[a3c] specify dir to save train logs

examples/A3C-Gym/train-atari.py

@@ -215,10 +215,6 @@ def get_training_dataflow(self):
 
 
 def train():
-    assert tf.test.is_gpu_available(), "Training requires GPUs!"
-    dirname = os.path.join('train_log', 'train-atari-{}'.format(ENV_NAME))
-    logger.set_logger_dir(dirname)
-
     # assign GPUs for training & inference
     num_gpu = get_num_gpu()
     global PREDICTOR_THREAD
@@ -275,9 +271,11 @@ def train():
     parser.add_argument('--env', help='env', required=True)
     parser.add_argument('--task', help='task to perform',
                         choices=['play', 'eval', 'train', 'dump_video'], default='train')
-    parser.add_argument('--output', help='output directory for submission', default='output_dir')
+    parser.add_argument('--output', help='output directory for logs and videos')
     parser.add_argument('--episode', help='number of episode to eval', default=100, type=int)
     args = parser.parse_args()
+    if args.output is None:
+        args.output = os.path.join('train_log', 'train-atari-{}'.format(args.env))
 
     ENV_NAME = args.env
     NUM_ACTIONS = get_player().action_space.n
@@ -303,4 +301,6 @@ def train():
                 get_player(train=False, dumpdir=args.output),
                 pred, args.episode)
     else:
+        assert tf.test.is_gpu_available(), "Training requires GPUs!"
+        logger.set_logger_dir(args.output)
         train()