Bug fixed

.gitignore

@@ -130,4 +130,4 @@ dmypy.json
 #NeuralMMO repository
 
 neuralmmo/resource/maps
-
+resource

Dockerfile

@@ -3,7 +3,7 @@
 
 # FROM aicrowd/base-images:neural-mmo-py38-torch-190
 # FROM aicrowd/base-images:neural-mmo-py38-torch-180
-FROM aicrowd/base-images:neural-mmo-py38-torch-171
+# FROM aicrowd/base-images:neural-mmo-py38-torch-171
 # FROM aicrowd/base-images:neural-mmo-py38
 
 USER root

config.py

-from agents import BaselineCombatAgent, BaselineForageAgent, RandomNeuralMMOAgent, BaselineRandomAgent
+from agents import BaselineCombatAgent, BaselineForageAgent, RandomNeuralMMOAgent, BaselineRandomAgent, NeuralBaselineAgent
 
 
 class LocalEvaluationConfig:

neuralmmo/Forge.py

@@ -38,7 +38,10 @@ def createPolicies(config, mapPolicy):
 def loadTrainer(config):
    '''Create monolithic RLlib trainer object'''
    torch.set_num_threads(1)
-   ray.init(local_mode=config.LOCAL_MODE)
+   ray.init(local_mode=config.LOCAL_MODE,
+     memory=2000 * 1024 * 1024,
+     object_store_memory=200 * 1024 * 1024,  
+   )
 
    #Register custom env
    ray.tune.registry.register_env("Neural_MMO",
@@ -88,12 +91,22 @@ def loadEvaluator(config):
 
 def loadModel(config):
    '''Load NN weights and optimizer state'''
+   imports()
    trainer = loadTrainer(config)
    utils.modelSize(trainer.defaultModel())
    if config.LOAD:
       trainer.restore()
    return trainer
 
+def imports():
+   '''conditional rl imports'''
+   global torch, ray, rllib, wrapper, utils
+   from neural_mmo.forge.ethyr.torch import utils
+   import torch
+   import ray
+   from ray import rllib
+   from projekt import rllib_wrapper as wrapper
+
 class Anvil():
    '''Neural MMO CLI powered by Google Fire
 
@@ -120,32 +133,24 @@ class Anvil():
       config.override(**kwargs)
       self.config = config
 
-   def imports(self):
-      '''conditional rl imports'''
-      global torch, ray, rllib, wrapper, utils
-      from neural_mmo.forge.ethyr.torch import utils
-      import torch
-      import ray
-      from ray import rllib
-      from projekt import rllib_wrapper as wrapper
 
    def train(self, **kwargs):
       '''Train a model starting with the current value of --MODEL'''
-      self.imports()
+      imports()
       loadModel(self.config).train()
 
    def evaluate(self, **kwargs):
       '''Evaluate a model on --EVAL_MAPS maps'''
       self.config.EVALUATE = True
       if not self.config.SCRIPTED:
-         self.imports()
+         imports()
       loadEvaluator(self.config).evaluate(self.config.GENERALIZE)
 
    def render(self, **kwargs):
       '''Start a WebSocket server that autoconnects to the 3D Unity client'''
       self.config.RENDER = True
       if not self.config.SCRIPTED:
-         self.imports()
+         imports()
       loadEvaluator(self.config).render()
 
    def generate(self, **kwargs):

neuralmmo/projekt/config.py

@@ -80,7 +80,7 @@ class SmallMaps(config.SmallMaps, RLlibConfig, config.AllGameSystems):
    EVALUATION_HORIZON      = 1024
 
    #Maps Path
-   PATH_MAPS = os.path.join(os.getcwd(),'neuralmmo/resource')
+   PATH_MAPS = os.path.join(os.getcwd(),'neuralmmo/resource/maps')
 
 
 class Debug(SmallMaps, config.AllGameSystems):