Use isort to sort imports and setup travis (#1085)

* add isort config

* use isort to sort imports

* add isort to travis

mmdet/models/anchor_heads/ga_retina_head.py

 import torch.nn as nn
 from mmcv.cnn import normal_init
 
-from .guided_anchor_head import GuidedAnchorHead, FeatureAdaption
-from ..registry import HEADS
-from ..utils import bias_init_with_prob, ConvModule
 from mmdet.ops import MaskedConv2d
+from ..registry import HEADS
+from ..utils import ConvModule, bias_init_with_prob
+from .guided_anchor_head import FeatureAdaption, GuidedAnchorHead
 
 
 @HEADS.register_module

mmdet/models/anchor_heads/ga_rpn_head.py

@@ -5,8 +5,8 @@ from mmcv.cnn import normal_init
 
 from mmdet.core import delta2bbox
 from mmdet.ops import nms
-from .guided_anchor_head import GuidedAnchorHead
 from ..registry import HEADS
+from .guided_anchor_head import GuidedAnchorHead
 
 
 @HEADS.register_module

mmdet/models/anchor_heads/guided_anchor_head.py

@@ -5,14 +5,14 @@ import torch
 import torch.nn as nn
 from mmcv.cnn import normal_init
 
-from mmdet.core import (AnchorGenerator, anchor_target, anchor_inside_flags,
-                        ga_loc_target, ga_shape_target, delta2bbox,
-                        multi_apply, multiclass_nms, force_fp32)
+from mmdet.core import (AnchorGenerator, anchor_inside_flags, anchor_target,
+                        delta2bbox, force_fp32, ga_loc_target, ga_shape_target,
+                        multi_apply, multiclass_nms)
 from mmdet.ops import DeformConv, MaskedConv2d
 from ..builder import build_loss
-from .anchor_head import AnchorHead
 from ..registry import HEADS
 from ..utils import bias_init_with_prob
+from .anchor_head import AnchorHead
 
 
 class FeatureAdaption(nn.Module):

mmdet/models/anchor_heads/retina_head.py

@@ -2,9 +2,9 @@ import numpy as np
 import torch.nn as nn
 from mmcv.cnn import normal_init
 
-from .anchor_head import AnchorHead
 from ..registry import HEADS
-from ..utils import bias_init_with_prob, ConvModule
+from ..utils import ConvModule, bias_init_with_prob
+from .anchor_head import AnchorHead
 
 
 @HEADS.register_module

mmdet/models/anchor_heads/rpn_head.py

@@ -5,8 +5,8 @@ from mmcv.cnn import normal_init
 
 from mmdet.core import delta2bbox
 from mmdet.ops import nms
-from .anchor_head import AnchorHead
 from ..registry import HEADS
+from .anchor_head import AnchorHead
 
 
 @HEADS.register_module

mmdet/models/anchor_heads/ssd_head.py

@@ -5,9 +5,9 @@ import torch.nn.functional as F
 from mmcv.cnn import xavier_init
 
 from mmdet.core import AnchorGenerator, anchor_target, multi_apply
-from .anchor_head import AnchorHead
 from ..losses import smooth_l1_loss
 from ..registry import HEADS
+from .anchor_head import AnchorHead
 
 
 # TODO: add loss evaluator for SSD

mmdet/models/backbones/hrnet.py

@@ -6,7 +6,7 @@ from mmcv.runner import load_checkpoint
 from torch.nn.modules.batchnorm import _BatchNorm
 
 from ..registry import BACKBONES
-from ..utils import build_norm_layer, build_conv_layer
+from ..utils import build_conv_layer, build_norm_layer
 from .resnet import BasicBlock, Bottleneck
 
 

mmdet/models/backbones/resnet.py

@@ -2,14 +2,12 @@ import logging
 
 import torch.nn as nn
 import torch.utils.checkpoint as cp
-from torch.nn.modules.batchnorm import _BatchNorm
-
 from mmcv.cnn import constant_init, kaiming_init
 from mmcv.runner import load_checkpoint
+from torch.nn.modules.batchnorm import _BatchNorm
 
