default `--predict_batch_size=8`

finetune_args.py

@@ -78,7 +78,7 @@ data_g.add_arg("dev_set",             str,  None,  "Path to validation data.")
 data_g.add_arg("vocab_path",          str,  None,  "Vocabulary path.")
 data_g.add_arg("max_seq_len",         int,  512,   "Number of words of the longest seqence.")
 data_g.add_arg("batch_size",          int,  32,    "Total examples' number in batch for training. see also --in_tokens.")
-data_g.add_arg("predict_batch_size",  int,  None,    "Total examples' number in batch for predict. see also --in_tokens.")
+data_g.add_arg("predict_batch_size",  int,  8,    "Total examples' number in batch for predict. see also --in_tokens.")
 data_g.add_arg("in_tokens",           bool, False,
               "If set, the batch size will be the maximum number of tokens in one batch. "
               "Otherwise, it will be the maximum number of examples in one batch.")

run_classifier.py

@@ -80,8 +80,6 @@ def main(args):
     if args.random_seed is not None:
         startup_prog.random_seed = args.random_seed
 
-    if args.predict_batch_size == None:
-        args.predict_batch_size = args.batch_size
     if args.do_train:
         train_data_generator = reader.data_generator(
             input_file=args.train_set,