update evo conf

evo/rc_car_outdoor.yaml

 #CMA Configuration
 CMA:
-  population_size: 64
+  population_size: 48
   init_sigma: 0.1
 
 Worker:
@@ -23,11 +23,11 @@ Solution:
   output_dim: 2
   output_activation: "tanh"
   activation: "tanh"
-  num_hiddens: [14,]
+  num_hiddens: [10,]
   l2_coefficient: 0
   patch_size: 8
   patch_stride: 4
-  top_k: 14
+  top_k: 10
   data_dim: 3
   normalize_positions: True
   use_lstm_controller: True 

evo/run_master.py

@@ -67,6 +67,10 @@ def run_master(config):
         use_conv_features=settings["Solution"]["use_conv_features"],
         num_conv_features=settings["Solution"]["num_conv_features"],
     )
+    if config.pretrained != "":
+        solution.load(config.pretrained)
+
+
 
     cma = CMA(
         population_size=settings["CMA"]["population_size"],
@@ -130,6 +134,7 @@ if __name__ == "__main__":
     )
     parser.add_argument("--port", help="Master port.", type=int, default=10000)
     parser.add_argument("--exp-name", help="Experiment name", default="CMA-ES Test")
+    parser.add_argument("--pretrained", help="Pretrained weights", default="")
     parser.add_argument(
         "--track",
         type=lambda x: bool(strtobool(x)),

evo/solution.py

@@ -421,6 +421,7 @@ class VisionTaskSolution(BaseTorchSolution):
         )
         self._layers.extend(self._mlp_solution.layers)
 
+        # exp 12
         #if self._use_conv_features:
         #    self._conv_features = nn.Sequential(
         #        nn.Conv2d(3, 6, 3),