lint code

animalai_train/animalai_train/curriculum_aai.py

 import json
 import math
 import os
-from typing import Dict, Any, TextIO
 
 from mlagents.trainers.exception import (
     CurriculumConfigError,
-    CurriculumLoadingError,
     CurriculumError,
 )
 from mlagents.trainers.curriculum import Curriculum

animalai_train/animalai_train/meta_curriculum_aai.py

 """Contains the MetaCurriculum class."""
 import os
-from typing import Dict, Set
+from typing import Dict
 from mlagents.trainers.meta_curriculum import MetaCurriculum
 from mlagents.trainers.exception import MetaCurriculumError
 from animalai_train.curriculum_aai import CurriculumAAI

animalai_train/animalai_train/run_options_aai.py

-from typing import NamedTuple, Dict, Optional, List
+from typing import NamedTuple, Dict, Optional
 from animalai.envs.arena_config import ArenaConfig
 
 
@@ -38,7 +38,7 @@ class RunOptionsAAI(NamedTuple):
     keep_checkpoints:   How many model checkpoints to keep
     base_port:          Base port for environment communication
     num_envs:           Number of parallel environments to use for training
-    curriculum_config:  Path to curriculum training folder 
+    curriculum_config:  Path to curriculum training folder
     lesson:             Start learning from this lesson if using curriculum
     multi_gpu:          Whether or not to use multiple GPU (not in current version)
     cpu:                Run with CPU only

animalai_train/animalai_train/simple_env_manager_aai.py

-from typing import Dict, List, Optional
+from typing import Dict, List
 
 from mlagents.trainers.env_manager import EnvironmentStep
 from mlagents.trainers.simple_env_manager import SimpleEnvManager

examples/train_ml_agents_sac.py

-from mlagents.trainers.trainer_util import load_config
-from animalai.envs.arena_config import ArenaConfig
-
-from animalai_train.run_options_aai import RunOptionsAAI
-from animalai_train.run_training_aai import run_training_aai
-
 # TODO: add SAC trainer or maybe add directly to train_ml_agents.py
-
-# trainer_config_path = "configurations/training_configurations/train_ml_agents_config.yaml"
-# environment_path = "env/AnimalAI"
-# arena_config_path = "configurations/arena_configurations/train_ml_agents_arenas.yml"
-# run_id = "train_ml_agents"
-# base_port = 5005
-# number_of_environments = 4
-# number_of_arenas_per_environment = 8
-#
-# args = RunOptionsAAI(
-#     trainer_config=load_config(trainer_config_path),
-#     env_path=environment_path,
-#     run_id=run_id,
-#     base_port=base_port,
-#     num_envs=number_of_environments,
-#     arena_config=ArenaConfig(arena_config_path),
-#     n_arenas_per_env=number_of_arenas_per_environment,
-# )
-#
-# run_training_aai(0, args)