Logging times supported closes #22

utils/logging.py

@@ -3,7 +3,7 @@
 
 import csv
 
-def log_to_csv(training_losses, validation_losses, metric_values, csv_path) -> None:
+def log_to_csv(training_losses, validation_losses, metric_values, times, csv_path) -> None:
     """
     Logs the training and validation losses, along with metric values, to a CSV file.
 
@@ -14,13 +14,15 @@ def log_to_csv(training_losses, validation_losses, metric_values, csv_path) -> N
             The keys are the names of the metrics, and the values are dictionaries
             with 'train' and 'valid' keys, representing the metric values for training
             and validation sets, respectively.
+        times (list): A list of times taken for each epoch.
         csv_path (str): The path to the CSV file where the log will be saved.
     """
     headers = ['epoch', 'train_loss', 'val_loss']
     metric_names = list(metric_values.keys())
     for name in metric_names:
         headers.append(f'train_{name}')
         headers.append(f'val_{name}')
+    headers.append('time')
 
     with open(csv_path, 'w', newline='') as csv_file:
         writer = csv.writer(csv_file)
@@ -39,6 +41,8 @@ def log_to_csv(training_losses, validation_losses, metric_values, csv_path) -> N
 
                 row.append(train_metrics[epoch] if epoch < len(train_metrics) else 'N/A')
                 row.append(valid_metrics[epoch] if epoch < len(valid_metrics) else 'N/A')
+
+            row.append(times[epoch])
 
             writer.writerow(row)