[engine/predicter] spaces

bob/ip/binseg/engine/predicter.py

 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 
-import os 
+import os
 import logging
 import time
 import datetime
@@ -24,7 +24,7 @@ def do_predict(
 
     """
     Run inference and calculate metrics
-    
+
     Parameters
     ---------
     model : :py:class:`torch.nn.Module`
@@ -37,12 +37,12 @@ def do_predict(
     logger = logging.getLogger("bob.ip.binseg.engine.inference")
     logger.info("Start evaluation")
     logger.info("Output folder: {}, Device: {}".format(output_folder, device))
-    results_subfolder = os.path.join(output_folder,'results') 
+    results_subfolder = os.path.join(output_folder,'results')
     os.makedirs(results_subfolder,exist_ok=True)
-    
+
     model.eval().to(device)
-    # Sigmoid for probabilities 
-    sigmoid = torch.nn.Sigmoid() 
+    # Sigmoid for probabilities
+    sigmoid = torch.nn.Sigmoid()
 
     # Setup timers
     start_total_time = time.time()
@@ -55,24 +55,24 @@ def do_predict(
             start_time = time.perf_counter()
 
             outputs = model(images)
-            
-            # necessary check for hed architecture that uses several outputs 
+
+            # necessary check for hed architecture that uses several outputs
             # for loss calculation instead of just the last concatfuse block
             if isinstance(outputs,list):
                 outputs = outputs[-1]
-            
+
             probabilities = sigmoid(outputs)
-            
+
             batch_time = time.perf_counter() - start_time
             times.append(batch_time)
             logger.info("Batch time: {:.5f} s".format(batch_time))
-            
+
             # Create probability images
             save_probability_images(probabilities, names, output_folder, logger)
             # Save hdf5
             save_hdf(probabilities, names, output_folder, logger)
 
- 
+
     # Report times
     total_inference_time = str(datetime.timedelta(seconds=int(sum(times))))
     average_batch_inference_time = np.mean(times)
@@ -82,7 +82,7 @@ def do_predict(
 
     times_file = "Times.txt"
     logger.info("saving {}".format(times_file))
- 
+
     with open (os.path.join(results_subfolder,times_file), "w+") as outfile:
         date = datetime.datetime.now()
         outfile.write("Date: {} \n".format(date.strftime("%Y-%m-%d %H:%M:%S")))