From 62a94276e9c885aea847962a21d4914822210058 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Wed, 15 Mar 2023 08:57:28 +0000 Subject: [PATCH 01/24] Updated version from 2.2.6 to 2.2.7 --- sinergym/version.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/sinergym/version.txt b/sinergym/version.txt index bda8fbec15..5bc1cc43d4 100644 --- a/sinergym/version.txt +++ b/sinergym/version.txt @@ -1 +1 @@ -2.2.6 +2.2.7 From 7282d1eea0959b538969b8a7fd79a59bc5665320 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Wed, 15 Mar 2023 09:40:26 +0000 Subject: [PATCH 02/24] Added wandb extra dependency --- setup.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/setup.py b/setup.py index 5c58562067..f99f00552c 100644 --- a/setup.py +++ b/setup.py @@ -24,6 +24,7 @@ 'extras': [ 'matplotlib', # visualization # 'stable-baselines3', # DRL with pytorch + 'wandb', 'mlflow==1.28.0', # tracking ML experiments 'tensorflow==2.9.1', 'tensorboard_plugin_profile==2.8.0', # Training logger @@ -54,7 +55,8 @@ # 'stable-baselines3', 'mlflow==1.28.0', 'tensorflow==2.9.1', - 'tensorboard_plugin_profile==2.8.0' + 'tensorboard_plugin_profile==2.8.0', + 'wandb' ], 'doc': [ 'sphinx', From cf97a7b0021ad1b5860688b61891d242500dc83d Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Wed, 15 Mar 2023 09:41:53 +0000 Subject: [PATCH 03/24] Deleted mlflow code and included wandb init and params log in DRL_battery.py --- scripts/DRL_battery.py | 506 +++++++++++++++++++---------------------- 1 file changed, 235 insertions(+), 271 deletions(-) diff --git a/scripts/DRL_battery.py b/scripts/DRL_battery.py index 7ad67b4e58..080ca55d60 100644 --- a/scripts/DRL_battery.py +++ b/scripts/DRL_battery.py @@ -15,7 +15,7 @@ from stable_baselines3.common.vec_env import DummyVecEnv import sinergym import sinergym.utils.gcloud as gcloud -from sinergym.utils.callbacks import LoggerCallback, LoggerEvalCallback +from sinergym.utils.callbacks import * from sinergym.utils.constants import * from sinergym.utils.rewards import * from sinergym.utils.wrappers import * @@ -56,304 +56,268 @@ name += '_' + experiment_date # ---------------------------------------------------------------------------- # -# Check if MLFLOW_TRACKING_URI is defined # +# WandB registration # # ---------------------------------------------------------------------------- # -mlflow_tracking_uri = os.environ.get('MLFLOW_TRACKING_URI') -if mlflow_tracking_uri is not None: - # Check ping to server - mlflow_ip = mlflow_tracking_uri.split('/')[-1].split(':')[0] - # If server is not valid, setting default local path to mlflow - response = os.system("ping -c 1 " + mlflow_ip) - if response != 0: - mlflow.set_tracking_uri('file://' + os.getcwd() + '/mlruns') -# MLflow track -with mlflow.start_run(run_name=name): - # Log experiment params - # sinergym and python versions - mlflow.log_param('sinergym-version', sinergym.__version__) - mlflow.log_param('python-version', sys.version) - # Main - mlflow.log_param('environment', conf['environment']) - mlflow.log_param('episodes', conf['episodes']) - mlflow.log_param('algorithm', conf['algorithm']['name']) - # Environment parameters overwriten - mlflow.log_params(conf.get('env_params')) - # Optional - mlflow.log_param('tensorboard', conf.get('tensorboard', False)) - mlflow.log_param( - 'log-interval', - conf['algorithm'].get( - 'log_interval', - False)) - mlflow.log_param('seed', conf.get('seed', False)) - if conf.get('cloud', False): - mlflow.log_param( - 'remote-store', - conf['cloud'].get( - 'remote_store', - False)) - if conf.get('wrappers'): - for key in conf['wrappers']: - mlflow.log_param(key, True) - mlflow.log_param('evaluation', bool(conf.get('evaluation', False))) - if conf.get('evaluation'): - mlflow.log_param( - 'evaluation-frequency', - conf['evaluation'].get('eval_freq')) - mlflow.log_param( - 'evaluation-length', - conf['evaluation'].get('eval_length')) - # algorithm params - mlflow.log_params(conf['algorithm'].get('parameters')) +# Create wandb.config object in order to log all experiment params +wandb_params = { + 'sinergym-version': sinergym.__version__, + 'python-version': sys.version +} +wandb_params.update(conf) - # --------------------- Overwrite environment parameters --------------------- # - env_params = {} - # Transform required str's into Callables - if conf.get('env_params'): - if conf['env_params'].get('reward'): - conf['env_params']['reward'] = eval(conf['env_params']['reward']) - if conf['env_params'].get('observation_space'): - conf['env_params']['observation_space'] = eval( - conf['env_params']['observation_space']) - if conf['env_params'].get('action_space'): - conf['env_params']['observation_space'] = eval( - conf['env_params']['action_space']) +# Init wandb entry +wandb.init( + project="sinergym", + entity="ugr-sail", + name=name, + config=wandb_params +) - env_params = conf['env_params'] +# --------------------- Overwrite environment parameters --------------------- # +env_params = {} +# Transform required str's into Callables +if conf.get('env_params'): + if conf['env_params'].get('reward'): + conf['env_params']['reward'] = eval(conf['env_params']['reward']) + if conf['env_params'].get('observation_space'): + conf['env_params']['observation_space'] = eval( + conf['env_params']['observation_space']) + if conf['env_params'].get('action_space'): + conf['env_params']['observation_space'] = eval( + conf['env_params']['action_space']) - # ---------------------------------------------------------------------------- # - # Environment construction # - # ---------------------------------------------------------------------------- # - env = gym.make( + env_params = conf['env_params'] + +# ---------------------------------------------------------------------------- # +# Environment construction # +# ---------------------------------------------------------------------------- # +env = gym.make( + conf['environment'], + ** env_params) + +# env for evaluation if is enabled +eval_env = None +if conf.get('evaluation'): + eval_env = gym.make( conf['environment'], ** env_params) - # env for evaluation if is enabled - eval_env = None - if conf.get('evaluation'): - eval_env = gym.make( - conf['environment'], - ** env_params) - - # ---------------------------------------------------------------------------- # - # Wrappers # - # ---------------------------------------------------------------------------- # - if conf.get('wrappers'): - for key, parameters in conf['wrappers'].items(): - wrapper_class = eval(key) - for name, value in parameters.items(): - # parse str parameters to sinergym Callable or Objects if it is - # required - if isinstance(value, str): - if 'sinergym.' in value: - parameters[name] = eval(value) - env = wrapper_class(env=env, ** parameters) - if eval_env is not None: - eval_env = wrapper_class(env=eval_env, ** parameters) +# ---------------------------------------------------------------------------- # +# Wrappers # +# ---------------------------------------------------------------------------- # +if conf.get('wrappers'): + for key, parameters in conf['wrappers'].items(): + wrapper_class = eval(key) + for name, value in parameters.items(): + # parse str parameters to sinergym Callable or Objects if it is + # required + if isinstance(value, str): + if 'sinergym.' in value: + parameters[name] = eval(value) + env = wrapper_class(env=env, ** parameters) + if eval_env is not None: + eval_env = wrapper_class(env=eval_env, ** parameters) - # ---------------------------------------------------------------------------- # - # Defining model (algorithm) # - # ---------------------------------------------------------------------------- # - algorithm_name = conf['algorithm']['name'] - algorithm_parameters = conf['algorithm']['parameters'] - if conf.get('model') is None: +# ---------------------------------------------------------------------------- # +# Defining model (algorithm) # +# ---------------------------------------------------------------------------- # +algorithm_name = conf['algorithm']['name'] +algorithm_parameters = conf['algorithm']['parameters'] +if conf.get('model') is None: - # --------------------------------------------------------# - # DQN # - # --------------------------------------------------------# - if algorithm_name == 'SB3-DQN': + # --------------------------------------------------------# + # DQN # + # --------------------------------------------------------# + if algorithm_name == 'SB3-DQN': - model = DQN(env=env, - seed=conf.get('seed', None), - tensorboard_log=conf.get('tensorboard', None), - ** algorithm_parameters) - # --------------------------------------------------------# - # DDPG # - # --------------------------------------------------------# - elif algorithm_name == 'SB3-DDPG': - model = DDPG(env=env, - seed=conf.get('seed', None), - tensorboard_log=conf.get('tensorboard', None), - ** algorithm_parameters) - # --------------------------------------------------------# - # A2C # - # --------------------------------------------------------# - elif algorithm_name == 'SB3-A2C': - model = A2C(env=env, - seed=conf.get('seed', None), - tensorboard_log=conf.get('tensorboard', None), - ** algorithm_parameters) - # --------------------------------------------------------# - # PPO # - # --------------------------------------------------------# - elif algorithm_name == 'SB3-PPO': - model = PPO(env=env, - seed=conf.get('seed', None), - tensorboard_log=conf.get('tensorboard', None), - ** algorithm_parameters) - # --------------------------------------------------------# - # SAC # - # --------------------------------------------------------# - elif algorithm_name == 'SB3-SAC': - model = SAC(env=env, - seed=conf.get('seed', None), - tensorboard_log=conf.get('tensorboard', None), - ** algorithm_parameters) - # --------------------------------------------------------# - # TD3 # - # --------------------------------------------------------# - elif algorithm_name == 'SB3-TD3': - model = TD3(env=env, - seed=conf.get('seed', None), - tensorboard_log=conf.get('tensorboard', None), - ** algorithm_parameters) - # --------------------------------------------------------# - # Error # - # --------------------------------------------------------# - else: - raise RuntimeError( - F'Algorithm specified [{algorithm_name} ] is not registered.') + model = DQN(env=env, + seed=conf.get('seed', None), + tensorboard_log=conf.get('tensorboard', None), + ** algorithm_parameters) + # --------------------------------------------------------# + # DDPG # + # --------------------------------------------------------# + elif algorithm_name == 'SB3-DDPG': + model = DDPG(env=env, + seed=conf.get('seed', None), + tensorboard_log=conf.get('tensorboard', None), + ** algorithm_parameters) + # --------------------------------------------------------# + # A2C # + # --------------------------------------------------------# + elif algorithm_name == 'SB3-A2C': + model = A2C(env=env, + seed=conf.get('seed', None), + tensorboard_log=conf.get('tensorboard', None), + ** algorithm_parameters) + # --------------------------------------------------------# + # PPO # + # --------------------------------------------------------# + elif algorithm_name == 'SB3-PPO': + model = PPO(env=env, + seed=conf.get('seed', None), + tensorboard_log=conf.get('tensorboard', None), + ** algorithm_parameters) + # --------------------------------------------------------# + # SAC # + # --------------------------------------------------------# + elif algorithm_name == 'SB3-SAC': + model = SAC(env=env, + seed=conf.get('seed', None), + tensorboard_log=conf.get('tensorboard', None), + ** algorithm_parameters) + # --------------------------------------------------------# + # TD3 # + # --------------------------------------------------------# + elif algorithm_name == 'SB3-TD3': + model = TD3(env=env, + seed=conf.get('seed', None), + tensorboard_log=conf.get('tensorboard', None), + ** algorithm_parameters) + # --------------------------------------------------------# + # Error # + # --------------------------------------------------------# + else: + raise RuntimeError( + F'Algorithm specified [{algorithm_name} ] is not registered.') +else: + model_path = '' + if 'gs://' in