Create config.py

config.py

@@ -0,0 +1,49 @@
+
+import argparse
+
+parser = argparse.ArgumentParser()
+
+def add_argument_group(name):
+    arg = parser.add_argument_group(name)
+    return arg
+
+
+misc_arg = add_argument_group('misc')
+misc_arg.add_argument('--split', type=bool, default = True)
+misc_arg.add_argument('--input_size', type=int, default = 256, 
+                      help='multiplies of 256 by the structure of the model') 
+misc_arg.add_argument('--use_network', type=bool, default = False)
+
+data_arg = add_argument_group('data')
+data_arg.add_argument('--downloading', type=bool, default = False)
+
+graph_arg = add_argument_group('graph')
+graph_arg.add_argument('--filter_length', type=int, default = 32)
+graph_arg.add_argument('--kernel_size', type=int, default = 16)
+graph_arg.add_argument('--drop_rate', type=float, default = 0.2)
+
+train_arg = add_argument_group('train')
+train_arg.add_argument('--feature', type=str, default = "MLII",
+                       help='one of MLII, V1, V2, V4, V5. Favorably MLII or V1')
+train_arg.add_argument('--epochs', type=int, default = 80)
+train_arg.add_argument('--batch', type=int, default = 256)
+train_arg.add_argument('--patience', type=int, default = 10)
+train_arg.add_argument('--min_lr', type=float, default = 0.00005)
+train_arg.add_argument('--checkpoint_path', type=str, default = None)
+train_arg.add_argument('--resume_epoch', type=int)
+train_arg.add_argument('--ensemble', type=bool, default = False)
+train_arg.add_argument('--trained_model', type=str, default = None, 
+                       help='dir and filename of the trained model for usage.')
+
+predict_arg = add_argument_group('predict')
+predict_arg.add_argument('--num', type=int, default = None)
+predict_arg.add_argument('--upload', type=bool, default = False)
+predict_arg.add_argument('--sample_rate', type=int, default = None)
+predict_arg.add_argument('--cinc_download', type=bool, default = False)
+
+
+
+def get_config():
+    config, unparsed = parser.parse_known_args()
+
+    return config