.0'
+mmcls_maximum_version = '0.21.0'
 mmcls_version = digit_version(mmcls.__version__)
 
 

mmfewshot/detection/core/evaluation/eval_hooks.py

@@ -39,8 +39,9 @@ class QuerySupportEvalHook(BaseEvalHook):
         # identified the 'train', 'val' and 'model_init' stages instead
         # of `return_loss` in mmdet. Thus, `single_gpu_test` should be
         # imported from mmfewshot.
-        from mmfewshot.detection.apis import \
-            (single_gpu_model_init, single_gpu_test)
+        from mmfewshot.detection.apis import (single_gpu_model_init,
+                                              single_gpu_test)
+
         # `single_gpu_model_init` extracts features from
         # `model_init_dataloader` for model initialization with single gpu.
         single_gpu_model_init(runner.model, self.model_init_dataloader)
@@ -102,8 +103,9 @@ class QuerySupportDistEvalHook(BaseDistEvalHook):
         # identified the 'train', 'val' and 'model_init' stages instead
         # of `return_loss` in mmdet. Thus, `multi_gpu_test` should be
         # imported from mmfewshot.
-        from mmfewshot.detection.apis import \
-            (multi_gpu_model_init, multi_gpu_test)
+        from mmfewshot.detection.apis import (multi_gpu_model_init,
+                                              multi_gpu_test)
+
         # Noted that `model_init_dataloader` should NOT use distributed
         # sampler to make all the models on different gpus get same data
         # results in the same initialized models.

mmfewshot/detection/datasets/builder.py

@@ -189,6 +189,7 @@ def build_dataloader(dataset: Dataset,
         seed=seed) if seed is not None else None
     if isinstance(dataset, QueryAwareDataset):
         from mmfewshot.utils import multi_pipeline_collate_fn
+
         # `QueryAwareDataset` will return a list of DataContainer
         # `multi_pipeline_collate_fn` are designed to handle
         # the data with list[list[DataContainer]]
@@ -203,12 +204,12 @@ def build_dataloader(dataset: Dataset,
             worker_init_fn=init_fn,
             **kwargs)
     elif isinstance(dataset, NWayKShotDataset):
-        from .dataloader_wrappers import NWayKShotDataloader
         from mmfewshot.utils import multi_pipeline_collate_fn
+        from .dataloader_wrappers import NWayKShotDataloader
+
         # `NWayKShotDataset` will return a list of DataContainer
         # `multi_pipeline_collate_fn` are designed to handle
         # the data with list[list[DataContainer]]
-
         # initialize query dataloader
         query_data_loader = DataLoader(
             dataset,
@@ -260,12 +261,12 @@ def build_dataloader(dataset: Dataset,
             query_data_loader=query_data_loader,
             support_data_loader=support_data_loader)
     elif isinstance(dataset, TwoBranchDataset):
-        from .dataloader_wrappers import TwoBranchDataloader
         from mmfewshot.utils import multi_pipeline_collate_fn
+        from .dataloader_wrappers import TwoBranchDataloader
+
         # `TwoBranchDataset` will return a list of DataContainer
         # `multi_pipeline_collate_fn` are designed to handle
         # the data with list[list[DataContainer]]
-
         # initialize main dataloader
         main_data_loader = DataLoader(
             dataset,

setup.cfg

@@ -1,7 +1,7 @@
 [isort]
 line_length = 79
 multi_line_output = 0
-known_standard_library = setuptools
+extra_standard_library = setuptools
 known_first_party = mmfewshot
 known_third_party = cv2,mmcls,mmcv,mmdet,numpy,pytest,pytorch_sphinx_theme,terminaltables,torch,typing_extensions
 

setup.py

@@ -37,9 +37,9 @@ def parse_requirements(fname='requirements.txt', with_version=True):
     CommandLine:
         python -c "import setup; print(setup.parse_requirements())"
     """
+    import re
     import sys
     from os.path import exists
-    import re
     require_fpath = fname
 
     def parse_line(line):