Update pre-commit hook config and fix styles (#2182)

* update pre-commit hook config

* fix styles conflicting with pre-commit hooks

mmdet/models/detectors/test_mixins.py

@@ -17,9 +17,9 @@ class RPNTestMixin(object):
     if sys.version_info >= (3, 7):
 
         async def async_test_rpn(self, x, img_meta, rpn_test_cfg):
-            sleep_interval = rpn_test_cfg.pop("async_sleep_interval", 0.025)
+            sleep_interval = rpn_test_cfg.pop('async_sleep_interval', 0.025)
             async with completed(
-                    __name__, "rpn_head_forward",
+                    __name__, 'rpn_head_forward',
                     sleep_interval=sleep_interval):
                 rpn_outs = self.rpn_head(x)
 
@@ -75,10 +75,10 @@ class BBoxTestMixin(object):
                 x[:len(self.bbox_roi_extractor.featmap_strides)], rois)
             if self.with_shared_head:
                 roi_feats = self.shared_head(roi_feats)
-            sleep_interval = rcnn_test_cfg.get("async_sleep_interval", 0.017)
+            sleep_interval = rcnn_test_cfg.get('async_sleep_interval', 0.017)
 
             async with completed(
-                    __name__, "bbox_head_forward",
+                    __name__, 'bbox_head_forward',
                     sleep_interval=sleep_interval):
                 cls_score, bbox_pred = self.bbox_head(roi_feats)
 
@@ -191,7 +191,7 @@ class MaskTestMixin(object):
                     sleep_interval = 0.035
                 async with completed(
                         __name__,
-                        "mask_head_forward",
+                        'mask_head_forward',
                         sleep_interval=sleep_interval):
                     mask_pred = self.mask_head(mask_feats)
                 segm_result = self.mask_head.get_seg_masks(

mmdet/models/detectors/two_stage.py

@@ -266,7 +266,7 @@ class TwoStageDetector(BaseDetector, RPNTestMixin, BBoxTestMixin,
                                 proposals=None,
                                 rescale=False):
         """Async test without augmentation."""
-        assert self.with_bbox, "Bbox head must be implemented."
+        assert self.with_bbox, 'Bbox head must be implemented.'
         x = self.extract_feat(img)
 
         if proposals is None:
@@ -294,7 +294,7 @@ class TwoStageDetector(BaseDetector, RPNTestMixin, BBoxTestMixin,
 
     def simple_test(self, img, img_meta, proposals=None, rescale=False):
         """Test without augmentation."""
-        assert self.with_bbox, "Bbox head must be implemented."
+        assert self.with_bbox, 'Bbox head must be implemented.'
 
         x = self.extract_feat(img)
 

mmdet/ops/dcn/src/deform_conv_cuda.cpp

@@ -164,7 +164,7 @@ int deform_conv_forward_cuda(at::Tensor input, at::Tensor weight,
   shape_check(input, offset, NULL, weight, kH, kW, dH, dW, padH, padW,
               dilationH, dilationW, group, deformable_group);
   at::DeviceGuard guard(input.device());
-  
+
   input = input.contiguous();
   offset = offset.contiguous();
   weight = weight.contiguous();
@@ -386,7 +386,7 @@ int deform_conv_backward_parameters_cuda(
   shape_check(input, offset, &gradOutput, gradWeight, kH, kW, dH, dW, padH,
               padW, dilationH, dilationW, group, deformable_group);
   at::DeviceGuard guard(input.device());
-  
+
   input = input.contiguous();
   offset = offset.contiguous();
   gradOutput = gradOutput.contiguous();
@@ -497,7 +497,7 @@ void modulated_deform_conv_cuda_forward(
   AT_CHECK(input.is_contiguous(), "input tensor has to be contiguous");
   AT_CHECK(weight.is_contiguous(), "weight tensor has to be contiguous");
   at::DeviceGuard guard(input.device());
-  
+
   const int batch = input.size(0);
   const int channels = input.size(1);
   const int height = input.size(2);

mmdet/ops/masked_conv/src/masked_conv2d_cuda.cpp

@@ -73,4 +73,4 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
         "masked_im2col forward (CUDA)");
   m.def("masked_col2im_forward", &masked_col2im_forward_cuda,
         "masked_col2im forward (CUDA)");
-}
\ No newline at end of file
+}

mmdet/ops/nms/src/nms_cuda.cpp

@@ -14,4 +14,4 @@ at::Tensor nms(const at::Tensor& dets, const float threshold) {
 
 PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
   m.def("nms", &nms, "non-maximum suppression");
-}
\ No newline at end of file
+}

mmdet/utils/collect_env.py

@@ -58,6 +58,6 @@ def collect_env():
     return env_info
 
 
-if __name__ == "__main__":
+if __name__ == '__main__':
     for name, val in collect_env().items():
         print('{}: {}'.format(name, val))

mmdet/utils/contextmanagers.py

-# coding: utf-8
 import asyncio
 import contextlib
 import logging

mmdet/utils/profiling.py

@@ -35,7 +35,7 @@ if sys.version_info >= (3, 7):
             end.synchronize()
             cpu_time = (cpu_end - cpu_start) * 1000
             gpu_time = start.elapsed_time(end)
-            msg = "{} {} cpu_time {:.2f} ms ".format(trace_name, name,
+            msg = '{} {} cpu_time {:.2f} ms '.format(trace_name, name,
                                                      cpu_time)
-            msg += "gpu_time {:.2f} ms stream {}".format(gpu_time, stream)
+            msg += 'gpu_time {:.2f} ms stream {}'.format(gpu_time, stream)
             print(msg, end_stream)

mmdet/utils/util_mixins.py

-# -*- coding: utf-8 -*-
 """
 This module defines the :class:`NiceRepr` mixin class, which defines a
 ``__repr__`` and ``__str__`` method that only depend on a custom ``__nice__``

requirements.txt

--r requirements/runtime.txt
+-r requirements/build.txt
 -r requirements/optional.txt
+-r requirements/runtime.txt
 -r requirements/tests.txt
--r requirements/build.txt

setup.py

 #!/usr/bin/env python
-# -*- coding: utf-8 -*-
 import os
 import subprocess
 import time
@@ -93,7 +92,7 @@ def make_cuda_ext(name, module, sources):
     define_macros = []
 
     if torch.cuda.is_available() or os.getenv('FORCE_CUDA', '0') == '1':
-        define_macros += [("WITH_CUDA", None)]
+        define_macros += [('WITH_CUDA', None)]
     else:
         raise EnvironmentError('CUDA is required to compile MMDetection!')
 

tests/async_benchmark.py

-# coding: utf-8
-
 import asyncio
 import os
 import shutil

tests/test_async.py

@@ -18,7 +18,7 @@ class AsyncTestCase(asynctest.TestCase):
     use_default_loop = False
     forbid_get_event_loop = True
 
-    TEST_TIMEOUT = int(os.getenv("ASYNCIO_TEST_TIMEOUT", "30"))
+    TEST_TIMEOUT = int(os.getenv('ASYNCIO_TEST_TIMEOUT', '30'))
 
     def _run_test_method(self, method):
         result = method()
@@ -33,7 +33,7 @@ class MaskRCNNDetector:
                  model_config,
                  checkpoint=None,
                  streamqueue_size=3,
-                 device="cuda:0"):
+                 device='cuda:0'):
 
         self.streamqueue_size = streamqueue_size
         self.device = device
@@ -66,13 +66,13 @@ class AsyncInferenceTestCase(AsyncTestCase):
             if not torch.cuda.is_available():
                 import pytest
 
-                pytest.skip("test requires GPU and torch+cuda")
+                pytest.skip('test requires GPU and torch+cuda')
 
             root_dir = os.path.dirname(os.path.dirname(__name__))
             model_config = os.path.join(root_dir,
-                                        "configs/mask_rcnn_r50_fpn_1x.py")
+                                        'configs/mask_rcnn_r50_fpn_1x.py')
             detector = MaskRCNNDetector(model_config)
             await detector.init()
-            img_path = os.path.join(root_dir, "demo/demo.jpg")
+            img_path = os.path.join(root_dir, 'demo/demo.jpg')
             bboxes, _ = await detector.apredict(img_path)
             self.assertTrue(bboxes)

tools/robustness_eval.py

@@ -196,7 +196,7 @@ def get_distortions_from_file(filename):
 def get_distortions_from_results(eval_output):
     distortions = []
     for i, distortion in enumerate(eval_output):
-        distortions.append(distortion.replace("_", " "))
+        distortions.append(distortion.replace('_', ' '))
     return distortions