add config functionality in command line

experiments/experiment_baseline.py

@@ -4,14 +4,31 @@ from pytorch_lightning import Trainer
 from test_tube import Experiment, HyperOptArgumentParser
 from models.baseline import CNN as Network
 
+config = {
+    'epochs':1
+}
 
+def epochs_500():
+    global config
+    config['epochs'] = 500
 
 def run(hparams):
     init_experiment(comment=hparams.experiment_name)
     from utils import CURR_RUN_PATH, logger # import these after init_experiment
     logger.info(CURR_RUN_PATH)
+    logger.info(f"tensorboard --logdir={CURR_RUN_PATH}")
     exp = Experiment(save_dir=CURR_RUN_PATH)
 
+    def setup_config():
+        conf = hparams.config
+        conf_func = globals()[conf]
+        try:
+            conf_func()
+        except:
+            logger.error(f"Config {conf} not defined")
+
+    setup_config()
+    global config
     # parameters used in the baseline (read from main.py and solver.py)
     # n_epochs = 500
     # lr = 1e-4
@@ -20,7 +37,7 @@ def run(hparams):
 
     if USE_GPU:
         trainer = Trainer(gpus=[0], distributed_backend='ddp',
-                          experiment=exp, max_nb_epochs=1, train_percent_check=1.0,
+                          experiment=exp, max_nb_epochs=config['epochs'], train_percent_check=hparams.train_percent,
                           fast_dev_run=False)
     else:
         trainer = Trainer(experiment=exp, max_nb_epochs=1, train_percent_check=0.01,
@@ -38,6 +55,11 @@ if __name__=='__main__':
     parent_parser = HyperOptArgumentParser(strategy='grid_search', add_help=False)
     parent_parser.add_argument('--experiment_name', type=str,
                                default='pt_lightning_exp_a', help='test tube exp name')
+    parent_parser.add_argument('--config', type=str, help='config function to run')
+    #TODO : multiple arguments for --config using nargs='+' is not working with the test_tube
+    # implementation of argument parser
+    parent_parser.add_argument('--train_percent', type=float,
+                               default=1.0, help='how much train data to use')
     parser = Network.add_model_specific_args(parent_parser)
     hyperparams = parser.parse_args()
     run(hyperparams)
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