typo fixes

Author: ajbrock

layers.py

@@ -258,12 +258,12 @@ def forward(self, x, gain, bias):
 # Simple function to handle groupnorm norm stylization                      
 def groupnorm(x, norm_style):
   # If number of channels specified in norm_style:
-  if 'ch' in self.norm_style:
-    ch = int(self.norm_style.split('_')[-1])
+  if 'ch' in norm_style:
+    ch = int(norm_style.split('_')[-1])
     groups = max(int(x.shape[1]) // ch, 1)
   # If number of groups specified in norm style
-  elif 'grp' in self.norm_style:
-    groups = int(self.norm_style.split('_')[-1])
+  elif 'grp' in norm_style:
+    groups = int(norm_style.split('_')[-1])
   # If neither, default to groups = 16
   else:
     groups = 16

train.py

@@ -210,7 +210,7 @@ def run(config):
         if config['G_eval_mode']:
           print('Switchin G to eval mode...')
           G.eval()
-        train_fns.test(G, D, G_ema, state_dict, config, sample,
+        train_fns.test(G, D, G_ema, z_, y_, state_dict, config, sample,
                        get_inception_metrics, experiment_name, test_log)
     # Increment epoch counter at end of epoch
     state_dict['epoch'] += 1

train_fns.py

@@ -157,7 +157,7 @@ def save_and_sample(G, D, G_ema, z_, y_, fixed_z, fixed_y,
     are an improvement over the previous best (either in IS or FID, 
     user-specified), logs the results, and saves a best_ copy if it's an 
     improvement. '''
-def test(G, D, G_ema, state_dict, config, sample, get_inception_metrics,
+def test(G, D, G_ema, z_, y_, state_dict, config, sample, get_inception_metrics,
          experiment_name, test_log):
   print('Gathering inception metrics...')
   if config['accumulate_stats']: