Add seed and thread arguments (#43)

So that any experiments can be controlled from the command line, I've set the defaults to what they were hardcoded (for the seed) and num_threads in kim_cnn to be consistent with the default in sm_cnn.

kim_cnn/main.py

@@ -11,10 +11,6 @@ import os
 if __name__=='__main__':
 
   import argparse
-  torch.manual_seed(3435)
-  np.random.seed(3435)
-  if torch.cuda.is_available():
-    torch.cuda.manual_seed(3435)
 
 
   argparser = argparse.ArgumentParser()
@@ -22,12 +18,20 @@ if __name__=='__main__':
   argparser.add_argument('--validate', action='store_true')
   argparser.add_argument('--test', action='store_true')
   argparser.add_argument('--load', action='store_true')
+  argparser.add_argument('--seed', help='Random seed', type=int, default=3435)
+  argparser.add_argument('--num_threads', help='The number of threads to use', type=int, default=4)
 
   args, extra_args = argparser.parse_known_args()
   # args.train = True/False ...
   # extra_args['--some': "xxxx"]
   cargs = {k: v for (k, v) in vars(Configurable.argparser.parse_args(extra_args)).items() if v is not None}
 
+  torch.manual_seed(args.seed)
+  np.random.seed(args.seed)
+  if torch.cuda.is_available():
+    torch.cuda.manual_seed(args.seed)
+  torch.set_num_threads(args.num_threads)
+
   if 'model_type' not in cargs:
     print("You need to specify the model_type")
     exit()
@@ -78,4 +82,4 @@ if __name__=='__main__':
     print(network.test(validate=True))
   elif args.test:
     print("### The accuracy for test set: ")
-    print(network.test(validate=False))
+    print(network.test(validate=False))

sm_cnn/main.py

@@ -118,11 +118,12 @@ if __name__ == "__main__":
     ap.add_argument("--dash-split", help="split words containing hyphens", action="store_true")
     ap.add_argument("--index-for-corpusIDF", help="fetches idf from Index. provide index path. will\
     generate a vocabFile")
+    ap.add_argument('--seed', help='Random seed', type=int, default=1234)
 
     args = ap.parse_args()
 
-    torch.manual_seed(1234)
-    np.random.seed(1234)
+    torch.manual_seed(args.seed)
+    np.random.seed(args.seed)
     torch.set_num_threads(args.num_threads)
 
     train_set, dev_set, test_set = 'train-all', 'raw-dev', 'raw-test'