-from mmdet.ops import DeformConv, ModulatedDeformConv, ContextBlock
 from mmdet.models.plugins import GeneralizedAttention
-
+from mmdet.ops import ContextBlock, DeformConv, ModulatedDeformConv
 from ..registry import BACKBONES
 from ..utils import build_conv_layer, build_norm_layer
 

mmdet/models/backbones/resnext.py

@@ -3,10 +3,10 @@ import math
 import torch.nn as nn
 
 from mmdet.ops import DeformConv, ModulatedDeformConv
-from .resnet import Bottleneck as _Bottleneck
-from .resnet import ResNet
 from ..registry import BACKBONES
 from ..utils import build_conv_layer, build_norm_layer
+from .resnet import Bottleneck as _Bottleneck
+from .resnet import ResNet
 
 
 class Bottleneck(_Bottleneck):

mmdet/models/backbones/ssd_vgg.py

@@ -3,8 +3,7 @@ import logging
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
-from mmcv.cnn import (VGG, xavier_init, constant_init, kaiming_init,
-                      normal_init)
+from mmcv.cnn import VGG, constant_init, kaiming_init, normal_init, xavier_init
 from mmcv.runner import load_checkpoint
 
 from ..registry import BACKBONES

mmdet/models/bbox_heads/bbox_head.py

@@ -2,8 +2,8 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 
-from mmdet.core import (delta2bbox, multiclass_nms, bbox_target, force_fp32,
-                        auto_fp16)
+from mmdet.core import (auto_fp16, bbox_target, delta2bbox, force_fp32,
+                        multiclass_nms)
 from ..builder import build_loss
 from ..losses import accuracy
 from ..registry import HEADS

mmdet/models/bbox_heads/convfc_bbox_head.py

 import torch.nn as nn
 
-from .bbox_head import BBoxHead
 from ..registry import HEADS
 from ..utils import ConvModule
+from .bbox_head import BBoxHead
 
 
 @HEADS.register_module

mmdet/models/builder.py

 from torch import nn
 
 from mmdet.utils import build_from_cfg
-from .registry import (BACKBONES, NECKS, ROI_EXTRACTORS, SHARED_HEADS, HEADS,
-                       LOSSES, DETECTORS)
+from .registry import (BACKBONES, DETECTORS, HEADS, LOSSES, NECKS,
+                       ROI_EXTRACTORS, SHARED_HEADS)
 
 
 def build(cfg, registry, default_args=None):

mmdet/models/detectors/base.py

@@ -3,10 +3,10 @@ from abc import ABCMeta, abstractmethod
 
 import mmcv
 import numpy as np
-import torch.nn as nn
 import pycocotools.mask as maskUtils
+import torch.nn as nn
 
-from mmdet.core import tensor2imgs, get_classes, auto_fp16
+from mmdet.core import auto_fp16, get_classes, tensor2imgs
 
 
 class BaseDetector(nn.Module):

mmdet/models/detectors/cascade_rcnn.py

@@ -3,12 +3,12 @@ from __future__ import division
 import torch
 import torch.nn as nn
 
-from .base import BaseDetector
-from .test_mixins import RPNTestMixin
+from mmdet.core import (bbox2result, bbox2roi, build_assigner, build_sampler,
+                        merge_aug_masks)
 from .. import builder
 from ..registry import DETECTORS
-from mmdet.core import (build_assigner, bbox2roi, bbox2result, build_sampler,
-                        merge_aug_masks)
+from .base import BaseDetector
+from .test_mixins import RPNTestMixin
 
 
 @DETECTORS.register_module

mmdet/models/detectors/fast_rcnn.py

-from .two_stage import TwoStageDetector
 from ..registry import DETECTORS
+from .two_stage import TwoStageDetector
 
 
 @DETECTORS.register_module

mmdet/models/detectors/faster_rcnn.py

-from .two_stage import TwoStageDetector
 from ..registry import DETECTORS
+from .two_stage import TwoStageDetector
 
 
 @DETECTORS.register_module

mmdet/models/detectors/fcos.py

-from .single_stage import SingleStageDetector
 from ..registry import DETECTORS
+from .single_stage import SingleStageDetector
 
 
 @DETECTORS.register_module

mmdet/models/detectors/grid_rcnn.py

-from .two_stage import TwoStageDetector
-from ..registry import DETECTORS
-
 import torch
 
+from mmdet.core import bbox2result, bbox2roi, build_assigner, build_sampler
 from .. import builder
-from mmdet.core import bbox2roi, bbox2result, build_assigner, build_sampler
+from ..registry import DETECTORS
+from .two_stage import TwoStageDetector
 
 
 @DETECTORS.register_module

mmdet/models/detectors/htc.py

 import torch
 import torch.nn.functional as F
 
-from .cascade_rcnn import CascadeRCNN
+from mmdet.core import (bbox2result, bbox2roi, build_assigner, build_sampler,
+                        merge_aug_masks)
 from .. import builder
 from ..registry import DETECTORS
-from mmdet.core import (bbox2roi, bbox2result, build_assigner, build_sampler,
-                        merge_aug_masks)
+from .cascade_rcnn import CascadeRCNN
 
 
 @DETECTORS.register_module