Copied test file to extend and implement training

examples/isaacgym_train.py

@@ -5,8 +5,6 @@ import matplotlib.pyplot as plt
 import torch
 from tqdm import trange
 
-from ml_logger import logger
-
 from Go2Py.sim.gym.envs import *
 from Go2Py.sim.gym.envs.base.legged_robot_config import Cfg
 from Go2Py.sim.gym.envs.go2.go2_config import config_go2
@@ -197,55 +195,12 @@ def run_env(render=False, headless=False):
         print("Show the first frame and exit.")
         exit()
 
-    # log the experiment parameters
-    logger.log_params(AC_Args=vars(AC_Args), PPO_Args=vars(PPO_Args), RunnerArgs=vars(RunnerArgs),
-                      Cfg=vars(Cfg))
-
-    env = HistoryWrapper(env)
-    gpu_id = 2
-    runner = Runner(env, device=f"cuda:{gpu_id}")
-    runner.learn(num_learning_iterations=10000, init_at_random_ep_len=True, eval_freq=100)
-
-    # for i in trange(1000, desc="Running"):
-    #     actions = 0. * torch.ones(env.num_envs, env.num_actions, device=env.device)
-    #     obs, rew, done, info = env.step(actions)
-    #     # breakpoint()
-    # print("Done")
+    for i in trange(1000, desc="Running"):
+        actions = 0. * torch.ones(env.num_envs, env.num_actions, device=env.device)
+        obs, rew, done, info = env.step(actions)
+        # breakpoint()
+    print("Done")
 
 
 if __name__ == '__main__':
-    from pathlib import Path
-    from ml_logger import logger
-    from go2_gym import MINI_GYM_ROOT_DIR
-
-    stem = Path(__file__).stem
-    logger.configure(logger.utcnow(f'gait-conditioned-agility/%Y-%m-%d/{stem}/%H%M%S.%f'),
-                     root=Path(f"{MINI_GYM_ROOT_DIR}/runs").resolve(), )
-    logger.log_text("""
-                charts: 
-                - yKey: train/episode/rew_total/mean
-                  xKey: iterations
-                - yKey: train/episode/rew_tracking_lin_vel/mean
-                  xKey: iterations
-                - yKey: train/episode/rew_tracking_contacts_shaped_force/mean
-                  xKey: iterations
-                - yKey: train/episode/rew_action_smoothness_1/mean
-                  xKey: iterations
-                - yKey: train/episode/rew_action_smoothness_2/mean
-                  xKey: iterations
-                - yKey: train/episode/rew_tracking_contacts_shaped_vel/mean
-                  xKey: iterations
-                - yKey: train/episode/rew_orientation_control/mean
-                  xKey: iterations
-                - yKey: train/episode/rew_dof_pos/mean
-                  xKey: iterations
-                - yKey: train/episode/command_area_trot/mean
-                  xKey: iterations
-                - yKey: train/episode/max_terrain_height/mean
-                  xKey: iterations
-                - type: video
-                  glob: "videos/*.mp4"
-                - yKey: adaptation_loss/mean
-                  xKey: iterations
-                """, filename=".charts.yml", dedent=True)
     run_env(render=True, headless=False)