fix issues with cloud training

config/ppo_transfer/CrawlerStatic.yaml

       learning_rate_schedule: linear
       encoder_layers: 2
       policy_layers: 1
-      feature_size: 64
+      value_layers: 1
+      feature_size: 256
     network_settings:
       normalize: true
       hidden_units: 512

ml-agents/mlagents/trainers/learn.py

     except Exception:
         print("\n\n\tUnity Technologies\n")
     print(get_version_string())
+    print(options)
+    print("transfer:", options.behaviors["3DBall"].transfer)
 
     if options.debug:
         log_level = logging_util.DEBUG
     if options.env_settings.seed == -1:
         run_seed = np.random.randint(0, 10000)
     run_training(run_seed, options)
-    if options.behaviors.transfer:
+    if options.behaviors["3DBall"].transfer:
         os.system('mlagents-learn config/ppo_transfer/3DBallHard.yaml --run-id=hardball-transfer --env=/unity-volume/3dballhard --num-envs=4 --force')
 
 

ml-agents/mlagents/trainers/settings.py

     threaded: bool = True
     self_play: Optional[SelfPlaySettings] = None
     behavioral_cloning: Optional[BehavioralCloningSettings] = None
+    transfer: bool = False
 
     cattr.register_structure_hook(
         Dict[RewardSignalType, RewardSignalSettings], RewardSignalSettings.structure