Merge pull request #59 from beyretb/dev-v1.0.5

Dev v1.0.5

README.md

@@ -167,11 +167,12 @@ features with the agent's frames in order to have frames in line with the config
 
 ## Version History
 
-- v1.0.4
+- v1.0.5
     - Adds customisable resolution during evaluation
     - Update `animalai-train` to tf 1.14 to fix `gin` broken dependency
     - Release source code for the environment (no support to be provided on this for now)
-
+    - Fixes some legacy dependencies and typos in both libraries
+
 - v1.0.3
     - Adds inference mode to Gym environment
     - Adds seed to Gym Environment

animalai/animalai/envs/gym/environment.py

@@ -56,7 +56,7 @@ def __init__(self,
                                      arenas_configurations=arenas_configurations,
                                      inference=inference,
                                      resolution=resolution)
-        # self.name = self._env.academy_name
+        self.name = 'aaio'
         self.vector_obs = None
         self.inference = inference
         self.resolution = resolution

animalai/setup.py

@@ -2,7 +2,7 @@
 
 setup(
     name='animalai',
-    version='1.0.3',
+    version='1.0.5',
     description='Animal AI competition interface',
     url='https://github.com/beyretb/AnimalAI-Olympics',
     author='Benjamin Beyret',

examples/animalai_train/animalai_train/trainers/curriculum.py

@@ -10,12 +10,10 @@
 
 
 class Curriculum(object):
-    def __init__(self, location, default_reset_parameters):
+    def __init__(self, location):
         """
         Initializes a Curriculum object.
         :param location: Path to JSON defining curriculum.
-        :param default_reset_parameters: Set of reset parameters for
-               environment.
         """
         self.max_lesson_num = 0
         self.measure = None
@@ -47,10 +45,10 @@ def __init__(self, location, default_reset_parameters):
 
         parameters = self.data['parameters']
         for key in parameters:
-            if key not in default_reset_parameters:
-                raise CurriculumError(
-                    'The parameter {0} in Curriculum {1} is not present in '
-                    'the Environment'.format(key, location))
+            # if key not in default_reset_parameters:
+            #     raise CurriculumError(
+            #         'The parameter {0} in Curriculum {1} is not present in '
+            #         'the Environment'.format(key, location))
             if len(parameters[key]) != self.max_lesson_num + 1:
                 raise CurriculumError(
                     'The parameter {0} in Curriculum {1} must have {2} values '

examples/animalai_train/animalai_train/trainers/learn.py

@@ -92,7 +92,7 @@ def try_create_meta_curriculum(curriculum_folder: Optional[str], env: UnityEnvir
     if curriculum_folder is None:
         return None
     else:
-        meta_curriculum = MetaCurriculum(curriculum_folder, env._resetParameters)
+        meta_curriculum = MetaCurriculum(curriculum_folder)
         if meta_curriculum:
             for brain_name in meta_curriculum.brains_to_curriculums.keys():
                 if brain_name not in env.external_brain_names:
@@ -167,8 +167,7 @@ def init_environment(env_path, docker_target_name, no_graphics, worker_id, fast_
         file_name=env_path,
         worker_id=worker_id,
         seed=seed,
-        docker_training=docker_training,
-        no_graphics=no_graphics
+        docker_training=docker_training
     )
 
 

examples/animalai_train/animalai_train/trainers/meta_curriculum.py

@@ -14,16 +14,14 @@ class MetaCurriculum(object):
     particular brain in the environment.
     """
 
-    def __init__(self, curriculum_folder, default_reset_parameters):
+    def __init__(self, curriculum_folder):
         """Initializes a MetaCurriculum object.
 
         Args:
             curriculum_folder (str): The relative or absolute path of the
                 folder which holds the curriculums for this environment.
                 The folder should contain JSON files whose names are the
                 brains that the curriculums belong to.
-            default_reset_parameters (dict): The default reset parameters
-                of the environment.
         """
         used_reset_parameters = set()
         self._brains_to_curriculums = {}
@@ -33,8 +31,7 @@ def __init__(self, curriculum_folder, default_reset_parameters):
                 brain_name = curriculum_filename.split('.')[0]
                 curriculum_filepath = \
                     os.path.join(curriculum_folder, curriculum_filename)
-                curriculum = Curriculum(curriculum_filepath,
-                                        default_reset_parameters)
+                curriculum = Curriculum(curriculum_filepath)
 
                 # Check if any two curriculums use the same reset params.
                 if any([(parameter in curriculum.get_config().keys())

examples/animalai_train/setup.py

@@ -2,7 +2,7 @@
 
 setup(
     name='animalai_train',
-    version='1.0.4',
+    version='1.0.5',
     description='Animal AI competition training library',
     url='https://github.com/beyretb/AnimalAI-Olympics',
     author='Benjamin Beyret',
@@ -20,7 +20,7 @@
     zip_safe=False,
 
     install_requires=[
-        'animalai>=1.0.3',
+        'animalai>=1.0.5',
         'dopamine-rl',
         'tensorflow==1.14',
         'matplotlib',
@@ -31,6 +31,7 @@
         'pyyaml>=5.1',
         'atari-py',
         'jsonpickle>=1.2',
+        'docopt',
         'pypiwin32==223;platform_system=="Windows"'],
     python_requires=">=3.5,<3.8",
 )

examples/submission/agent.py

@@ -46,9 +46,11 @@ def reset(self, t=250):
 
     def step(self, obs, reward, done, info):
         """
-        A single step the agent should take based on the current
-        :param brain_info:  a single BrainInfo containing the observations and reward for a single step for one agent
-        :return:            a list of actions to execute (of size 2)
+        :param obs: agent's observation of the current environment
+        :param reward: amount of reward returned after previous action
+        :param done: whether the episode has ended.
+        :param info: contains auxiliary diagnostic information, including BrainInfo.
+        :return: the action to take, a list or size 2
         """
 
         brain_info = info['brain_info']