conf['model']: + # Download from given bucket (gcloud configured with privileges) + client = gcloud.init_storage_client() + bucket_name = conf['model'].split('/')[2] + model_path = conf['model'].split(bucket_name + '/')[-1] + gcloud.read_from_bucket(client, bucket_name, model_path) + model_path = './' + model_path else: - model_path = '' - if 'gs://' in conf['model']: - # Download from given bucket (gcloud configured with privileges) - client = gcloud.init_storage_client() - bucket_name = conf['model'].split('/')[2] - model_path = conf['model'].split(bucket_name + '/')[-1] - gcloud.read_from_bucket(client, bucket_name, model_path) - model_path = './' + model_path - else: - model_path = conf['model'] + model_path = conf['model'] - model = None - if algorithm_name == 'SB3-DQN': - model = DQN.load( - model_path, tensorboard_log=conf.get( - 'tensorboard', None)) - elif algorithm_name == 'SB3-DDPG': - model = DDPG.load( - model_path, tensorboard_log=conf.get( - 'tensorboard', None)) - elif algorithm_name == 'SB3-A2C': - model = A2C.load( - model_path, tensorboard_log=conf.get( - 'tensorboard', None)) - elif algorithm_name == 'SB3-PPO': - model = PPO.load( - model_path, tensorboard_log=conf.get( - 'tensorboard', None)) - elif algorithm_name == 'SB3-SAC': - model = SAC.load( - model_path, tensorboard_log=conf.get( - 'tensorboard', None)) - elif algorithm_name == 'SB3-TD3': - model = TD3.load( - model_path, tensorboard_log=conf.get( - 'tensorboard', None)) - else: - raise RuntimeError('Algorithm specified is not registered.') + model = None + if algorithm_name == 'SB3-DQN': + model = DQN.load( + model_path, tensorboard_log=conf.get( + 'tensorboard', None)) + elif algorithm_name == 'SB3-DDPG': + model = DDPG.load( + model_path, tensorboard_log=conf.get( + 'tensorboard', None)) + elif algorithm_name == 'SB3-A2C': + model = A2C.load( + model_path, tensorboard_log=conf.get( + 'tensorboard', None)) + elif algorithm_name == 'SB3-PPO': + model = PPO.load( + model_path, tensorboard_log=conf.get( + 'tensorboard', None)) + elif algorithm_name == 'SB3-SAC': + model = SAC.load( + model_path, tensorboard_log=conf.get( + 'tensorboard', None)) + elif algorithm_name == 'SB3-TD3': + model = TD3.load( + model_path, tensorboard_log=conf.get( + 'tensorboard', None)) + else: + raise RuntimeError('Algorithm specified is not registered.') - model.set_env(env) + model.set_env(env) - # ---------------------------------------------------------------------------- # - # Calculating total training timesteps based on number of episodes # - # ---------------------------------------------------------------------------- # - n_timesteps_episode = env.simulator._eplus_one_epi_len / \ - env.simulator._eplus_run_stepsize - timesteps = conf['episodes'] * n_timesteps_episode - 1 +# ---------------------------------------------------------------------------- # +# Calculating total training timesteps based on number of episodes # +# ---------------------------------------------------------------------------- # +n_timesteps_episode = env.simulator._eplus_one_epi_len / \ + env.simulator._eplus_run_stepsize +timesteps = conf['episodes'] * n_timesteps_episode - 1 - # ---------------------------------------------------------------------------- # - # CALLBACKS # - # ---------------------------------------------------------------------------- # - callbacks = [] +# ---------------------------------------------------------------------------- # +# CALLBACKS # +# ---------------------------------------------------------------------------- # +callbacks = [] - # Set up Evaluation and saving best model - if conf.get('evaluation'): - eval_callback = LoggerEvalCallback( - eval_env, - best_model_save_path='best_model/' + name, - log_path='best_model/' + name + '/', - eval_freq=n_timesteps_episode * - conf['evaluation']['eval_freq'], - deterministic=True, - render=False, - n_eval_episodes=conf['evaluation']['eval_length']) - callbacks.append(eval_callback) +# Set up Evaluation and saving best model +if conf.get('evaluation'): + eval_callback = LoggerEvalCallback( + eval_env, + best_model_save_path='best_model/' + name, + log_path='best_model/' + name + '/', + eval_freq=n_timesteps_episode * + conf['evaluation']['eval_freq'], + deterministic=True, + render=False, + n_eval_episodes=conf['evaluation']['eval_length']) + callbacks.append(eval_callback) - # Set up tensorboard logger - if conf.get('tensorboard'): - log_callback = LoggerCallback() - callbacks.append(log_callback) - # lets change default dir for TensorboardFormatLogger only - tb_path = conf['tensorboard'] + '/' + name - new_logger = configure(tb_path, ["tensorboard"]) - model.set_logger(new_logger) +# Set up tensorboard logger +if conf.get('tensorboard'): + log_callback = LoggerCallback() + callbacks.append(log_callback) + # lets change default dir for TensorboardFormatLogger only + tb_path = conf['tensorboard'] + '/' + name + new_logger = configure(tb_path, ["tensorboard"]) + model.set_logger(new_logger) - callback = CallbackList(callbacks) +callback = CallbackList(callbacks) - # ---------------------------------------------------------------------------- # - # TRAINING # - # ---------------------------------------------------------------------------- # - model.learn( - total_timesteps=timesteps, - callback=callback, - log_interval=conf['algorithm']['log_interval']) - model.save(env.simulator._env_working_dir_parent + '/' + name) +# ---------------------------------------------------------------------------- # +# TRAINING # +# ---------------------------------------------------------------------------- # +model.learn( + total_timesteps=timesteps, + callback=callback, + log_interval=conf['algorithm']['log_interval']) +model.save(env.simulator._env_working_dir_parent + '/' + name) - # If the algorithm doesn't reset or close the environment, this script will do it in - # order to correctly log all the simulation data (Energyplus + Sinergym - # logs) - if env.simulator._episode_existed: - env.close() +# If the algorithm doesn't reset or close the environment, this script will do it in +# order to correctly log all the simulation data (Energyplus + Sinergym +# logs) +if env.simulator._episode_existed: + env.close() - # ---------------------------------------------------------------------------- # - # Mlflow artifacts storege and Google Cloud Bucket Storage # - # ---------------------------------------------------------------------------- # - if conf.get('cloud'): - if conf['cloud'].get('remote_store'): - # Initiate Google Cloud client - client = gcloud.init_storage_client() - # Code for send output and tensorboard to common resource here. +# ---------------------------------------------------------------------------- # +# Mlflow artifacts storege and Google Cloud Bucket Storage # +# ---------------------------------------------------------------------------- # +if conf.get('cloud'): + if conf['cloud'].get('remote_store'): + # Initiate Google Cloud client + client = gcloud.init_storage_client() + # Code for send output and tensorboard to common resource here. + gcloud.upload_to_bucket( + client, + src_path=env.simulator._env_working_dir_parent, + dest_bucket_name=conf['cloud']['remote_store'], + dest_path=name) + # Code for send output and tensorboard to mlflow artifacts. + mlflow.log_artifacts( + local_dir=env.simulator._env_working_dir_parent, + artifact_path=name) + if conf.get('evaluation'): gcloud.upload_to_bucket( client, - src_path=env.simulator._env_working_dir_parent, + src_path='best_model/' + name + '/', dest_bucket_name=conf['cloud']['remote_store'], - dest_path=name) - # Code for send output and tensorboard to mlflow artifacts. + dest_path='best_model/' + name + '/') mlflow.log_artifacts( - local_dir=env.simulator._env_working_dir_parent, - artifact_path=name) - if conf.get('evaluation'): - gcloud.upload_to_bucket( - client, - src_path='best_model/' + name + '/', - dest_bucket_name=conf['cloud']['remote_store'], - dest_path='best_model/' + name + '/') - mlflow.log_artifacts( - local_dir='best_model/' + name, - artifact_path='best_model/' + name) - # If tensorboard is active (in local) we should send to mlflow - if conf.get('tensorboard') and 'gs://' + \ - conf['cloud']['remote_store'] not in conf.get('tensorboard'): - gcloud.upload_to_bucket( - client, - src_path=conf['tensorboard'] + '/' + name + '/', - dest_bucket_name=conf['cloud']['remote_store'], - dest_path=os.path.abspath(conf['tensorboard']).split('/')[-1] + '/' + name + '/') - mlflow.log_artifacts( - local_dir=conf['tensorboard'] + '/' + name, - artifact_path=os.path.abspath(conf['tensorboard']).split('/')[-1] + '/' + name) - - # gcloud.upload_to_bucket( - # client, - # src_path='mlruns/', - # dest_bucket_name=conf['cloud']['remote_store'], - # dest_path='mlruns/') + local_dir='best_model/' + name, + artifact_path='best_model/' + name) + # If tensorboard is active (in local) we should send to mlflow + if conf.get('tensorboard') and 'gs://' + \ + conf['cloud']['remote_store'] not in conf.get('tensorboard'): + gcloud.upload_to_bucket( + client, + src_path=conf['tensorboard'] + '/' + name + '/', + dest_bucket_name=conf['cloud']['remote_store'], + dest_path=os.path.abspath(conf['tensorboard']).split('/')[-1] + '/' + name + '/') + mlflow.log_artifacts( + local_dir=conf['tensorboard'] + '/' + name, + artifact_path=os.path.abspath(conf['tensorboard']).split('/')[-1] + '/' + name) - # End mlflow run - mlflow.end_run() + # gcloud.upload_to_bucket( + # client, + # src_path='mlruns/', + # dest_bucket_name=conf['cloud']['remote_store'], + # dest_path='mlruns/') # ---------------------------------------------------------------------------- # # Autodelete option if is a cloud resource # From 20907d53450df40a50b2bdac2e7084e853646446 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Wed, 15 Mar 2023 09:52:34 +0000 Subject: [PATCH 04/24] Deleted tensorboard_log in SB3 models and mlflow artifact stores in DRL_battery.py --- scripts/DRL_battery.py | 49 ++++++------------------------------------ 1 file changed, 6 insertions(+), 43 deletions(-) diff --git a/scripts/DRL_battery.py b/scripts/DRL_battery.py index 080ca55d60..f2a89ac8a5 100644 --- a/scripts/DRL_battery.py +++ b/scripts/DRL_battery.py @@ -133,7 +133,6 @@ model = DQN(env=env, seed=conf.get('seed', None), - tensorboard_log=conf.get('tensorboard', None), ** algorithm_parameters) # --------------------------------------------------------# # DDPG # @@ -141,7 +140,6 @@ elif algorithm_name == 'SB3-DDPG': model = DDPG(env=env, seed=conf.get('seed', None), - tensorboard_log=conf.get('tensorboard', None), ** algorithm_parameters) # --------------------------------------------------------# # A2C # @@ -149,7 +147,6 @@ elif algorithm_name == 'SB3-A2C': model = A2C(env=env, seed=conf.get('seed', None), - tensorboard_log=conf.get('tensorboard', None), ** algorithm_parameters) # --------------------------------------------------------# # PPO # @@ -157,7 +154,6 @@ elif algorithm_name == 'SB3-PPO': model = PPO(env=env, seed=conf.get('seed', None), - tensorboard_log=conf.get('tensorboard', None), ** algorithm_parameters) # --------------------------------------------------------# # SAC # @@ -165,7 +161,6 @@ elif algorithm_name == 'SB3-SAC': model = SAC(env=env, seed=conf.get('seed', None), - tensorboard_log=conf.get('tensorboard', None), ** algorithm_parameters) # --------------------------------------------------------# # TD3 # @@ -173,7 +168,6 @@ elif algorithm_name == 'SB3-TD3': model = TD3(env=env, seed=conf.get('seed', None), - tensorboard_log=conf.get('tensorboard', None), ** algorithm_parameters) # --------------------------------------------------------# # Error # @@ -197,28 +191,22 @@ model = None if algorithm_name == 'SB3-DQN': model = DQN.load( - model_path, tensorboard_log=conf.get( - 'tensorboard', None)) + model_path) elif algorithm_name == 'SB3-DDPG': model = DDPG.load( - model_path, tensorboard_log=conf.get( - 'tensorboard', None)) + model_path) elif algorithm_name == 'SB3-A2C': model = A2C.load( - model_path, tensorboard_log=conf.get( - 'tensorboard', None)) + model_path) elif algorithm_name == 'SB3-PPO': model = PPO.load( - model_path, tensorboard_log=conf.get( - 