#917 - Almost there. All output files being writen for SB3/RLLIB PPO & A2C. Just need to bring in the hardcoded agents then update the testa and docs.

src/primaite/config/_package_data/lay_down/lay_down_config_1_DDOS_basic.yaml

@@ -1,7 +1,3 @@
-- item_type: ACTIONS
-  type: NODE
-- item_type: STEPS
-  steps: 128
 - item_type: PORTS
   ports_list:
     - port: '80'

src/primaite/config/_package_data/lay_down/lay_down_config_2_DDOS_basic.yaml

@@ -1,7 +1,3 @@
-- item_type: ACTIONS
-  type: NODE
-- item_type: STEPS
-  steps: 128
 - item_type: PORTS
   ports_list:
     - port: '80'

src/primaite/config/_package_data/lay_down/lay_down_config_3_DOS_very_basic.yaml

@@ -1,7 +1,3 @@
-- item_type: ACTIONS
-  type: NODE
-- item_type: STEPS
-  steps: 256
 - item_type: PORTS
   ports_list:
     - port: '80'

src/primaite/config/_package_data/training/training_config_main.yaml

@@ -59,7 +59,7 @@ observation_space_high_value: 1000000000
 # "NONE" (No Output)
 # "INFO" (Info Messages)
 # "ALL" (All Messages)
-output_verbose_level: INFO
+output_verbose_level: NONE
 
 # Reward values
 # Generic

src/primaite/config/training_config.py

@@ -185,7 +185,6 @@ class TrainingConfig:
         for field, enum_class in field_enum_map.items():
             if field in config_dict:
                 config_dict[field] = enum_class[config_dict[field]]
-
         return TrainingConfig(**config_dict)
 
     def to_dict(self, json_serializable: bool = True):
@@ -203,6 +202,7 @@ class TrainingConfig:
             data["red_agent_identifier"] = self.red_agent_identifier.value
             data["action_type"] = self.action_type.value
             data["output_verbose_level"] = self.output_verbose_level.value
+            data["session_type"] = self.session_type.value
 
         return data