Add yapf and isort to travis (#96)

* add yapf and isort to travis

* minor formatting

* remove blank lines

* skip unit tests for progressbar when python2

* update travis to ubuntu 16.04

* use a newer version ffmpeg

* add -y to add-apt-repository

.travis.yml

-dist: trusty
+dist: xenial
 sudo: required
 language: python
 
 before_install:
-  - sudo add-apt-repository -y ppa:mc3man/trusty-media
+  - sudo add-apt-repository -y ppa:mc3man/xerus-media
   - sudo apt-get update
   - sudo apt-get install -y ffmpeg
 
 install:
-  - pip install opencv-python pyyaml codecov flake8 Cython
+  - pip install Cython opencv-python pyyaml codecov flake8 yapf isort
 
 cache:
   pip: true
@@ -19,11 +19,14 @@ env:
 
 python:
   - "2.7"
-  - "3.4"
   - "3.5"
   - "3.6"
+  - "3.7"
 
-before_script: flake8
+before_script:
+  - flake8
+  - isort -rc --diff mmcv/ tests/ examples/
+  - yapf -r -d mmcv/ tests/ examples/
 
 script: coverage run --source=mmcv setup.py test
 

examples/train_cifar10.py

@@ -3,18 +3,18 @@ import os
 from argparse import ArgumentParser
 from collections import OrderedDict
 
+import resnet_cifar
 import torch
 import torch.distributed as dist
 import torch.multiprocessing as mp
 import torch.nn.functional as F
-from mmcv import Config
-from mmcv.runner import Runner, DistSamplerSeedHook
 from torch.nn.parallel import DataParallel, DistributedDataParallel
 from torch.utils.data import DataLoader
 from torch.utils.data.distributed import DistributedSampler
 from torchvision import datasets, transforms
 
-import resnet_cifar
+from mmcv import Config
+from mmcv.runner import DistSamplerSeedHook, Runner
 
 
 def accuracy(output, target, topk=(1, )):

mmcv/arraymisc/quantization.py

@@ -50,7 +50,7 @@ def dequantize(arr, min_val, max_val, levels, dtype=np.float64):
             'min_val ({}) must be smaller than max_val ({})'.format(
                 min_val, max_val))
 
-    dequantized_arr = (arr + 0.5).astype(dtype) * (
-        max_val - min_val) / levels + min_val
+    dequantized_arr = (arr + 0.5).astype(dtype) * (max_val -
+                                                   min_val) / levels + min_val
 
     return dequantized_arr

mmcv/cnn/resnet.py

@@ -3,8 +3,8 @@ import logging
 import torch.nn as nn
 import torch.utils.checkpoint as cp
 
-from .weight_init import constant_init, kaiming_init
 from ..runner import load_checkpoint
+from .weight_init import constant_init, kaiming_init
 
 
 def conv3x3(in_planes, out_planes, stride=1, dilation=1):

mmcv/cnn/vgg.py

@@ -2,8 +2,8 @@ import logging
 
 import torch.nn as nn
 
-from .weight_init import constant_init, normal_init, kaiming_init
 from ..runner import load_checkpoint
+from .weight_init import constant_init, kaiming_init, normal_init
 
 
 def conv3x3(in_planes, out_planes, dilation=1):

mmcv/fileio/handlers/yaml_handler.py

 import yaml
+
 try:
     from yaml import CLoader as Loader, CDumper as Dumper
 except ImportError:
     from yaml import Loader, Dumper
 
-from .base import BaseFileHandler
+from .base import BaseFileHandler  # isort:skip
 
 
 class YamlHandler(BaseFileHandler):

mmcv/fileio/io.py

+from ..utils import is_list_of, is_str
 from .handlers import BaseFileHandler, JsonHandler, PickleHandler, YamlHandler
-from ..utils import is_str, is_list_of
 
 file_handlers = {
     'json': JsonHandler(),

mmcv/image/io.py

@@ -3,8 +3,8 @@ import os.path as osp
 import cv2
 import numpy as np
 
-from mmcv.utils import is_str, check_file_exist, mkdir_or_exist
 from mmcv.opencv_info import USE_OPENCV2
+from mmcv.utils import check_file_exist, is_str, mkdir_or_exist
 
 if not USE_OPENCV2:
     from cv2 import IMREAD_COLOR, IMREAD_GRAYSCALE, IMREAD_UNCHANGED

mmcv/parallel/distributed.py

 import torch
 import torch.distributed as dist
 import torch.nn as nn
-from torch._utils import (_flatten_dense_tensors, _unflatten_dense_tensors,
-                          _take_tensors)
+from torch._utils import (_flatten_dense_tensors, _take_tensors,
+                          _unflatten_dense_tensors)
 
 from .scatter_gather import scatter_kwargs
 

mmcv/runner/checkpoint.py

@@ -6,14 +6,13 @@ import warnings
 from collections import OrderedDict
 from importlib import import_module
 
-import mmcv
 import torch
 import torchvision
 from torch.utils import model_zoo
 
+import mmcv
 from .utils import get_dist_info
 
-
 open_mmlab_model_urls = {
     'vgg16_caffe': 'https://s3.ap-northeast-2.amazonaws.com/open-mmlab/pretrain/third_party/vgg16_caffe-292e1171.pth',  # noqa: E501
     'resnet50_caffe': 'https://s3.ap-northeast-2.amazonaws.com/open-mmlab/pretrain/third_party/resnet50_caffe-788b5fa3.pth',  # noqa: E501

mmcv/runner/hooks/checkpoint.py

-from .hook import Hook
 from ..utils import master_only
+from .hook import Hook
 
 
 class CheckpointHook(Hook):

mmcv/runner/hooks/logger/pavi.py

 from __future__ import print_function
-
 import logging
 import os
 import os.path as osp
@@ -10,8 +9,8 @@ from threading import Thread
 import requests
 from six.moves.queue import Empty, Queue
 
+from ...utils import get_host_info, master_only
 from .base import LoggerHook
-from ...utils import master_only, get_host_info
 
 
 class PaviClient(object):

mmcv/runner/hooks/logger/tensorboard.py

 import os.path as osp
 
-from .base import LoggerHook
 from ...utils import master_only
+from .base import LoggerHook
 
 
 class TensorboardLoggerHook(LoggerHook):

mmcv/runner/hooks/logger/text.py

@@ -46,8 +46,9 @@ class TextLoggerHook(LoggerHook):
                     log_dict['time'], log_dict['data_time']))
                 log_str += 'memory: {}, '.format(log_dict['memory'])
         else:
-            log_str = 'Epoch({}) [{}][{}]\t'.format(
-                log_dict['mode'], log_dict['epoch'] - 1, log_dict['iter'])
+            log_str = 'Epoch({}) [{}][{}]\t'.format(log_dict['mode'],
+                                                    log_dict['epoch'] - 1,
+                                                    log_dict['iter'])
         log_items = []
         for name, val in log_dict.items():
             # TODO: resolve this hack

mmcv/runner/hooks/lr_updater.py

 from __future__ import division
-
 from math import cos, pi
 
 from .hook import Hook

mmcv/runner/runner.py

@@ -2,14 +2,14 @@ import logging
 import os.path as osp
 import time
 
-import mmcv
 import torch
 
+import mmcv
 from . import hooks
-from .log_buffer import LogBuffer
-from .hooks import (Hook, LrUpdaterHook, CheckpointHook, IterTimerHook,
-                    OptimizerHook, lr_updater)
 from .checkpoint import load_checkpoint, save_checkpoint
+from .hooks import (CheckpointHook, Hook, IterTimerHook, LrUpdaterHook,
+                    OptimizerHook, lr_updater)
+from .log_buffer import LogBuffer
 from .priority import get_priority
 from .utils import get_dist_info, get_host_info, get_time_str, obj_from_dict
 
@@ -139,8 +139,8 @@ class Runner(object):
             <class 'torch.optim.sgd.SGD'>
         """
         if isinstance(optimizer, dict):
-            optimizer = obj_from_dict(
-                optimizer, torch.optim, dict(params=self.model.parameters()))
+            optimizer = obj_from_dict(optimizer, torch.optim,
+                                      dict(params=self.model.parameters()))
         elif not isinstance(optimizer, torch.optim.Optimizer):
             raise TypeError(
                 'optimizer must be either an Optimizer object or a dict, '

mmcv/runner/utils.py

@@ -4,10 +4,11 @@ import time
 from getpass import getuser
 from socket import gethostname
 
-import mmcv
 import torch
 import torch.distributed as dist
 
+import mmcv
+
 
 def get_host_info():
     return '{}@{}'.format(getuser(), gethostname())

mmcv/utils/misc.py

@@ -3,6 +3,9 @@ import functools
 import itertools
 import subprocess
 from importlib import import_module
+
+import six
+
 # ABCs from collections will be deprecated in python 3.8+,
 # while collections.abc is not available in python 2.7
 try:
@@ -10,8 +13,6 @@ try:
 except ImportError:
     import collections as collections_abc
 
-import six
-
 
 def is_str(x):
     """Whether the input is an string instance."""

mmcv/utils/progressbar.py

@@ -11,8 +11,8 @@ class ProgressBar(object):
     def __init__(self, task_num=0, bar_width=50, start=True):
         self.task_num = task_num
         max_bar_width = self._get_max_bar_width()
-        self.bar_width = (bar_width
-                          if bar_width <= max_bar_width else max_bar_width)
+        self.bar_width = (
+            bar_width if bar_width <= max_bar_width else max_bar_width)
         self.completed = 0
         if start:
             self.start()

mmcv/video/__init__.py

 from .io import Cache, VideoReader, frames2video
 from .processing import convert_video, resize_video, cut_video, concat_video
-from .optflow import (flowread, flowwrite, quantize_flow,
-                      dequantize_flow, flow_warp)
+from .optflow import (flowread, flowwrite, quantize_flow, dequantize_flow,
+                      flow_warp)
 
 __all__ = [
     'Cache', 'VideoReader', 'frames2video', 'convert_video', 'resize_video',