'tensorboard', None)) + model_path) elif algorithm_name == 'SB3-SAC': model = SAC.load( - model_path, tensorboard_log=conf.get( - 'tensorboard', None)) + model_path) elif algorithm_name == 'SB3-TD3': model = TD3.load( - model_path, tensorboard_log=conf.get( - 'tensorboard', None)) + model_path) else: raise RuntimeError('Algorithm specified is not registered.') @@ -288,37 +276,12 @@ src_path=env.simulator._env_working_dir_parent, dest_bucket_name=conf['cloud']['remote_store'], dest_path=name) - # Code for send output and tensorboard to mlflow artifacts. - mlflow.log_artifacts( - local_dir=env.simulator._env_working_dir_parent, - artifact_path=name) if conf.get('evaluation'): gcloud.upload_to_bucket( client, src_path='best_model/' + name + '/', dest_bucket_name=conf['cloud']['remote_store'], dest_path='best_model/' + name + '/') - mlflow.log_artifacts( - local_dir='best_model/' + name, - artifact_path='best_model/' + name) - # If tensorboard is active (in local) we should send to mlflow - if conf.get('tensorboard') and 'gs://' + \ - conf['cloud']['remote_store'] not in conf.get('tensorboard'): - gcloud.upload_to_bucket( - client, - src_path=conf['tensorboard'] + '/' + name + '/', - dest_bucket_name=conf['cloud']['remote_store'], - dest_path=os.path.abspath(conf['tensorboard']).split('/')[-1] + '/' + name + '/') - mlflow.log_artifacts( - local_dir=conf['tensorboard'] + '/' + name, - artifact_path=os.path.abspath(conf['tensorboard']).split('/')[-1] + '/' + name) - - # gcloud.upload_to_bucket( - # client, - # src_path='mlruns/', - # dest_bucket_name=conf['cloud']['remote_store'], - # dest_path='mlruns/') - # ---------------------------------------------------------------------------- # # Autodelete option if is a cloud resource # # ---------------------------------------------------------------------------- # From 9b5bde7eb2459f3086ad0492d47f8e3d337dbd5f Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Wed, 15 Mar 2023 13:20:00 +0000 Subject: [PATCH 05/24] Deleted mlflow and tensorboard extra dependencies --- setup.py | 6 ------ 1 file changed, 6 deletions(-) diff --git a/setup.py b/setup.py index f99f00552c..049be6143f 100644 --- a/setup.py +++ b/setup.py @@ -25,9 +25,6 @@ 'matplotlib', # visualization # 'stable-baselines3', # DRL with pytorch 'wandb', - 'mlflow==1.28.0', # tracking ML experiments - 'tensorflow==2.9.1', - 'tensorboard_plugin_profile==2.8.0', # Training logger 'pytest', 'pytest-cov', 'pytest-xdist', # Unit test repository @@ -53,9 +50,6 @@ ], 'DRL': [ # 'stable-baselines3', - 'mlflow==1.28.0', - 'tensorflow==2.9.1', - 'tensorboard_plugin_profile==2.8.0', 'wandb' ], 'doc': [ From 40ee707e6a63fbc9a40c2cc096f0166f7473cf3e Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Wed, 15 Mar 2023 13:20:55 +0000 Subject: [PATCH 06/24] Deleted tensorboard element and added wandb in JSON example for DRL_battery.py --- scripts/DRL_battery_example.json | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/scripts/DRL_battery_example.json b/scripts/DRL_battery_example.json index 50dd24033b..c8bda0aa61 100644 --- a/scripts/DRL_battery_example.json +++ b/scripts/DRL_battery_example.json @@ -54,5 +54,9 @@ "eval_freq": 2, "eval_length": 1 }, - "tensorboard": "./tensorboard_log/" + "wandb": { + "project": "sinergym", + "entity": "ugr-sail", + "save_code": true + } } \ No newline at end of file From 19347088e2ebbcc8d43a4d5b9f2513600a6298a0 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Wed, 15 Mar 2023 13:21:51 +0000 Subject: [PATCH 07/24] Added WandBOutputFormar for callback loggers in SB3 --- sinergym/utils/logger.py | 28 +++++++++++++++++++++++++++- 1 file changed, 27 insertions(+), 1 deletion(-) diff --git a/sinergym/utils/logger.py b/sinergym/utils/logger.py index 7d182ed0d3..3c4c651e46 100644 --- a/sinergym/utils/logger.py +++ b/sinergym/utils/logger.py @@ -4,7 +4,9 @@ import logging import os import sys -from typing import Any, Dict, List, Optional, Union +from typing import Any, Dict, List, Optional, Union, Tuple +from stable_baselines3.common.logger import Logger, KVWriter +import wandb import numpy as np @@ -300,3 +302,27 @@ def deactivate_flag(self) -> None: """Deactivate Sinergym CSV logger """ self.flag = False + + +class WandBOutputFormat(KVWriter): + """ + Dumps key/value pairs onto WandB. This class is based on SB3 used in logger callback + """ + + def write( + self, + key_values: Dict[str, Any], + key_excluded: Dict[str, Union[str, Tuple[str, ...]]], + step: int = 0, + ) -> None: + + for (key, value), (_, excluded) in zip( + sorted(key_values.items()), sorted(key_excluded.items()) + ): + + if excluded is not None and "wandb" in excluded: + continue + + if isinstance(value, np.ScalarType): + if not isinstance(value, str): + wandb.log({key: value}, step=step) From dd3b5f4b45c1cd3c3c40737ab5d1835a0f1d4f38 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Thu, 16 Mar 2023 10:07:43 +0000 Subject: [PATCH 08/24] Added wandb folder to gitignore --- .gitignore | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index 7133d3c0ff..042aaee589 100644 --- a/.gitignore +++ b/.gitignore @@ -49,4 +49,7 @@ dist/ #coverage .coverage codecov -coverage.xml \ No newline at end of file +coverage.xml + +#wandb +wandb/ \ No newline at end of file From 899b1720510e2df9cb80d41c947f18b243ec518a Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Thu, 16 Mar 2023 11:30:07 +0000 Subject: [PATCH 09/24] Fixed log interval parameter in DRL_battery.py JSON example and fixed wandb section --- scripts/DRL_battery_example.json | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/scripts/DRL_battery_example.json b/scripts/DRL_battery_example.json index c8bda0aa61..f3e8330463 100644 --- a/scripts/DRL_battery_example.json +++ b/scripts/DRL_battery_example.json @@ -4,7 +4,7 @@ "episodes": 5, "algorithm": { "name": "SB3-PPO", - "log_interval": 100, + "log_interval": 1, "parameters": { "policy": "MlpPolicy", "verbose": 1, @@ -56,7 +56,6 @@ }, "wandb": { "project": "sinergym", - "entity": "ugr-sail", - "save_code": true + "entity": "alex_ugr" } } \ No newline at end of file From 626cd1681741a1894cb7a18eeef3223616a1b534 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Thu, 16 Mar 2023 11:33:18 +0000 Subject: [PATCH 10/24] DRL_battery.py: Added Monitor wrapper to env and wandb artifacts --- scripts/DRL_battery.py | 100 +++++++++++++++++++++++++---------------- 1 file changed, 61 insertions(+), 39 deletions(-) diff --git a/scripts/DRL_battery.py b/scripts/DRL_battery.py index f2a89ac8a5..e92eaf4b1e 100644 --- a/scripts/DRL_battery.py +++ b/scripts/DRL_battery.py @@ -1,25 +1,24 @@ import argparse -import sys -import os import json +import os +import sys from datetime import datetime import gymnasium as gym -import mlflow import numpy as np -import tensorboard -from stable_baselines3 import * -from stable_baselines3.common.callbacks import CallbackList -from stable_baselines3.common.logger import configure -from stable_baselines3.common.noise import NormalActionNoise -from stable_baselines3.common.vec_env import DummyVecEnv import sinergym import sinergym.utils.gcloud as gcloud from sinergym.utils.callbacks import * from sinergym.utils.constants import * +from sinergym.utils.logger import CSVLogger, WandBOutputFormat from sinergym.utils.rewards import * from sinergym.utils.wrappers import * -from sinergym.utils.logger import * +from stable_baselines3 import * +from stable_baselines3.common.callbacks import CallbackList +from stable_baselines3.common.logger import HumanOutputFormat, Logger +from stable_baselines3.common.monitor import Monitor + +import wandb # ---------------------------------------------------------------------------- # # Parameters definition # @@ -59,20 +58,22 @@ # WandB registration # # ---------------------------------------------------------------------------- # -# Create wandb.config object in order to log all experiment params -wandb_params = { - 'sinergym-version': sinergym.__version__, - 'python-version': sys.version -} -wandb_params.update(conf) - -# Init wandb entry -wandb.init( - project="sinergym", - entity="ugr-sail", - name=name, - config=wandb_params -) +if conf.get('wandb'): + # Create wandb.config object in order to log all experiment params + experiment_params = { + 'sinergym-version': sinergym.__version__, + 'python-version': sys.version + } + experiment_params.update(conf) + + # Get wandb init params + wandb_params = conf['wandb'] + # Init wandb entry + run = wandb.init( + name=name + '_' + wandb.util.generate_id(), + config=experiment_params, + ** wandb_params + ) # --------------------- Overwrite environment parameters --------------------- # env_params = {} @@ -95,6 +96,7 @@ env = gym.make( conf['environment'], ** env_params) +env = Monitor(env) # env for evaluation if is enabled eval_env = None @@ -102,6 +104,7 @@ eval_env = gym.make( conf['environment'], ** env_params) + eval_env = Monitor(eval_env) # ---------------------------------------------------------------------------- # # Wrappers # @@ -228,23 +231,30 @@ if conf.get('evaluation'): eval_callback = LoggerEvalCallback( eval_env, - best_model_save_path='best_model/' + name, + best_model_save_path='best_model/' + + name, log_path='best_model/' + name + '/', - eval_freq=n_timesteps_episode * - conf['evaluation']['eval_freq'], + eval_freq=n_timesteps_episode * conf['evaluation']['eval_freq'], deterministic=True, render=False, n_eval_episodes=conf['evaluation']['eval_length']) callbacks.append(eval_callback) # Set up tensorboard logger -if conf.get('tensorboard'): +if conf.get('wandb'): + # wandb logger and setting in SB3 + logger = Logger( + folder=None, + output_formats=[ + HumanOutputFormat( + sys.stdout, + max_length=120), + WandBOutputFormat()]) + model.set_logger(logger) + # Append callback log_callback = LoggerCallback() callbacks.append(log_callback) - # lets change default dir for TensorboardFormatLogger only - tb_path = conf['tensorboard'] + '/' + name - new_logger = configure(tb_path, ["tensorboard"]) - model.set_logger(new_logger) + callback = CallbackList(callbacks) @@ -264,7 +274,20 @@ env.close() # ---------------------------------------------------------------------------- # -# Mlflow artifacts storege and Google Cloud Bucket Storage # +# Wandb artifact log # +# ---------------------------------------------------------------------------- # + +if conf.get('wandb'): + artifact = wandb.Artifact('train', 'model') + artifact.add_dir(env.simulator._env_working_dir_parent) + artifact.add_dir('./best_model/') + run.log_artifact(artifact) + +# wandb has finished +run.finish() + +# ---------------------------------------------------------------------------- # +# Google Cloud Bucket Storage # # ---------------------------------------------------------------------------- # if conf.get('cloud'): if conf['cloud'].get('remote_store'): @@ -285,9 +308,8 @@ # ---------------------------------------------------------------------------- # # Autodelete option if is a cloud resource # # ---------------------------------------------------------------------------- # - if conf.get('cloud'): - if conf['cloud'].get( - 'remote_store') and conf['cloud'].get('auto_delete'): - token = gcloud.get_service_account_token() - gcloud.delete_instance_MIG_from_container( - conf['cloud']['group_name'], token) + if conf['cloud'].get( + 'remote_store') and conf['cloud'].get('auto_delete'): + token = gcloud.get_service_account_token() + gcloud.delete_instance_MIG_from_container( + conf['cloud']['group_name'], token) From d605df5b5b26af1fa68e2b46319ebc849b59be1e Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Thu, 16 Mar 2023 13:42:44 +0000 Subject: [PATCH 11/24] Updated docs source modules --- ...inergym.utils.logger.WandBOutputFormat.rst | 25 +++++++++++++++++++ .../pages/modules/sinergym.utils.logger.rst | 3 ++- .../sinergym.utils.wrappers.LoggerWrapper.rst | 3 ++- ...ym.utils.wrappers.MultiObjectiveReward.rst | 3 ++- ...inergym.utils.wrappers.MultiObsWrapper.rst | 3 ++- ...ym.utils.wrappers.NormalizeObservation.rst | 3 ++- ...orageSmoothingActionConstraintsWrapper.rst | 3 ++- 7 files changed, 37 insertions(+), 6 deletions(-) create mode 100644 docs/source/pages/modules/sinergym.utils.logger.WandBOutputFormat.rst diff --git a/docs/source/pages/modules/sinergym.utils.logger.WandBOutputFormat.rst b/docs/source/pages/modules/sinergym.utils.logger.WandBOutputFormat.rst new file mode 100644 index 0000000000..44904d29c5 --- /dev/null +++ b/docs/source/pages/modules/sinergym.utils.logger.WandBOutputFormat.rst @@ -0,0 +1,25 @@ +sinergym.utils.logger.WandBOutputFormat +======================================= + +.. currentmodule:: sinergym.utils.logger + +.. autoclass:: WandBOutputFormat + :members: + :undoc-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~WandBOutputFormat.