flake8 fixes

nmtpytorch/config.py

@@ -16,7 +16,7 @@
     'device_id': 'auto_1',       # auto_N for automatic N gpus
                                  # 0,1,2 for manual N gpus
                                  # 0 for 0th (single) GPU
-    'seed': 0,                   # > 0: only if you want to reproduce a previous experiment!
+    'seed': 0,                   # > 0 if you want to reproduce a previous experiment
     'gclip': 5.,                 # Clip gradients above clip_c
     'l2_reg': 0.,                # L2 penalty factor
     'patience': 20,              # Early stopping patience

nmtpytorch/datasets/multilabelmulti30k.py

@@ -6,7 +6,6 @@
 from .collate import get_collate
 
 
-
 class MultiLabelMulti30kDataset(object):
     """Returns a Dataset for multi-label Multi30k using raw JPG images.
 

nmtpytorch/layers/flatten.py

@@ -1,5 +1,6 @@
 import torch
 
+
 class Flatten(torch.nn.Module):
     """A flatten module to squeeze single dimensions."""
     def __init__(self):

nmtpytorch/layers/simplegru_decoder.py

@@ -4,7 +4,6 @@
 import torch.nn.functional as F
 
 from ..utils.data import to_var
-from ..utils.nn import get_rnn_hidden_state
 from . import FF, Attention
 
 
@@ -87,8 +86,8 @@ def f_init(self, ctx_dict):
 
         elif self.dec_init == 'mean':
             h_0 = self.ff_dec_init(
-                ctx.sum(0).div(ctx_mask.unsqueeze(-1).sum(0)) \
-                        if ctx_mask is not None else ctx.mean(0))
+                ctx.sum(0).div(ctx_mask.unsqueeze(-1).sum(0))
+                if ctx_mask is not None else ctx.mean(0))
         elif self.dec_init == 'max':
             h_0 = self.ff_dec_init(ctx.max(0)[0])
         elif self.dec_init == 'last':

nmtpytorch/models/nmt.py

@@ -42,6 +42,7 @@ def set_defaults(self):
             'max_trg_len': 80,          # Reject sentences where target > 80
             'direction': None,          # Network directionality, i.e. en->de
         }
+
     def __init__(self, opts, logger=None):
         super().__init__()
         self.print = print if logger is None else logger.info

nmtpytorch/models/sat.py

@@ -1,7 +1,5 @@
 # -*- coding: utf-8 -*-
 from ..layers import ImageEncoder, XuDecoder
-from ..vocabulary import Vocabulary
-from ..utils.topology import Topology
 
 from ..datasets import Multi30kRawDataset
 

nmtpytorch/tester.py

@@ -62,7 +62,7 @@ def __init__(self, **kwargs):
     def test(self, instance, split):
         instance.load_data(split)
         loader = instance.datasets[split].get_iterator(
-                self.batch_size, inference=True)
+            self.batch_size, inference=True)
 
         self.logger.info('Starting computation')
         start = time.time()