diff --git a/configs/explore.json b/configs/explore.json
index 408c35d..ef3e350 100644
--- a/configs/explore.json
+++ b/configs/explore.json
@@ -34,6 +34,6 @@
     },
 
     "io" : {
-        "output_save_path" : "/deep/group/sudnya/repro/cnn2-size256_128-num64_64_dp0_5_str7"
+        "output_save_path" : "/deep/group/sudnya/launch-many-at-once/"
     }
 }
diff --git a/configs/param-adam.json b/configs/param-adam.json
new file mode 100644
index 0000000..1251e5d
--- /dev/null
+++ b/configs/param-adam.json
@@ -0,0 +1,45 @@
+{
+    "name" : "optimizer",
+    "value": [
+        {
+            "name": "adam",
+            "epochs" : 50,
+            "learning_rate" : 1e-2,
+            "decay_rate" : 1.0,
+            "decay_steps" : 2000,
+            "beta_1": 0.9,
+            "beta_2": 0.999,
+            "epsilon": 1e-08
+        },
+        {
+            "name": "adam",
+            "epochs" : 50,
+            "learning_rate" : 1e-2,
+            "decay_rate" : 1.0,
+            "decay_steps" : 2000,
+            "beta_1": 0.6,
+            "beta_2": 0.999,
+            "epsilon": 1e-08
+        },
+        {
+            "name": "adam",
+            "epochs" : 50,
+            "learning_rate" : 1e-2,
+            "decay_rate" : 1.0,
+            "decay_steps" : 2000,
+            "beta_1": 0.3,
+            "beta_2": 0.999,
+            "epsilon": 1e-08
+        },
+        {
+            "name": "adam",
+            "epochs" : 50,
+            "learning_rate" : 1e-2,
+            "decay_rate" : 1.0,
+            "decay_steps" : 2000,
+            "beta_1": 0.1,
+            "beta_2": 0.999,
+            "epsilon": 1e-08
+        }
+]
+}
diff --git a/configs/param.json b/configs/param.json
new file mode 100644
index 0000000..356eb60
--- /dev/null
+++ b/configs/param.json
@@ -0,0 +1,4 @@
+{
+    "name" : "dropout",
+    "value": [0.5, 0.6, 0.7]
+}
diff --git a/dq-launch.sh b/dq-launch.sh
new file mode 100755
index 0000000..fd41afe
--- /dev/null
+++ b/dq-launch.sh
@@ -0,0 +1,7 @@
+#!/bin/bash
+
+echo This job is running on $(hostname)
+export LD_LIBARY_PATH=/usr/local/cuda-8.0/lib64
+export PATH=/usr/local/cuda-8.0/bin
+python train.py -c $DQ_CFG
+echo "Started training at: ", $(date +%m:%d:%y-%H:%M:%S)
diff --git a/launch-many.py b/launch-many.py
new file mode 100644
index 0000000..c562483
--- /dev/null
+++ b/launch-many.py
@@ -0,0 +1,149 @@
+import argparse
+import json
+import logging
+import os
+import subprocess
+from pathlib import Path
+
+logger = logging.getLogger("Launcher")
+
+class Launcher:
+    """
+    Launcher class for calling dq to launch train.py with each entry in a  
+    list of hyperparameters
+    """
+    def __init__(self, default_config, param, experiment_name):
+        """
+        :param default_config: the default config file
+        :param param: the parameters to be overridden in the base config
+                     (these are the hyper parameters we search on and output 
+                      path)
+        :param experiment_name: name of the experiment
+        """
+        
+        output_dir = default_config.get("io").get("output_save_path")
+        output_dir = os.path.join( output_dir, experiment_name)
+
+        override_config = default_config
+        logger.debug("override cfg starts as " + str(override_config))
+        
+        ctr = 0
+        for p_name in param.get("value"):
+            logger.debug("Hyper param: " + str(p_name))
+            
+            #TODO not tested for more than one hyperparams list
+            for k, v in override_config.items():
+                if k == p_name:
+                    logger.debug ("Found " + str(p_name) + " : " + str(v))
+                    for i in param.get("value"):
+                        override_config[k] = i 
+                        #self.search_and_replace_dict(v, p_name), val)
+            
+                        o_dir_exp = self.get_op_path(output_dir, p_name, ctr)