__init__ + ~WandBOutputFormat.write + + + + + + \ No newline at end of file diff --git a/docs/source/pages/modules/sinergym.utils.logger.rst b/docs/source/pages/modules/sinergym.utils.logger.rst index 96f545fce5..637f4e99cb 100644 --- a/docs/source/pages/modules/sinergym.utils.logger.rst +++ b/docs/source/pages/modules/sinergym.utils.logger.rst @@ -1,4 +1,4 @@ -sinergym.utils.logger +sinergym.utils.logger ===================== .. automodule:: sinergym.utils.logger @@ -21,6 +21,7 @@ sinergym.utils.logger CSVLogger Logger + WandBOutputFormat diff --git a/docs/source/pages/modules/sinergym.utils.wrappers.LoggerWrapper.rst b/docs/source/pages/modules/sinergym.utils.wrappers.LoggerWrapper.rst index 7dcb08da12..428da28bbe 100644 --- a/docs/source/pages/modules/sinergym.utils.wrappers.LoggerWrapper.rst +++ b/docs/source/pages/modules/sinergym.utils.wrappers.LoggerWrapper.rst @@ -1,4 +1,4 @@ -sinergym.utils.wrappers.LoggerWrapper +sinergym.utils.wrappers.LoggerWrapper ===================================== .. currentmodule:: sinergym.utils.wrappers @@ -23,6 +23,7 @@ sinergym.utils.wrappers.LoggerWrapper ~LoggerWrapper.render ~LoggerWrapper.reset ~LoggerWrapper.step + ~LoggerWrapper.wrapper_spec diff --git a/docs/source/pages/modules/sinergym.utils.wrappers.MultiObjectiveReward.rst b/docs/source/pages/modules/sinergym.utils.wrappers.MultiObjectiveReward.rst index 15aed32e05..6affb13786 100644 --- a/docs/source/pages/modules/sinergym.utils.wrappers.MultiObjectiveReward.rst +++ b/docs/source/pages/modules/sinergym.utils.wrappers.MultiObjectiveReward.rst @@ -1,4 +1,4 @@ -sinergym.utils.wrappers.MultiObjectiveReward +sinergym.utils.wrappers.MultiObjectiveReward ============================================ .. currentmodule:: sinergym.utils.wrappers @@ -21,6 +21,7 @@ sinergym.utils.wrappers.MultiObjectiveReward ~MultiObjectiveReward.render ~MultiObjectiveReward.reset ~MultiObjectiveReward.step + ~MultiObjectiveReward.wrapper_spec diff --git a/docs/source/pages/modules/sinergym.utils.wrappers.MultiObsWrapper.rst b/docs/source/pages/modules/sinergym.utils.wrappers.MultiObsWrapper.rst index 772c837b53..a95ff4fd0a 100644 --- a/docs/source/pages/modules/sinergym.utils.wrappers.MultiObsWrapper.rst +++ b/docs/source/pages/modules/sinergym.utils.wrappers.MultiObsWrapper.rst @@ -1,4 +1,4 @@ -sinergym.utils.wrappers.MultiObsWrapper +sinergym.utils.wrappers.MultiObsWrapper ======================================= .. currentmodule:: sinergym.utils.wrappers @@ -21,6 +21,7 @@ sinergym.utils.wrappers.MultiObsWrapper ~MultiObsWrapper.render ~MultiObsWrapper.reset ~MultiObsWrapper.step + ~MultiObsWrapper.wrapper_spec diff --git a/docs/source/pages/modules/sinergym.utils.wrappers.NormalizeObservation.rst b/docs/source/pages/modules/sinergym.utils.wrappers.NormalizeObservation.rst index 215e6fce3b..0b3a7f1144 100644 --- a/docs/source/pages/modules/sinergym.utils.wrappers.NormalizeObservation.rst +++ b/docs/source/pages/modules/sinergym.utils.wrappers.NormalizeObservation.rst @@ -1,4 +1,4 @@ -sinergym.utils.wrappers.NormalizeObservation +sinergym.utils.wrappers.NormalizeObservation ============================================ .. currentmodule:: sinergym.utils.wrappers @@ -23,6 +23,7 @@ sinergym.utils.wrappers.NormalizeObservation ~NormalizeObservation.render ~NormalizeObservation.reset ~NormalizeObservation.step + ~NormalizeObservation.wrapper_spec diff --git a/docs/source/pages/modules/sinergym.utils.wrappers.OfficeGridStorageSmoothingActionConstraintsWrapper.rst b/docs/source/pages/modules/sinergym.utils.wrappers.OfficeGridStorageSmoothingActionConstraintsWrapper.rst index 5151fbead3..32a3569d00 100644 --- a/docs/source/pages/modules/sinergym.utils.wrappers.OfficeGridStorageSmoothingActionConstraintsWrapper.rst +++ b/docs/source/pages/modules/sinergym.utils.wrappers.OfficeGridStorageSmoothingActionConstraintsWrapper.rst @@ -1,4 +1,4 @@ -sinergym.utils.wrappers.OfficeGridStorageSmoothingActionConstraintsWrapper +sinergym.utils.wrappers.OfficeGridStorageSmoothingActionConstraintsWrapper ========================================================================== .. currentmodule:: sinergym.utils.wrappers @@ -22,6 +22,7 @@ sinergym.utils.wrappers.OfficeGridStorageSmoothingActionConstraintsWrapper 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w- zj#~b1PTPM;0+|C2^gIgpZzS-u;J8rxv9Ym_b#ro97Q55&V-(ftz@^QpcR|8;ri*>%CP(I71Wpfq^g{+}8QnL(Ia VpFR8|B9a0yjk{nqq>9Dse*wE`3n%~p literal 0 HcmV?d00001 From e2fec9ee13fd63b9e064670937a63a6cd510a424 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Thu, 16 Mar 2023 14:36:31 +0000 Subject: [PATCH 13/24] Updated documentation about DRL and google cloud with sinergym --- .../pages/deep-reinforcement-learning.rst | 85 ++++--- docs/source/pages/gcloudAPI.rst | 210 +----------------- 2 files changed, 64 insertions(+), 231 deletions(-) diff --git a/docs/source/pages/deep-reinforcement-learning.rst b/docs/source/pages/deep-reinforcement-learning.rst index d0a3b843d5..6e9d3c6616 100644 --- a/docs/source/pages/deep-reinforcement-learning.rst +++ b/docs/source/pages/deep-reinforcement-learning.rst @@ -49,13 +49,30 @@ about how information is extracted which is why its implementation. ``sinergym_logger`` attribute in constructor. ``LoggerCallback`` inherits from Stable Baselines 3 ``BaseCallback`` and -uses `Tensorboard `__ on the -background at the same time. With *Tensorboard*, it's possible to visualize all DRL -training in real time and compare between different executions. This is an example: +uses `Weights & Biases `__(*wandb*) in the background in order to host +all information extracted. With *wandb*, it's possible to track and visualize all DRL +training in real time, register hyperparameters and details of each execution, save artifacts +such as models and sinergym output, and compare between different executions. This is an example: -.. image:: /_static/tensorboard_example.png +- Hyperparameter and summary registration: + +.. image:: /_static/wandb_example1.png + :width: 800 + :alt: WandB hyperparameters + :align: center + +- Artifacts registered (if evaluation is enabled, best model is registered too): + +.. image:: /_static/wandb_example2.png :width: 800 - :alt: Tensorboard example + :alt: WandB artifacts + :align: center + +- Metrics visualization in real time: + +.. image:: /_static/wandb_example3.png + :width: 800 + :alt: WandB charts :align: center There are tables which are in some algorithms and not in others and vice versa. @@ -80,7 +97,7 @@ at the end of the training). Its name is ``LoggerEvalCallback`` and it inherits from Stable Baselines 3 ``EvalCallback``. The main feature added is that the model evaluation is logged in a particular section in -Tensorboard too for the concrete metrics of the building model. +*wandb* too for the concrete metrics of the building model. We have to define in ``LoggerEvalCallback`` construction how many training episodes we want the evaluation process to take place. On the other hand, we have to define how many episodes @@ -91,14 +108,14 @@ therefore, the more faithful it will be to reality in terms of how good the curr turning out to be. However, it will take more time. It calculates timestep and episode average for power consumption, comfort penalty and power penalty. -On the other hand, it calculates too comfort violation percentage in episodes too. +On the other hand, it calculates comfort violation percentage in episodes too. Currently, only mean reward is taken into account to decide when a model is better. -*********************** -Tensorboard structure -*********************** +****************************** +Weights and Biases structure +****************************** -The main structure for *Sinergym* with *Tensorboard* is: +The main structure for *Sinergym* with *wandb* is: * **action**: This section has action values during training. When algorithm is On Policy, it will appear **action_simulation** too. This is because @@ -195,33 +212,43 @@ JSON structure example in `sinergym/scripts/DRL_battery_example.json `__, in order to **tracking experiments** -and recorded them methodically. It is recommended to use it. -You can start a local server with information stored during the -battery of experiments such as initial and ending date of execution, -hyperparameters, duration, etc. + 1. Setting an appropriate name for the experiment. Following the next + format: ``--episodes-seed()`` -Here is an example: + 2. Starting WandB track experiment with that name (if configured in JSON), it will create an local path (*./wandb*) too. -.. image:: /_static/mlflow_example.png - :width: 800 - :alt: Tensorboard example - :align: center + 3. Log all parameters allocated in JSON configuration (including *sinergym.__version__* and python version). + + 4. Setting env with parameters overwritten in case of establishing them. + + 5. Setting wrappers specified in JSON. + + 6. Defining model algorithm using hyperparameters defined. + + 7. Calculate training timesteps using number of episodes. + + 8. Setting up evaluation callback if it has been specified. + + 9. Setting up WandB logger callback if it has been specified. + + 10. Training with environment. + + 11. If remote store has been specified, saving all outputs in Google + Cloud Bucket. If wandb has been specified, saving all + outputs in wandb run artifact. + 12. Auto-delete remote container in Google Cloud Platform when parameter + auto-delete has been specified. -.. note:: For information about how use *Tensorboard* and *Mlflow* with a Cloud - Computing paradigm, see :ref:`Remote Tensorboard log` and - :ref:`Mlflow tracking server set up`. +.. note:: For information about how use *WandB* with a Cloud + Computing paradigm, see :ref:`Remote Weights and Biases log`. .. note:: *This is a work in progress project. Direct support with others algorithms is being planned for the future!* \ No newline at end of file diff --git a/docs/source/pages/gcloudAPI.rst b/docs/source/pages/gcloudAPI.rst index 7b1f0f638a..d43650da34 100644 --- a/docs/source/pages/gcloudAPI.rst +++ b/docs/source/pages/gcloudAPI.rst @@ -8,8 +8,7 @@ Cloud account and combine with *Sinergym* easily. The main idea is to construct a **virtual machine** (VM) using **Google Cloud Engine** (GCE) in order to execute our **Sinergym container** -on it. At the same time, this remote container will update a **Google Cloud -Bucket with experiments results** and **mlflow tracking server** with artifacts +on it. At the same time, this remote container will update **Weights and Biases tracking server** with artifacts if we configure that experiment with those options. When an instance has finished its job, container **auto-remove** its host @@ -231,7 +230,7 @@ firstly, for example: --container-privileged \ --service-account storage-account@sinergym.iam.gserviceaccount.com \ --scopes https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/devstorage.full_control \ - --container-env=gce_zone=europe-west1-b,gce_project_id=sinergym,MLFLOW_TRACKING_URI=http://$(gcloud compute addresses describe mlflow-ip --format='get(address)'):5000 \ + --container-env=gce_zone=europe-west1-b,gce_project_id=sinergym \ --container-restart-policy never \ --container-stdin \ --container-tty \ @@ -291,120 +290,22 @@ Executing experiments in remote containers This script, called *DRL_battery.py*, will be allocated in every remote container and it is used to execute experiments and combine it with -**Google Cloud Bucket**, **Mlflow Artifacts**, **auto-remove**, etc: +**Google Cloud Bucket**, **Weights and Biases**, **auto-remove**, etc: .. literalinclude:: ../../../scripts/DRL_battery.py :language: python .. note:: **DRL_battery.py** is able to be used to local