linter fix

train.py

@@ -190,7 +190,7 @@ def train(model, criterion, criterion_st, optimizer, optimizer_st, scheduler,
         grad_norm, _ = check_update(model, c.grad_clip)
         optimizer.step()
 
-        # compute alignment score  
+        # compute alignment score
         align_score = alignment_diagonal_score(alignments)
         keep_avg.update_value('avg_align_score', align_score)
 
@@ -281,7 +281,7 @@ def train(model, criterion, criterion_st, optimizer, optimizer_st, scheduler,
         "AvgPostnetLoss:{:.5f}  AvgDecoderLoss:{:.5f}  "
         "AvgStopLoss:{:.5f}  EpochTime:{:.2f}  "
         "AvgStepTime:{:.2f}  AvgLoaderTime:{:.2f}".format(global_step, keep_avg['avg_postnet_loss'], keep_avg['avg_decoder_loss'],
-                                                          keep_avg['avg_stop_loss'], keep_avg['avg_align_score'], 
+                                                          keep_avg['avg_stop_loss'], keep_avg['avg_align_score'],
                                                           epoch_time, keep_avg['avg_step_time'], keep_avg['avg_loader_time']),
         flush=True)
 
@@ -305,11 +305,11 @@ def evaluate(model, criterion, criterion_st, ap, global_step, epoch):
         speaker_mapping = load_speaker_mapping(OUT_PATH)
     model.eval()
     epoch_time = 0
-    eval_values_dict = {'avg_postnet_loss' : 0,
-                        'avg_decoder_loss' : 0,
-                        'avg_stop_loss' : 0,
+    eval_values_dict = {'avg_postnet_loss': 0,
+                        'avg_decoder_loss': 0,
+                        'avg_stop_loss': 0,
                         'avg_align_score': 0}
-    keep_avg = KeepAverage() 
+    keep_avg = KeepAverage()
     keep_avg.add_values(eval_values_dict)
     print("\n > Validation")
     if c.test_sentences_file is None:
@@ -401,18 +401,19 @@ def evaluate(model, criterion, criterion_st, ap, global_step, epoch):
                     if c.stopnet:
                         stop_loss = reduce_tensor(stop_loss.data, num_gpus)
 
-                keep_avg.update_values({'avg_postnet_loss' : float(postnet_loss.item()),
-                                        'avg_decoder_loss' : float(decoder_loss.item()),
-                                        'avg_stop_loss' : float(stop_loss.item())})
+                keep_avg.update_values({'avg_postnet_loss': float(postnet_loss.item()),
+                                        'avg_decoder_loss': float(decoder_loss.item()),
+                                        'avg_stop_loss': float(stop_loss.item())})
 
                 if num_iter % c.print_step == 0:
                     print(
                         "   | > TotalLoss: {:.5f}   PostnetLoss: {:.5f} - {:.5f}  DecoderLoss:{:.5f} - {:.5f} "
-                        "StopLoss: {:.5f} - {:.5f}  AlignScore: {:.4f} : {:.4f}".format(loss.item(),
-                                                    postnet_loss.item(), keep_avg['avg_postnet_loss'],
-                                                    decoder_loss.item(), keep_avg['avg_decoder_loss'],
-                                                    stop_loss.item(), keep_avg['avg_stop_loss'],
-                                                    align_score.item(), keep_avg['avg_align_score']),
+                        "StopLoss: {:.5f} - {:.5f}  AlignScore: {:.4f} : {:.4f}".format(
+                            loss.item(),
+                            postnet_loss.item(), keep_avg['avg_postnet_loss'],
+                            decoder_loss.item(), keep_avg['avg_decoder_loss'],
+                            stop_loss.item(), keep_avg['avg_stop_loss'],
+                            align_score.item(), keep_avg['avg_align_score']),
                         flush=True)
 
             if args.rank == 0:

utils/generic_utils.py

@@ -31,7 +31,8 @@ def load_config(config_path):
 def get_git_branch():
     try:
         out = subprocess.check_output(["git", "branch"]).decode("utf8")
-        current = next(line for line in out.split("\n") if line.startswith("*"))
+        current = next(line for line in out.split(
+            "\n") if line.startswith("*"))
         current.replace("* ", "")
     except subprocess.CalledProcessError:
         current = "inside_docker"
@@ -298,7 +299,7 @@ def split_dataset(items):
         # most stupid code ever -- Fix it !
         while len(items_eval) < eval_split_size:
             speakers = [item[-1] for item in items]
-            speaker_counter = Counter(speakers) 
+            speaker_counter = Counter(speakers)
             item_idx = np.random.randint(0, len(items))
             if speaker_counter[items[item_idx][-1]] > 1:
                 items_eval.append(items[item_idx])
@@ -323,20 +324,21 @@ class KeepAverage():
 
     def __getitem__(self, key):
         return self.avg_values[key]
-    
+
     def add_value(self, name, init_val=0, init_iter=0):
         self.avg_values[name] = init_val
         self.iters[name] = init_iter
-    
+
     def update_value(self, name, value, weighted_avg=False):
         if weighted_avg:
             self.avg_values[name] = 0.99 * self.avg_values[name] + 0.01 * value
             self.iters[name] += 1
         else:
-            self.avg_values[name] = self.avg_values[name] * self.iters[name] + value 
+            self.avg_values[name] = self.avg_values[name] * \
+                self.iters[name] + value
             self.iters[name] += 1
             self.avg_values[name] /= self.iters[name]
-    
+
     def add_values(self, name_dict):
         for key, value in name_dict.items():
             self.add_value(key, init_val=value)
@@ -344,4 +346,3 @@ class KeepAverage():
     def update_values(self, value_dict):
         for key, value in value_dict.items():
             self.update_value(key, value)
-    

utils/measures.py

@@ -1,6 +1,3 @@
-import torch
-import numpy as np
-
 
 def alignment_diagonal_score(alignments):
     """
@@ -12,8 +9,3 @@ def alignment_diagonal_score(alignments):
         alignments : batch x decoder_steps x encoder_steps
     """
     return alignments.max(dim=1)[0].mean(dim=1).mean(dim=0)
-
-
-
-
-