Working on #18 : more configurability for autoencoders

autodqm_ml/algorithms/autoencoder.py

@@ -15,7 +15,7 @@
 from autodqm_ml import utils
 
 DEFAULT_OPT = {
-        "batch_size" : 16,
+        "batch_size" : 16, 
         "val_batch_size" : 1024,
         "n_epochs" : 1000,
         "early_stopping" : True,
@@ -51,10 +51,14 @@ def __init__(self, **kwargs):
 
         self.mode = kwargs.get('autoencoder_mode', 'individual')
         if not self.mode in ["individual", "simultaneous"]:
-            logger.exception("AutoEncoder : __init__] mode '%s' is not a recognized option for AutoEncoder. Currently available modes are 'individual' (default) and 'simultaneous'." % (self.mode))
+            logger.exception("[AutoEncoder : __init__] mode '%s' is not a recognized option for AutoEncoder. Currently available modes are 'individual' (default) and 'simultaneous'." % (self.mode))
             raise ValueError()
         self.models = {}
 
+        logger.debug("[AutoEncoder : __init__] Constructing AutoEncoder with the following training options and hyperparameters:")
+        for param, value in self.config.items():
+            logger.debug("\t %s : %s" % (param, str(value)))
+
 
     def load_model(self, model_file):
         """

scripts/train.py

@@ -83,10 +83,16 @@
     if not os.path.exists(args.algorithm):
         algorithm_config_file = expand_path(args.algorithm)
     else:
-        algorithm_config_file = algo
+        algorithm_config_file = args.algorithm
+
     with open(algorithm_config_file, "r") as f_in:
         config = json.load(f_in)
 
+    # Add command line arguments to config
+    for k,v in vars(args).items():
+        if v is not None:
+            config[k] = v # note: if you specify an argument both through command line argument and json, we give precedence to the version from command line arguments 
+
 else:
     config = vars(args)
     config["name"] = args.algorithm.lower()