experiments - into client computer. For example, ``--auto_delete`` parameter + into client computer. For example, ``auto_delete`` parameter will have no effect in experiment. This experiments results could be sent to bucket and mlflow artifacts if it is specified. We will see it. -The list of parameter is pretty large. Let's see it: - -- ``--environment`` or ``-env``: Environment name you want to use - (see :ref:`Environments`). - -- ``--episodes`` or ``-ep``: Number of episodes you want to train - agent in simulation (Depending on environment episode length can - be different). - -- ``--algorithm`` or ``-alg``: Algorithm you want to use to train - (Currently, it is available *PPO*, *A2C*, *DQN*, *DDPG* and *SAC*). - -- ``--reward`` or ``-rw``: Reward class you want to use for reward - function. Currently, possible values are "linear" and "exponential" - (see :ref:`Rewards`). - -- ``--normalization`` or ``-norm``: Apply normalization wrapper to - observations during training. If it isn't specified wrapper will - not be applied (see :ref:`Wrappers`). - -- ``--multiobs`` or ``-mobs``: Apply Multi-Observation wrapper to - observations during training. If it isn't specified wrapper will - not be applied (see :ref:`Wrappers`). - -- ``--logger`` or ``-log``: Apply Sinergym logger wrapper during - training. If it isn't specified wrapper will not be applied - (see :ref:`Wrappers` and :ref:`Logger`). - -- ``--tensorboard`` or ``-tens``: This parameter will contain a - **path-file** or **path-remote-bucket** to allocate tensorboard - training logs. If it isn't specified this log will be deactivate - (see :ref:`Tensorboard structure`). - -- ``--evaluation`` or ``-eval``: If it is specified, evaluation - callback will be activate, else model evaluation will be deactivate - during training (see :ref:`Deep Reinforcement Learning Integration`). - -- ``--eval_freq`` or ``-evalf``: Only if ``--evaluation`` flag has been - written. Episode frequency for evaluation. - -- ``--eval_length`` or ``-evall``: Only if ``--evaluation`` flag has been - written. Number of episodes for each evaluation. - -- ``--log_interval`` or ``-inter``: This parameter is used for ``learn()`` - method in each algorithm. It is important specify a correct value. - -- ``--seed`` or ``-sd``: Seed for training, random components in process - will be able to be recreated. - -- ``--remote_store`` or ``-sto``: Determine if sinergym output and - tensorboard log (when a local path is specified and not a remote - bucket path) will be sent to a common resource (Bucket), else will - be allocate in remote container memory only. - -- ``--mlflow_store`` or ``-mlflow``: Determine if sinergym output and - tensorboard log (when a local path is specified and not a remote bucket - path) will be sent to a Mlflow Artifact, else will be allocate in remote - container memory only. - -- ``--group_name`` or ``-group``: It specify to which MIG the host instance - belongs, it is important if --auto-delete is activated. - -- ``--auto_delete`` or ``-del``: Whether this parameter is specified, - remote instance will be auto removed when its job has finished. - -- **algorithm hyperparameters**: Execute ``python DRL_battery --help`` - for more information. +The list of parameter is pretty large. See :ref:`How use` section. .. warning:: For a correct auto_delete functionality, please, use MIG's instead of individual instances. -This script do the next: - - 1. Setting an appropriate name for the experiment. Following the next - format: ``--episodes-seed()`` - - 2. Starting Mlflow track experiment with that name, if mlflow server - is not available, it will be used an local path (*./mlruns*) in - remote container. - - 3. Log all MlFlow parameters (including *sinergym.__version__*). - - 4. Setting reward function specified in ``--reward`` parameter. - - 5. Setting wrappers specified in environment. - - 6. Defining model algorithm using hyperparameters. - - 7. Calculate training timesteps using number of episodes. - - 8. Setting up evaluation callback if it has been specified. - - 9. Setting up Tensorboard logger callback if it has been specified. - - 10. Training with environment. - - 11. If ``--remote_store`` has been specified, saving all outputs in Google - Cloud Bucket. If ``--mlflow_store`` has been specified, saving all - outputs in Mlflow run artifact. - - 12. Auto-delete remote container in Google Cloud Platform when parameter - ``--auto_delete`` has been specified. - Containers permission to bucket storage output ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @@ -413,8 +314,7 @@ it is specified ``--scope``, ``--service-account`` and ``--container-env``. This aim to *remote_store* option in *DRL_battery.py* works correctly. Those parameters provide each container with permissions to write in the bucket and manage Google Cloud Platform (auto instance remove function). -Container environment variables indicate zone, project_id and mlflow tracking -server uri need it in :ref:`Mlflow tracking server set up`. +Container environment variables indicate zone and project_id. Hence, it is **necessary** to **set up this service account** and give privileges in order to that objective. Then, following @@ -485,105 +385,11 @@ This script loads the model. Once the model is loaded, it predicts the actions f states during the agreed episodes. The information is collected and sent to a cloud storage if it has been specified, otherwise it is stored in local memory. -*********************** -Remote Tensorboard log -*********************** - -In ``--tensorboard`` parameter we have to specify a **local path** or a **Bucket path**. - -If we specify a **local path**, tensorboard logs will be stored in remote containers memory. -If you have specified ``--remote_store`` or ``--mlflow_store``, this logs will be sent to -those remote storage when experiment finishes. -One of the strengths of Tensorboard is the ability to see the data in real time as the training -is running. Thus, it is recommended to define in ``--tensorboard`` the **bucket path** directly -in order to send that information -as the training is generating it (see -`this issue `__ -for more information). In our project we have *gs://experiments-storage/tensorboard_log* but you -can have whatever you want. - -.. note:: If in ``--tensorboard`` you have specified a gs path, ``--remote_store`` - or ``--mlflow_store`` parameters don't store tensorboard logs. -.. warning:: Whether you have written a bucket path, don't write ``/`` at the end - (``gs://experiments-storage/tensorboard_log/``), this causes that real-time - remote storage doesn't work correctly. - -.. warning:: In the case that gs URI isn't recognized. Maybe is due to your tensorboard - installation hasn't got access your google account. Try - `gcloud auth application-default login `__ command. - -Visualize remote Tensorboard log in real-time +Visualize remote wandb log in real-time ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -You have two options: - - 1. Create a remote server with tensorboard service deployed. - - 2. Initiate that service in your local computer, reading from the bucket log, - and access to the visualization in *http://localhost:6006* - -The second options is enough since we can read from bucket when we need directly -and shut down local service when we finish. - -.. code:: sh - - $ tensorboard --logdir gs://experiments-storage/tensorboard_log/ - - -****************************** -Mlflow tracking server set up -****************************** - -Mlflow tracking server can be set up into your google account in order to organize -your own experiments (:ref:`Mlflow`). You can separate **back-end** (SQL database) -from tracking server. -In this way, you can shut down or delete server instance without loose your experiments -run data, since SQL is always up. Let's see how: - -.. literalinclude:: ../../../mlflowbuild.sh - :language: sh - -This bash script defines all the process to configure this functionality automatically. -(Once you execute it you don't have to use this script anymore). The arguments -it needs are: *PROJECT_ID*, *BUCKET_NAME*, *ZONE* and *DB_ROOT_PASSWORD*. - -This script do the next for you: - - 1. Creating Service account for mlflow service `[mlflow-tracking-sa]`. - - 2. Creating Back-end artifact bucket. - - 3. Creating SQL instance with root password specified in argument 4. - - 4. Creating mlflow database inner SQL instance. - - 5. Creating service account privileges to use Back-end `[roles/cloudsql.editor]` - - 6. Generating an automatic script called **start_mlflow_tracking.sh** and sending to - ``gs:///scripts/``. - - 7. Deleting local **start_mlflow_tracking.sh** file. - - 8. Creating static external IP for ``mlflow-tracking-server``. - - 9. Deploying remote server ``[mlflow-tracking-server]``. - -Step 8 is very important, this allows you to delete server instance and create again when -you need it without redefining server IP in sinergym-template for remote container experiments. -Notice that server instance creation use service account for mlflow, with this configuration -mlflow can read from SQL server. In :ref:`4. Create your VM or MIG` it is specified -MLFLOW_TRACKING_URI container environment variable using that external static IP. - -.. warning:: It is important execute this script before create sinergym-template instances in order - to annotate `mlflow-server-ip`. - -.. note:: If you want to change any backend configuration, you can change any parameter of the - script bellow. - -.. note:: Whether you have written ``--mlflow_store``, Sinergym outputs will be sent to mlflow server - as artifacts. These artifacts will be stored in the same bucket where is allocated - ``gs://``. +You only have to enter in `Weights & Biases `__ and log in with your GitHub account. ******************** Google Cloud Alerts From 53f6dedd9c603811519a25db7971bf55e22f0ad4 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Fri, 17 Mar 2023 09:34:34 +0000 Subject: [PATCH 14/24] Added Stable Baselines 3 (gymnasium branch) in extra requires --- requirements.txt | 2 +- setup.py | 7 ++++--- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/requirements.txt b/requirements.txt index 04c124ff0f..cffcc8b593 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,6 +1,6 @@ autopep8 eppy -gymnasium +gymnasium @ git+https://github.com/Farama-Foundation/Gymnasium@main isort numpy opyplus diff --git a/setup.py b/setup.py index 049be6143f..bdd98a174a 100644 --- a/setup.py +++ b/setup.py @@ -23,7 +23,8 @@ extras_require={ 'extras': [ 'matplotlib', # visualization - # 'stable-baselines3', # DRL with pytorch + # DRL with pytorch + 'stable-baselines3 @ git+https://github.com/DLR-RM/stable-baselines3@feat/gymnasium-support', 'wandb', 'pytest', 'pytest-cov', @@ -46,10 +47,10 @@ 'pytest', 'pytest-cov', 'pytest-xdist', - # 'stable-baselines3' + 'stable-baselines3 @ git+https://github.com/DLR-RM/stable-baselines3@feat/gymnasium-support', ], 'DRL': [ - # 'stable-baselines3', + 'stable-baselines3 @ git+https://github.com/DLR-RM/stable-baselines3@feat/gymnasium-support', 'wandb' ], 'doc': [ From 3752ce3e0f60d89ad11069ee778a42ee2a706b87 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Fri, 17 Mar 2023 10:23:55 +0000 Subject: [PATCH 15/24] Fixed spelling and sphinx compilation --- docs/source/pages/deep-reinforcement-learning.rst | 3 --- docs/source/pages/wrappers.rst | 2 +- docs/source/spelling_wordlist.txt | 7 +++++++ sinergym/envs/eplus_env.py | 2 +- sinergym/simulators/eplus.py | 2 +- sinergym/utils/wrappers.py | 2 +- 6 files changed, 11 insertions(+), 7 deletions(-) diff --git a/docs/source/pages/deep-reinforcement-learning.rst b/docs/source/pages/deep-reinforcement-learning.rst index 6e9d3c6616..c896f576a5 100644 --- a/docs/source/pages/deep-reinforcement-learning.rst +++ b/docs/source/pages/deep-reinforcement-learning.rst @@ -247,8 +247,5 @@ This script do the next: 12. Auto-delete remote container in Google Cloud Platform when parameter auto-delete has been specified. -.. note:: For information about how use *WandB* with a Cloud - Computing paradigm, see :ref:`Remote Weights and Biases log`. - .. note:: *This is a work in progress project. Direct support with others algorithms is being planned for the future!