+                        o_cfg_path = os.path.join(o_dir_exp, "override.cfg")
+                        ctr += 1
+                        override_config['io']['output_save_path'] = o_dir_exp
+            
+                        if not os.path.exists(o_dir_exp):
+                            logger.debug("Creating " + str(o_dir_exp))
+                            path = Path(o_dir_exp)
+                            path.mkdir(parents=True)
+                        
+                        with open(o_cfg_path, 'w') as fp:
+                            json.dump(override_config, fp)
+
+                        #call dq TODO
+                        DQ_CFG = output_cfg_path
+                        os.system("DQ_CFG=%s dq-submit dq-launch.sh"%output_cfg_path)
+
+
+    def get_cfg_path(self, output_dir, param_name, val):
+        dr = os.path.join(output_dir , param_name + "_" + str(val))
+        logger.debug("dir: " + str(dr))
+        return dr
+   
+
+#    #TODO: refactor later
+#    def search_and_replace_dict(self, cfg, param, val):
+#        if isinstance(cfg, dict):
+#            for k, v in cfg.items():
+#                
+#                # is a dict itself
+#                if isinstance(v, dict):
+#                    if k == param:
+#                        print("Found "+ str(k) + " : " + str(cfg[k]))
+#                        cfg[k] = val
+#                        print("Replaced to " + str(cfg[k]))
+#                        return
+#                    else:
+#                        return self.search_and_replace_dict(v, param, val)
+#                
+#        return
+
+
+
+def get_default_config():
+    retVal = {
+	"seed" : 4337,
+	"data" : { "path" : "/deep/group/med/alivecor/training2017", "seed" : 2016 },
+	"optimizer" : { "name": "momentum", "epochs" : 50, "learning_rate" : 1e-2,
+	    "momentum" : 0.95, "decay_rate" : 1.0, "decay_steps" : 2000
+	},
+	"model" : { "dropout" : 0.5, "batch_size" : 32,
+	    "conv_layers" : [
+		{ "filter_size" : 256, "num_filters" : 64, "stride" : 7 },
+		{ "filter_size" : 128, "num_filters" : 64, "stride" : 7 }
+	   ] },
+	"io" : {
+	    "output_save_path" : "/tmp"
+	}
+    }
+    return retVal
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Launcher")
+    parser.add_argument("-v", "--verbose", default=False, action="store_true")
+    parser.add_argument("-e", "--experiment_name", default=None)
+    parser.add_argument("-b", "--base_config", default=None)
+    parser.add_argument("-p", "--parameter_config", default=None)
+
+    parsed_arguments = parser.parse_args()
+    arguments = vars(parsed_arguments)
+
+    is_verbose       = arguments['verbose']
+    base_config      = arguments['base_config']
+    param_config     = arguments['parameter_config']
+    experiment_name  = arguments['experiment_name'].rstrip()
+
+    if is_verbose:
+        logging.basicConfig(level=logging.DEBUG)
+    else:
+        logging.basicConfig(level=logging.INFO)
+    
+
+    default_config = {}
+    param          = {}
+    if not base_config:
+        default_config = get_default_config()
+        logger.debug("No base cfg supplied, so using default - " + str(base_config))
+    else:
+        with open(base_config) as fid:
+            default_config = json.load(fid)
+    
+    if not param_config:
+        raise ValueError("Mandatory to specify parameter config")
+    else:
+        with open(param_config) as fid:
+            param = json.load(fid)
+    
+    if not experiment_name:
+        raise ValueError("Mandatory to specify experiment name")
+
+    launcher = Launcher(default_config, param, experiment_name)
+
+
+
+if __name__ == '__main__':
+    main()
+
diff --git a/launch.sh b/launch.sh
index 3738c40..6a860b1 100755
--- a/launch.sh
+++ b/launch.sh
@@ -2,5 +2,5 @@
 
 #gpu=3
 #env CUDA_VISIBLE_DEVICES=$gpu 
-python train.py -c configs/explore.json 
+python train.py -c configs/cnn20-lr-1.json -v
 echo "Started training at: ", $(date +%m:%d:%y-%H:%M:%S)