fix random seeds for reproducibility

train.py

@@ -1,6 +1,7 @@
 import argparse
 import collections
 import torch
+import numpy as np
 import data_loader.data_loaders as module_data
 import model.loss as module_loss
 import model.metric as module_metric
@@ -9,6 +10,13 @@
 from trainer import Trainer
 
 
+# fix random seeds for reproducibility
+SEED = 123
+torch.manual_seed(SEED)
+torch.backends.cudnn.deterministic = True
+torch.backends.cudnn.benchmark = False
+np.random.seed(SEED)
+
 def main(config):
     logger = config.get_logger('train')