* \ No newline at end of file diff --git a/docs/source/pages/wrappers.rst b/docs/source/pages/wrappers.rst index c7c0123851..d952d890e8 100644 --- a/docs/source/pages/wrappers.rst +++ b/docs/source/pages/wrappers.rst @@ -16,7 +16,7 @@ You can implement your own wrappers inheriting from *gym.Wrapper* or some of its - **MultiObjectiveReward**: Environment step will return a vector reward (selected elements in wrapper constructor, one for each objective) instead of a traditional scalar value. See `#301 `__. -- **MultiObsWrapper**: Stack observation received in a history queue (size customizable). +- **MultiObsWrapper**: Stack observation received in a history queue (size can be customized). .. note:: For examples about how to use these wrappers, visit :ref:`Wrappers example`. diff --git a/docs/source/spelling_wordlist.txt b/docs/source/spelling_wordlist.txt index 22efac752e..f9f382b3d1 100644 --- a/docs/source/spelling_wordlist.txt +++ b/docs/source/spelling_wordlist.txt @@ -2,6 +2,7 @@ adam approximator argparse Argparse +args ArgumentParser arxiv Arxiv @@ -96,6 +97,8 @@ hyperparameters idd idf init +initialise +initialize isn isort iterable @@ -119,6 +122,7 @@ mlflow mlp mon mujoco +MultiObjectiveReward MultiObsWrapper multiprocess Multiprocessed @@ -213,6 +217,9 @@ Utils VecEnv vectorized vf +WandB +wandb +WandBOutputFormat wEconomizer winterday wouldn diff --git a/sinergym/envs/eplus_env.py b/sinergym/envs/eplus_env.py index 00b6331f5d..aeeed15445 100644 --- a/sinergym/envs/eplus_env.py +++ b/sinergym/envs/eplus_env.py @@ -210,7 +210,7 @@ def step(self, action (Union[int, float, np.integer, np.ndarray, List[Any], Tuple[Any]]): Action selected by the agent. Returns: - Tuple[np.ndarray, float, bool, Dict[str, Any]]: Observation for next timestep, reward obtained, Whether the episode has ended or not, Wheather episode has been truncated or not, and a dictionary with extra information + Tuple[np.ndarray, float, bool, Dict[str, Any]]: Observation for next timestep, reward obtained, Whether the episode has ended or not, Whether episode has been truncated or not, and a dictionary with extra information """ # Get action diff --git a/sinergym/simulators/eplus.py b/sinergym/simulators/eplus.py index 1633ea5a24..f98c1646e6 100644 --- a/sinergym/simulators/eplus.py +++ b/sinergym/simulators/eplus.py @@ -277,7 +277,7 @@ def step(self, action: Union[int, float, np.integer, np.ndarray, List[Any], Returns: Tuple[List[float], bool, bool, Dict[str, Any]]: EnergyPlus results in a 1-D list corresponding to the - variables in variables.cfg. Second element is wether episode has terminated state, third wether episode + variables in variables.cfg. Second element is whether episode has terminated state, third whether episode has truncated state (always False), and last element is a Python Dictionary with additional information about step """ # Check if terminal diff --git a/sinergym/utils/wrappers.py b/sinergym/utils/wrappers.py index 5489db8692..0e703200ab 100644 --- a/sinergym/utils/wrappers.py +++ b/sinergym/utils/wrappers.py @@ -229,7 +229,7 @@ def step(self, action: Union[int, np.ndarray] action (Union[int, float, np.integer, np.ndarray, List[Any], Tuple[Any]]): Action selected by the agent. Returns: - Tuple[np.ndarray, float, bool, Dict[str, Any]]: Observation for next timestep, reward obtained, Whether the episode has ended or not, Wheather episode has been truncated or not, and a dictionary with extra information + Tuple[np.ndarray, float, bool, Dict[str, Any]]: Observation for next timestep, reward obtained, Whether the episode has ended or not, Whether episode has been truncated or not, and a dictionary with extra information """ obs, reward, terminated, truncated, info = self.env.step(action) # We added some extra values (month,day,hour) manually in env, so we From e8fcb504d9b39fe39ec25d9719bc413e4bebda08 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Fri, 17 Mar 2023 14:32:20 +0000 Subject: [PATCH 16/24] Added artifact_name and artifact_tag to DRL_battery JSON and adapted in DRL_battery.py --- scripts/DRL_battery.py | 12 ++++++++---- scripts/DRL_battery_example.json | 4 +++- 2 files changed, 11 insertions(+), 5 deletions(-) diff --git a/scripts/DRL_battery.py b/scripts/DRL_battery.py index e92eaf4b1e..8b4c40ac90 100644 --- a/scripts/DRL_battery.py +++ b/scripts/DRL_battery.py @@ -240,7 +240,7 @@ n_eval_episodes=conf['evaluation']['eval_length']) callbacks.append(eval_callback) -# Set up tensorboard logger +# Set up wandb logger if conf.get('wandb'): # wandb logger and setting in SB3 logger = Logger( @@ -278,9 +278,13 @@ # ---------------------------------------------------------------------------- # if conf.get('wandb'): - artifact = wandb.Artifact('train', 'model') - artifact.add_dir(env.simulator._env_working_dir_parent) - artifact.add_dir('./best_model/') + artifact = wandb.Artifact( + name=conf['wandb']['artifact_name'], + type=conf['wandb']['artifact_type']) + artifact.add_dir( + env.simulator._env_working_dir_parent, + name='sinergym_output/') + artifact.add_dir('./best_model/', name='evaluation/') run.log_artifact(artifact) # wandb has finished diff --git a/scripts/DRL_battery_example.json b/scripts/DRL_battery_example.json index f3e8330463..5e727cebba 100644 --- a/scripts/DRL_battery_example.json +++ b/scripts/DRL_battery_example.json @@ -56,6 +56,8 @@ }, "wandb": { "project": "sinergym", - "entity": "alex_ugr" + "entity": "alex_ugr", + "artifact_name": "training", + "artifact_tag": "experiment1" } } \ No newline at end of file From d27c664228d842ab26ccc61b50b4949f88855ef3 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Fri, 17 Mar 2023 14:32:55 +0000 Subject: [PATCH 17/24] Adapted load_agent.py to new JSON format and created JSON example (with wandb model load option included) --- scripts/load_agent.py | 263 ++++++++++++++------------------ scripts/load_agent_example.json | 52 +++++++ 2 files changed, 168 insertions(+), 147 deletions(-) create mode 100644 scripts/load_agent_example.json diff --git a/scripts/load_agent.py b/scripts/load_agent.py index 0da09f47cb..bd2bee6b19 100644 --- a/scripts/load_agent.py +++ b/scripts/load_agent.py @@ -1,14 +1,18 @@ import argparse +import json +import sys import gymnasium as gym import numpy as np -from stable_baselines3 import A2C, DDPG, DQN, PPO, SAC, TD3 - import sinergym import sinergym.utils.gcloud as gcloud -from sinergym.utils.constants import RANGES_5ZONE, RANGES_DATACENTER, RANGES_IW -from sinergym.utils.rewards import ExpReward, LinearReward -from sinergym.utils.wrappers import LoggerWrapper, NormalizeObservation +from sinergym.utils.constants import * +from sinergym.utils.rewards import * +from sinergym.utils.wrappers import * +from stable_baselines3 import A2C, DDPG, DQN, PPO, SAC, TD3 +from stable_baselines3.common.monitor import Monitor + +import wandb # ---------------------------------------------------------------------------- # # Parameters # @@ -16,169 +20,133 @@ parser = argparse.ArgumentParser() parser.add_argument( - '--environment', - '-env', - required=True, - type=str, - dest='environment', - help='Environment name of simulation (see sinergym/__init__.py).') -parser.add_argument( - '--model', - '-mod', + '--configuration', + '-conf', required=True, type=str, - default=None, - dest='model', - help='Path where model is stored.') -parser.add_argument( - '--episodes', - '-ep', - type=int, - default=1, - dest='episodes', - help='Number of episodes for training.') -parser.add_argument( - '--algorithm', - '-alg', - type=str, - default='PPO', - dest='algorithm', - help='Algorithm used to train (possible values: PPO, A2C, DQN, DDPG, SAC, TD3).') -parser.add_argument( - '--reward', - '-rw', - type=str, - default='linear', - dest='reward', - help='Reward function used by model, by default is linear (possible values: linear, exponential).') -parser.add_argument( - '--energy_weight', - '-rew', - type=float, - dest='energy_weight', - help='Reward energy weight with compatible rewards types.') -parser.add_argument( - '--normalization', - '-norm', - action='store_true', - dest='normalization', - help='Apply normalization to observations if this flag is specified.') -parser.add_argument( - '--logger', - '-log', - action='store_true', - dest='logger', - help='Apply Sinergym CSVLogger class if this flag is specified.') -parser.add_argument( - '--seed', - '-sd', - type=int, - default=None, - dest='seed', - help='Seed used to algorithm training.') -parser.add_argument( - '--id', - '-id', - type=str, - default=None, - dest='id', - help='Custom load evaluation identifier.') -parser.add_argument( - '--remote_store', - '-sto', - action='store_true', - dest='remote_store', - help='Determine if sinergym output will be sent to a Google Cloud Storage Bucket.') -parser.add_argument( - '--group_name', - '-group', - type=str, - dest='group_name', - help='This field indicate instance group name') -parser.add_argument( - '--bucket_name', - '-buc', - type=str, - default='experiments-storage', - dest='bucket_name', - help='This field indicates bucket name (not used currently in script)') -parser.add_argument( - '--auto_delete', - '-del', - action='store_true', - dest='auto_delete', - help='If is a GCE instance and this flag is active, that instance will be removed from GCP.') + dest='configuration', + help='Path to experiment configuration (JSON file)' +) args = parser.parse_args() +# ---------------------------------------------------------------------------- # +# Read json parameters # +# ---------------------------------------------------------------------------- # + +with open(args.configuration) as json_conf: + conf = json.load(json_conf) + # ---------------------------------------------------------------------------- # # Evaluation name # # ---------------------------------------------------------------------------- # -name = args.model.split('/')[-1] + '-EVAL-episodes-' + \ - str(args.episodes) -if args.id: - name += '-id-' + args.id +name = conf['model'].split('/')[-1] + '-EVAL-episodes-' + \ + str(conf['episodes']) +if conf.get('id'): + name += '-id-' + conf['id'] # ---------------------------------------------------------------------------- # -# Environment definition # +# WandB registration # # ---------------------------------------------------------------------------- # -if args.reward == 'linear': - reward = LinearReward -elif args.reward == 'exponential': - reward = ExpReward -else: - raise RuntimeError('Reward function specified is not registered.') -env = gym.make(args.environment, reward=reward) -if hasattr(env.reward_fn, 'W_energy') and args.energy_weight: - env.reward_fn.W_energy = args.energy_weight +if conf.get('wandb'): + # Create wandb.config object in order to log all experiment params + experiment_params = { + 'sinergym-version': sinergym.__version__, + 'python-version': sys.version + } + experiment_params.update(conf) + + # Get wandb init params + wandb_params = conf['wandb'] + # Init wandb entry + run = wandb.init( + name=name + '_' + wandb.util.generate_id(), + config=experiment_params, + ** wandb_params + ) + +# --------------------- Overwrite environment parameters --------------------- # +env_params = {} +# Transform required str's into Callables +if conf.get('env_params'): + if conf['env_params'].get('reward'): + conf['env_params']['reward'] = eval(conf['env_params']['reward']) + if conf['env_params'].get('observation_space'): + conf['env_params']['observation_space'] = eval( + conf['env_params']['observation_space']) + if conf['env_params'].get('action_space'): + conf['env_params']['observation_space'] = eval( + conf['env_params']['action_space']) + + env_params = conf['env_params'] + +# ---------------------------------------------------------------------------- # +# Environment definition # +# ---------------------------------------------------------------------------- # +env = gym.make( + conf['environment'], + ** env_params) +env = Monitor(env) # ---------------------------------------------------------------------------- # # Wrappers # # ---------------------------------------------------------------------------- # -if args.normalization: - # We have to know what dictionary ranges to use - norm_range = None - env_type = args.environment.split('-')[1] - if env_type == 'datacenter': - norm_range = RANGES_DATACENTER - elif env_type == '5Zone': - norm_range = RANGES_5ZONE - elif env_type == 'IWMullion': - norm_range = RANGES_IW - else: - raise NameError('env_type is not valid, check environment name') - env = NormalizeObservation(env, ranges=norm_range) -if args.logger: - env = LoggerWrapper(env) +if conf.get('wrappers'): + for key, parameters in conf['wrappers'].items(): + wrapper_class = eval(key) + for name, value in parameters.items(): + # parse str parameters to sinergym Callable or Objects if it is + # required + if isinstance(value, str): + if 'sinergym.' in value: + parameters[name] = eval(value) + env = wrapper_class(env=env, ** parameters) # ---------------------------------------------------------------------------- # # Load Agent # # ---------------------------------------------------------------------------- # -# If a model is from a bucket, download model -if 'gs://' in args.model: +# ------------------------ Weights and Bias model path ----------------------- # +if conf.get('wandb'): + if conf['wandb'].get('load_model'): + # get model path + artifact_tag = conf['wandb']['load_model'].get( + 'artifact_tag', 'latest') + wandb_path = conf['wandb']['load_model']['entity'] + '/' + conf['wandb']['load_model']['project'] + \ + '/' + conf['wandb']['load_model']['artifact_type'] + ':' + artifact_tag + # Download artifact + artifact = run.use_artifact(wandb_path) + artifact.get_path(conf['wandb']['load_model'] + ['artifact_path']).download('.') + # Set model path to local wandb file downloaded + model_path = './' + conf['wandb']['load_model']['artifact_path'] + +# -------------------------- Google cloud model path ------------------------- # +elif 'gs://' in conf['model']: # Download from given bucket (gcloud configured with privileges) client = gcloud.init_storage_client() - bucket_name = args.model.split('/')[2] - model_path = args.model.split(bucket_name + '/')[-1] + bucket_name = conf['model'].split('/')[2] + model_path = conf['model'].split(bucket_name + '/')[-1] gcloud.read_from_bucket(client, bucket_name, model_path) model_path = './' + model_path +# ----------------------------- Local model path ----------------------------- # else: - model_path = args.model + model_path = conf['model'] model = None -if args.algorithm == 'DQN': +algorithm_name = conf['algorithm']['name'] +if algorithm_name == 'SB3-DQN': model = DQN.load(model_path) -elif args.algorithm == 'DDPG': +elif algorithm_name == 'SB3-DDPG': model = DDPG.load(model_path) -elif args.algorithm == 'A2C': +elif algorithm_name == 'SB3-A2C': model = A2C.load(model_path) -elif args.algorithm == 'PPO': +elif algorithm_name == 'SB3-PPO': model = PPO.load(model_path) -elif args.algorithm == 'SAC': +elif algorithm_name == 'SB3-SAC': model = SAC.load(model_path) -elif args.algorithm == 'TD3': +elif algorithm_name == 'SB3-TD3': model = TD3.load(model_path) else: raise RuntimeError('Algorithm specified is not registered.') @@ -186,7 +154,7 @@ # ---------------------------------------------------------------------------- # # Execute loaded agent # # ---------------------------------------------------------------------------- # -for i in range(args.episodes): +for i in range(conf['episodes']): obs, info = env.reset() rewards = [] terminated = False @@ -210,19 +178,20 @@ # ---------------------------------------------------------------------------- # # Store results # # ---------------------------------------------------------------------------- # -if args.remote_store: - # Initiate Google Cloud client - client = gcloud.init_storage_client() - # Code for send output and tensorboard to common resource here. - gcloud.upload_to_bucket( - client, - src_path=env.simulator._env_working_dir_parent, - dest_bucket_name='experiments-storage', - dest_path=name) +if conf.get('cloud'): + if conf.get('remote_store'): + # Initiate Google Cloud client + client = gcloud.init_storage_client() + # Code for send output and tensorboard to common resource here. + gcloud.upload_to_bucket( + client, + src_path=env.simulator._env_working_dir_parent, + dest_bucket_name='experiments-storage', + dest_path=name) # ---------------------------------------------------------------------------- # # Auto-delete remote container # # ---------------------------------------------------------------------------- # -if args.group_name and args.auto_delete: +if conf.get('group_name') and conf.get('auto_delete'): token = gcloud.get_service_account_token() - gcloud.delete_instance_MIG_from_container(args.group_name, token) + gcloud.delete_instance_MIG_from_container(conf('group_name'), token) diff --git a/scripts/load_agent_example.json b/scripts/load_agent_example.json new file mode 100644 index 0000000000..e5b7abb952 --- /dev/null +++ b/scripts/load_agent_example.json @@ -0,0 +1,52 @@ +{ + "id": "LoadExample", + "environment": "Eplus-5Zone-hot-continuous-stochastic-v1", + "episodes": 5, + "algorithm": { + "name": "SB3-PPO" + }, + "env_params": { + "reward": "LinearReward", + "reward_kwargs": { + "temperature_variable": [ + "Zone Air Temperature(SPACE1-1)", + "Zone Air Temperature(SPACE1-2)" + ], + "energy_variable": "Facility Total HVAC Electricity Demand Rate(Whole Building)", + "range_comfort_winter": [ + 20.0, + 23.5 + ], + "range_comfort_summer": [ + 23.0, + 26.0 + ] + }, + "act_repeat": 1 + }, + "seed": 3, + "model": "alex_ugr/sinergym/train:latest", + "wrappers": { + "NormalizeObservation": { + "ranges": "sinergym.utils.constants.RANGES_5ZONE" + }, + "LoggerWrapper": { + "logger_class": "sinergym.utils.logger.CSVLogger", + "flag": true + } + }, + "wandb": { + "project": "sinergym_evaluations", + "entity": "alex_ugr", + "artifact_name": "evaluating", + "artifact_type": "evaluation1", + "load_model": { + "project": "sinergym", + "entity": "alex_ugr", + "artifact_name": "training", + "artifact_type": "experiment1", + "artifact_tag": "v9", + "artifact_path": "sinergym_output/flag.zip" + } + } +} \ No newline at end of file From 61cac075618467a732477c6a9fae8b02f89b83c2 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Mon, 20 Mar 2023 09:34:25 +0000 Subject: [PATCH 18/24] Deleted stable baselines 3 from gymnasium PR extra dependency --- requirements.txt | 2 +- setup.py | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/requirements.txt b/requirements.txt index cffcc8b593..04c124ff0f 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,6 +1,6 @@ autopep8 eppy -gymnasium @ git+https://github.com/Farama-Foundation/Gymnasium@main +gymnasium isort numpy opyplus diff --git a/setup.py b/setup.py index bdd98a174a..e433aa7865 100644 --- a/setup.py +++ b/setup.py @@ -24,7 +24,7 @@ 'extras': [ 'matplotlib', # visualization # DRL with pytorch - 'stable-baselines3 @ git+https://github.com/DLR-RM/stable-baselines3@feat/gymnasium-support', + # 'stable-baselines3 @ git+https://github.com/DLR-RM/stable-baselines3@feat/gymnasium-support', 'wandb', 'pytest', 'pytest-cov', @@ -47,10 +47,10 @@ 'pytest', 'pytest-cov', 'pytest-xdist', - 'stable-baselines3 @ git+https://github.com/DLR-RM/stable-baselines3@feat/gymnasium-support', + # 'stable-baselines3 @ git+https://github.com/DLR-RM/stable-baselines3@feat/gymnasium-support', ], 'DRL': [ - 'stable-baselines3 @ git+https://github.com/DLR-RM/stable-baselines3@feat/gymnasium-support', + # 'stable-baselines3 @ git+https://github.com/DLR-RM/stable-baselines3@feat/gymnasium-support', 'wandb' ], 'doc': [ From 617a676f6396cb362fe0a6e0ebe242292ef2f0ab Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Mon, 20 Mar 2023 09:45:53 +0000 Subject: [PATCH 19/24] Fixed DRL_battery wandb artifact definition --- scripts/DRL_battery.py | 2 +- scripts/DRL_battery_example.json | 8 +++++--- 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/scripts/DRL_battery.py b/scripts/DRL_battery.py index 8b4c40ac90..dc2ec4ca48 100644 --- a/scripts/DRL_battery.py +++ b/scripts/DRL_battery.py @@ -67,7 +67,7 @@ experiment_params.update(conf) # Get wandb init params - wandb_params = conf['wandb'] + wandb_params = conf['wandb']['init_params'] # Init wandb entry run = wandb.init( name=name + '_' + wandb.util.generate_id(), diff --git a/scripts/DRL_battery_example.json b/scripts/DRL_battery_example.json index 5e727cebba..fba15d6f56 100644 --- a/scripts/DRL_battery_example.json +++ b/scripts/DRL_battery_example.json @@ -55,9 +55,11 @@ "eval_length": 1 }, "wandb": { - "project": "sinergym", - "entity": "alex_ugr", + "init_params": { + "project": "sinergym", + "entity": "alex_ugr" + }, "artifact_name": "training", - "artifact_tag": "experiment1" + "artifact_type": "experiment1" } } \ No newline at end of file From eea60c8d033a953ebe543cf933eedb6a6acc0ee0 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Mon, 20 Mar 2023 11:15:24 +0000 Subject: [PATCH 20/24] Updated DRL_battery.py model save path and wandb artifact --- scripts/DRL_battery.py | 33 +++++++++++++++++++++------------ sinergym/envs/eplus_env.py | 2 ++ 2 files changed, 23 insertions(+), 12 deletions(-) diff --git a/scripts/DRL_battery.py b/scripts/DRL_battery.py index dc2ec4ca48..ac23ba044c 100644 --- a/scripts/DRL_battery.py +++ b/scripts/DRL_battery.py @@ -46,13 +46,13 @@ # Register run name # # ---------------------------------------------------------------------------- # experiment_date = datetime.today().strftime('%Y-%m-%d_%H:%M') -name = conf['algorithm']['name'] + '-' + conf['environment'] + \ +experiment_name = conf['algorithm']['name'] + '-' + conf['environment'] + \ '-episodes-' + str(conf['episodes']) if conf.get('seed'): - name += '-seed-' + str(conf['seed']) + experiment_name += '-seed-' + str(conf['seed']) if conf.get('id'): - name += '-id-' + str(conf['id']) -name += '_' + experiment_date + experiment_name += '-id-' + str(conf['id']) +experiment_name += '_' + experiment_date # ---------------------------------------------------------------------------- # # WandB registration # @@ -70,7 +70,7 @@ wandb_params = conf['wandb']['init_params'] # Init wandb entry run = wandb.init( - name=name + '_' + wandb.util.generate_id(), + name=experiment_name + '_' + wandb.util.generate_id(), config=experiment_params, ** wandb_params ) @@ -93,6 +93,8 @@ # ---------------------------------------------------------------------------- # # Environment construction # # ---------------------------------------------------------------------------- # +# For this script, the execution name will be updated +env_params.update({'env_name': experiment_name}) env = gym.make( conf['environment'], ** env_params) @@ -101,6 +103,8 @@ # env for evaluation if is enabled eval_env = None if conf.get('evaluation'): + eval_name = conf['evaluation'].get('name', env.name + '-EVAL') + env_params.update({'env_name': eval_name}) eval_env = gym.make( conf['environment'], ** env_params) @@ -231,10 +235,12 @@ if conf.get('evaluation'): eval_callback = LoggerEvalCallback( eval_env, - best_model_save_path='best_model/' + - name, - log_path='best_model/' + name + '/', - eval_freq=n_timesteps_episode * conf['evaluation']['eval_freq'], + best_model_save_path=eval_env.simulator._env_working_dir_parent + + '/best_model/', + log_path=eval_env.simulator._env_working_dir_parent + + '/best_model/', + eval_freq=n_timesteps_episode * + conf['evaluation']['eval_freq'], deterministic=True, render=False, n_eval_episodes=conf['evaluation']['eval_length']) @@ -265,7 +271,7 @@ total_timesteps=timesteps, callback=callback, log_interval=conf['algorithm']['log_interval']) -model.save(env.simulator._env_working_dir_parent + '/' + name) +model.save(env.simulator._env_working_dir_parent + '/model') # If the algorithm doesn't reset or close the environment, this script will do it in # order to correctly log all the simulation data (Energyplus + Sinergym @@ -283,8 +289,11 @@ type=conf['wandb']['artifact_type']) artifact.add_dir( env.simulator._env_working_dir_parent, - name='sinergym_output/') - artifact.add_dir('./best_model/', name='evaluation/') + name='training_output/') + if conf.get('evaluation'): + artifact.add_dir( + eval_env.simulator._env_working_dir_parent, + name='evaluation_output/') run.log_artifact(artifact) # wandb