Fix tests and flake8

fairseq/trainer.py

@@ -47,13 +47,13 @@ class Trainer(object):
         self.meters['train_nll_loss'] = AverageMeter()
         self.meters['valid_loss'] = AverageMeter()
         self.meters['valid_nll_loss'] = AverageMeter()
-        self.meters['wps'] = TimeMeter()      # words per second
-        self.meters['ups'] = TimeMeter()      # updates per second
-        self.meters['wpb'] = AverageMeter()   # words per batch
-        self.meters['bsz'] = AverageMeter()   # sentences per batch
-        self.meters['gnorm'] = AverageMeter() # gradient norm
-        self.meters['clip'] = AverageMeter()  # % of updates clipped
-        self.meters['oom'] = AverageMeter()   # out of memory
+        self.meters['wps'] = TimeMeter()       # words per second
+        self.meters['ups'] = TimeMeter()       # updates per second
+        self.meters['wpb'] = AverageMeter()    # words per batch
+        self.meters['bsz'] = AverageMeter()    # sentences per batch
+        self.meters['gnorm'] = AverageMeter()  # gradient norm
+        self.meters['clip'] = AverageMeter()   # % of updates clipped
+        self.meters['oom'] = AverageMeter()    # out of memory
 
         self._max_bsz_seen = 0
         self._num_updates = 0

preprocess.py

@@ -39,6 +39,7 @@ def get_parser():
     parser.add_argument('--joined-dictionary', action='store_true', help='Generate joined dictionary')
     return parser
 
+
 def main(args):
     print(args)
     os.makedirs(args.destdir, exist_ok=True)

tests/test_binaries.py

@@ -11,12 +11,16 @@ import random
 import sys
 import tempfile
 import unittest
+from unittest import mock
 
 import torch
 
 from fairseq import options
 
-import preprocess, train, generate, interactive
+import preprocess
+import train
+import generate
+import interactive
 
 
 class TestBinaries(unittest.TestCase):
@@ -82,7 +86,9 @@ class TestBinaries(unittest.TestCase):
                 '--no-progress-bar',
             ],
         )
-        train.main(train_args)
+        with mock.patch('train.torch.cuda.device_count') as device_count:
+            device_count.return_value = 1
+            train.main(train_args)
 
     def generate(self, data_dir):
         generate_parser = options.get_generation_parser()

train.py

@@ -14,6 +14,7 @@ from distributed_train import main as distributed_main
 from multiprocessing_train import main as multiprocessing_main
 from singleprocess_train import main as singleprocess_main
 
+
 def main(args):
     if args.distributed_port > 0 \
             or args.distributed_init_method is not None:
@@ -23,6 +24,7 @@ def main(args):
     else:
         singleprocess_main(args)
 
+
 if __name__ == '__main__':
     parser = options.get_training_parser()
     args = options.parse_args_and_arch(parser)