Fixing data modification and torch seed issues

chemprop/train/cross_validate.py

@@ -1,4 +1,5 @@
 from collections import defaultdict
+from copy import deepcopy
 import csv
 from logging import Logger
 import os
@@ -58,9 +59,6 @@ def cross_validate(args: TrainArgs,
     # Save args
     args.save(os.path.join(args.save_dir, 'args.json'))
 
-    # Set pytorch seed for random initial weights
-    torch.manual_seed(args.pytorch_seed)
-
     # Get data
     debug('Loading data')
     data = get_data(path=args.data_path, args=args, logger=logger, skip_none_targets=True)
@@ -75,7 +73,7 @@ def cross_validate(args: TrainArgs,
         args.seed = init_seed + fold_num
         args.save_dir = os.path.join(save_dir, f'fold_{fold_num}')
         makedirs(args.save_dir)
-        model_scores = train_func(args, data, logger)
+        model_scores = train_func(args, deepcopy(data), logger)  # deepcopy since data may be modified
         for metric, scores in model_scores.items():
             all_scores[metric].append(scores)
     all_scores = dict(all_scores)

chemprop/train/run_training.py

@@ -1,6 +1,5 @@
 from logging import Logger
 import os
-import sys
 from typing import Dict, List
 
 import numpy as np
@@ -40,6 +39,9 @@ def run_training(args: TrainArgs,
     else:
         debug = info = print
 
+    # Set pytorch seed for random initial weights
+    torch.manual_seed(args.pytorch_seed)
+
     # Split data
     debug(f'Splitting data with seed {args.seed}')
     if args.separate_test_path: