From 37b9a3380ea7bdf315e78c1a2b0228594bf4fa8d Mon Sep 17 00:00:00 2001 From: jake Date: Sat, 17 Sep 2022 09:26:44 -0500 Subject: [PATCH] Working training - 00003 learning rate and frame skip --- Run.py | 4 +++- Train.py | 6 +++--- ....tfevents.1663115951.DESKTOP-2TA29VI.6788.0 | Bin 0 -> 204651 bytes ...tfevents.1662841712.LAPTOP-AGKSCH3K.27512.0 | Bin ...tfevents.1662509338.LAPTOP-AGKSCH3K.18916.0 | Bin ...tfevents.1662486193.LAPTOP-AGKSCH3K.13348.0 | Bin 3513 -> 0 bytes ...tfevents.1662950917.LAPTOP-AGKSCH3K.28096.0 | Bin 40 -> 0 bytes ...tfevents.1662500642.LAPTOP-AGKSCH3K.14712.0 | Bin 87 -> 0 bytes ...tfevents.1662501247.LAPTOP-AGKSCH3K.12180.0 | Bin 892 -> 0 bytes ...tfevents.1662603209.LAPTOP-AGKSCH3K.21812.0 | Bin 40 -> 0 bytes ...tfevents.1662639490.LAPTOP-AGKSCH3K.26540.0 | Bin 5026 -> 0 bytes ...tfevents.1662651833.LAPTOP-AGKSCH3K.28392.0 | Bin 1584 -> 0 bytes ...tfevents.1662668897.LAPTOP-AGKSCH3K.16744.0 | Bin 42235 -> 0 bytes ...tfevents.1662751929.LAPTOP-AGKSCH3K.13224.0 | Bin 14 files changed, 6 insertions(+), 4 deletions(-) create mode 100644 board/PPO-00003_1/events.out.tfevents.1663115951.DESKTOP-2TA29VI.6788.0 rename board/{PPO_10 => PPO-0003-skip4}/events.out.tfevents.1662841712.LAPTOP-AGKSCH3K.27512.0 (100%) rename board/{PPO_4 => PPO-0003_1}/events.out.tfevents.1662509338.LAPTOP-AGKSCH3K.18916.0 (100%) delete mode 100644 board/PPO_1/events.out.tfevents.1662486193.LAPTOP-AGKSCH3K.13348.0 delete mode 100644 board/PPO_11/events.out.tfevents.1662950917.LAPTOP-AGKSCH3K.28096.0 delete mode 100644 board/PPO_2/events.out.tfevents.1662500642.LAPTOP-AGKSCH3K.14712.0 delete mode 100644 board/PPO_3/events.out.tfevents.1662501247.LAPTOP-AGKSCH3K.12180.0 delete mode 100644 board/PPO_5/events.out.tfevents.1662603209.LAPTOP-AGKSCH3K.21812.0 delete mode 100644 board/PPO_6/events.out.tfevents.1662639490.LAPTOP-AGKSCH3K.26540.0 delete mode 100644 board/PPO_7/events.out.tfevents.1662651833.LAPTOP-AGKSCH3K.28392.0 delete mode 100644 board/PPO_8/events.out.tfevents.1662668897.LAPTOP-AGKSCH3K.16744.0 rename board/{PPO_9 => TrainAgain}/events.out.tfevents.1662751929.LAPTOP-AGKSCH3K.13224.0 (100%) diff --git a/Run.py b/Run.py index 1b2c331..2e5341f 100644 --- a/Run.py +++ b/Run.py @@ -2,6 +2,7 @@ import gym from RandomAgent import TimeLimitWrapper from stable_baselines3 import PPO +from stable_baselines3.common.atari_wrappers import MaxAndSkipEnv model = PPO.load("tmp/best_model.zip") @@ -11,7 +12,8 @@ def main(): #env = retro.make(game='MegaMan2-Nes') env = retro.make(game='SuperMarioBros-Nes') env = TimeLimitWrapper(env) - + env = MaxAndSkipEnv(env, 4) + obs = env.reset() done = False diff --git a/Train.py b/Train.py index d368779..9d78569 100644 --- a/Train.py +++ b/Train.py @@ -94,11 +94,11 @@ def _init(): # You can choose between `DummyVecEnv` (usually faster) and `SubprocVecEnv` # env = make_vec_env(env_id, n_envs=num_cpu, seed=0, vec_env_cls=SubprocVecEnv) - #model = PPO('CnnPolicy', env, verbose=1, tensorboard_log="./board/") - model = PPO.load("tmp/best_model", env=env) + model = PPO('CnnPolicy', env, verbose=1, tensorboard_log="./board/", learning_rate=0.00003) + #model = PPO.load("tmp/best_model", env=env) print("------------- Start Learning -------------") callback = SaveOnBestTrainingRewardCallback(check_freq=1000, log_dir=log_dir) - model.learn(total_timesteps=5000000, callback=callback) + model.learn(total_timesteps=5000000, callback=callback, tb_log_name="PPO-00003") model.save(env_id) print("------------- Done Learning -------------") env = retro.make(game=env_id) diff --git a/board/PPO-00003_1/events.out.tfevents.1663115951.DESKTOP-2TA29VI.6788.0 b/board/PPO-00003_1/events.out.tfevents.1663115951.DESKTOP-2TA29VI.6788.0 new file mode 100644 index 0000000000000000000000000000000000000000..7d7ce36034cd96acd80bf093d49bed875cafe579 GIT binary patch literal 204651 zcmb5%d0b5U{|E31(P9Y|$x_x7g;1E8qvni#$xfCcC8U&+$eQd+p``5D*APN9iOP~K 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