has finished diff --git a/sinergym/envs/eplus_env.py b/sinergym/envs/eplus_env.py index aeeed15445..5d4e3cfb83 100644 --- a/sinergym/envs/eplus_env.py +++ b/sinergym/envs/eplus_env.py @@ -80,6 +80,8 @@ def __init__( self.variables['observation'] = observation_variables self.variables['action'] = action_variables + self.name = env_name + # ---------------------------------------------------------------------------- # # Simulator # # ---------------------------------------------------------------------------- # From c6abb2e8be2f52feab93d19b83a1bd372152948a Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Mon, 20 Mar 2023 12:16:39 +0000 Subject: [PATCH 21/24] Updated load_agent evaluation name, updated wandb init_params, fixed wandb_path and artifact registration added --- scripts/load_agent.py | 32 ++++++++++++++++++++++++++------ scripts/load_agent_example.json | 12 +++++++----- 2 files changed, 33 insertions(+), 11 deletions(-) diff --git a/scripts/load_agent.py b/scripts/load_agent.py index bd2bee6b19..b0a392010f 100644 --- a/scripts/load_agent.py +++ b/scripts/load_agent.py @@ -39,10 +39,12 @@ # ---------------------------------------------------------------------------- # # Evaluation name # # ---------------------------------------------------------------------------- # -name = conf['model'].split('/')[-1] + '-EVAL-episodes-' + \ - str(conf['episodes']) +evaluation_date = datetime.today().strftime('%Y-%m-%d_%H:%M') +evaluation_name = conf['algorithm']['name'] + '-' + conf['environment'] + \ + '-episodes-' + str(conf['episodes']) if conf.get('id'): - name += '-id-' + conf['id'] + evaluation_name += '-id-' + str(conf['id']) +evaluation_name += '_' + evaluation_date # ---------------------------------------------------------------------------- # # WandB registration # @@ -57,10 +59,10 @@ experiment_params.update(conf) # Get wandb init params - wandb_params = conf['wandb'] + wandb_params = conf['wandb']['init_params'] # Init wandb entry run = wandb.init( - name=name + '_' + wandb.util.generate_id(), + name=evaluation_name + '_' + wandb.util.generate_id(), config=experiment_params, ** wandb_params ) @@ -83,6 +85,7 @@ # ---------------------------------------------------------------------------- # # Environment definition # # ---------------------------------------------------------------------------- # +env_params.update({'env_name': evaluation_name}) env = gym.make( conf['environment'], ** env_params) @@ -113,7 +116,7 @@ artifact_tag = conf['wandb']['load_model'].get( 'artifact_tag', 'latest') wandb_path = conf['wandb']['load_model']['entity'] + '/' + conf['wandb']['load_model']['project'] + \ - '/' + conf['wandb']['load_model']['artifact_type'] + ':' + artifact_tag + '/' + conf['wandb']['load_model']['artifact_name'] + ':' + artifact_tag # Download artifact artifact = run.use_artifact(wandb_path) artifact.get_path(conf['wandb']['load_model'] @@ -175,6 +178,23 @@ sum(rewards)) env.close() +# ---------------------------------------------------------------------------- # +# Wandb Artifacts # +# ---------------------------------------------------------------------------- # + +if conf.get('wandb'): + artifact = wandb.Artifact( + name=conf['wandb']['artifact_name'], + type=conf['wandb']['artifact_type']) + artifact.add_dir( + env.simulator._env_working_dir_parent, + name='evaluation_output/') + + run.log_artifact(artifact) + +# wandb has finished +run.finish() + # ---------------------------------------------------------------------------- # # Store results # # ---------------------------------------------------------------------------- # diff --git a/scripts/load_agent_example.json b/scripts/load_agent_example.json index e5b7abb952..79fb170387 100644 --- a/scripts/load_agent_example.json +++ b/scripts/load_agent_example.json @@ -25,7 +25,7 @@ "act_repeat": 1 }, "seed": 3, - "model": "alex_ugr/sinergym/train:latest", + "model": "alex_ugr/sinergym/training:latest", "wrappers": { "NormalizeObservation": { "ranges": "sinergym.utils.constants.RANGES_5ZONE" @@ -36,8 +36,10 @@ } }, "wandb": { - "project": "sinergym_evaluations", - "entity": "alex_ugr", + "init_params": { + "project": "sinergym_evaluations", + "entity": "alex_ugr" + }, "artifact_name": "evaluating", "artifact_type": "evaluation1", "load_model": { @@ -45,8 +47,8 @@ "entity": "alex_ugr", "artifact_name": "training", "artifact_type": "experiment1", - "artifact_tag": "v9", - "artifact_path": "sinergym_output/flag.zip" + "artifact_tag": "v0", + "artifact_path": "evaluation_output/best_model/model.zip" } } } \ No newline at end of file From f9e8c89738b24dfc2f571e1d2e63b39bc43fc90b Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Mon, 20 Mar 2023 13:31:07 +0000 Subject: [PATCH 22/24] updated structure documentation for load_agent.py --- .../pages/deep-reinforcement-learning.rst | 43 +++++++++-- docs/source/pages/gcloudAPI.rst | 73 +++---------------- scripts/DRL_battery.py | 2 +- scripts/load_agent.py | 2 +- 4 files changed, 49 insertions(+), 71 deletions(-) diff --git a/docs/source/pages/deep-reinforcement-learning.rst b/docs/source/pages/deep-reinforcement-learning.rst index c896f576a5..ec72dcf4ab 100644 --- a/docs/source/pages/deep-reinforcement-learning.rst +++ b/docs/source/pages/deep-reinforcement-learning.rst @@ -170,13 +170,19 @@ The main structure for *Sinergym* with *wandb* is: .. note:: Evaluation of models can be recorded too, adding ``EvalLoggerCallback`` to model learn method. -********** -How use -********** +************ +How to use +************ + +For more information about how to use it with cloud computing, visit :ref:`Sinergym with Google Cloud` + + +Train a model +~~~~~~~~~~~~~~~~ You can try your own experiments and benefit from this functionality. `sinergym/scripts/DRL_battery.py `__ -is a example code to use it. You can use ``DRL_battery.py`` directly from +is a script to help you to do it. You can use ``DRL_battery.py`` directly from your local computer or using Google Cloud Platform. The most **important information** you must keep in mind when you try @@ -210,7 +216,7 @@ JSON structure example in `sinergym/scripts/DRL_battery_example.json `__ +is a script to help you to do it. You can use ``load_agent.py`` directly from +your local computer or using Google Cloud Platform. + +``load_agent.py`` has a unique parameter to be able to execute it; ``-conf``. +This parameter is a str to indicate the JSON file in which there are allocated +all information about the evaluation you want to execute. You can see the +JSON structure example in `sinergym/scripts/load_agent_example.json `__: + +* The **obligatory** parameters are: environment, episodes, + algorithm (only algorithm name is necessary) and model to load. + +* The **optional** parameters are: All environment parameters (if it is specified + will be overwrite the default environment value), + experiment ID, wrappers to use (respecting the order), + wandb functionality and cloud options. + +This script loads the model. Once the model is loaded, it predicts the actions from the +states during the agreed episodes. The information is collected and sent to a remote +storage if it is indicated (such as WandB), +otherwise it is stored in local memory. + .. note:: *This is a work in progress project. Direct support with others algorithms is being planned for the future!* \ No newline at end of file diff --git a/docs/source/pages/gcloudAPI.rst b/docs/source/pages/gcloudAPI.rst index d43650da34..8265f25d24 100644 --- a/docs/source/pages/gcloudAPI.rst +++ b/docs/source/pages/gcloudAPI.rst @@ -97,7 +97,7 @@ Or you can use **Google Cloud Platform Console**: If you have installed *Sinergym* and *Sinergym extras*. **Google Cloud SDK must be linked with other python modules** in order to some functionality works in -the future (for example, *Tensorboard*). Please, execute the next in your terminal: +the future. Please, execute the next in your terminal: .. code:: sh @@ -288,20 +288,16 @@ you can enter in remote container with *gcloud ssh* and execute Executing experiments in remote containers ******************************************** -This script, called *DRL_battery.py*, will be allocated in every remote -container and it is used to execute experiments and combine it with -**Google Cloud Bucket**, **Weights and Biases**, **auto-remove**, etc: +`DRL_battery.py `__ and +`load_agent.py `__ +will be allocated in every remote container and it is used to execute experiments and evaluations, +being possible to combine with **Google Cloud Bucket**, **Weights and Biases**, **auto-remove**, etc: -.. literalinclude:: ../../../scripts/DRL_battery.py - :language: python +.. note:: **DRL_battery.py** can be used in local experiments + and send output data and artifact to remote storage + such as wandb without configure cloud computing too. -.. note:: **DRL_battery.py** is able to be used to local experiments - into client computer. For example, ``auto_delete`` parameter - will have no effect in experiment. This experiments results - could be sent to bucket and mlflow artifacts if it is specified. - We will see it. - -The list of parameter is pretty large. See :ref:`How use` section. +The structure of the JSON to configure the experiment or evaluation is specified in :ref:`How to use` section. .. warning:: For a correct auto_delete functionality, please, use MIG's instead of individual instances. @@ -335,57 +331,6 @@ root (gitignore will ignore this file in remote). Finally, we export this file in **GOOGLE_CLOUD_CREDENTIALS** in our local computer in order to gcloud SDK knows that it has to use that token to authenticate. -********************** -Load a trained model -********************** - -For this purpose, we have a script called *load_agent.py* which can be used both -on a remote machine and locally on our computer, just like *DRL_battery.py*. - -So, what this script does is to use the path that we pass as a parameter where our -model is located. It loads the model and performs the evaluation that we want. - -The list of parameter is: - -- ``--environment`` or ``-env``: Environment name you want to use. - -- ``--model`` or ``-mod``: Trained model (zip file) you want to use to execute - the evaluation. This path can be a local path file into your computer (remote or host) - or a Google Cloud Storage resource (bucket like ``gs:///``). - -- ``--episodes`` or ``-ep``: Number of episodes you want to evaluate agent in simulation - (Depending on environment episode length can be different). - -- ``--algorithm`` or ``-alg``: Algorithm which model was trained (Currently, it is - available *PPO*, *A2C*, *DQN*, *DDPG* and *SAC*). - -- ``--reward`` or ``-rw``: Reward class you want to use for reward function (same reward - than training model is recommended). Currently, possible values are - "linear" and "exponential". - -- ``--normalization`` or ``-norm``: Apply normalization wrapper to observations during - evaluation. If it isn't specified wrapper will not be applied. - -- ``--logger`` or ``-log``: Apply Sinergym logger wrapper during evaluation. If it isn't - specified wrapper will not be applied. - -- ``--seed`` or ``-sd``: Seed for evaluation, random components in process will be able - to be recreated. - -- ``--remote_store`` or ``-sto``: Determine if sinergym output will be sent to a common resource - (Bucket), else will be allocate in container or host memory only. - -- ``--group_name`` or ``-group``: It specify to which MIG the host instance belongs, it is important - if --auto-delete is activated. - -- ``--auto_delete`` or ``-del``: Whether this parameter is specified, remote instance will be auto - removed when its job has finished. - -This script loads the model. Once the model is loaded, it predicts the actions from the -states during the agreed episodes. The information is collected and sent to a cloud storage -if it has been specified, otherwise it is stored in local memory. - - Visualize remote wandb log in real-time ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ diff --git a/scripts/DRL_battery.py b/scripts/DRL_battery.py index ac23ba044c..185d1570ff 100644 --- a/scripts/DRL_battery.py +++ b/scripts/DRL_battery.py @@ -306,7 +306,7 @@ if conf['cloud'].get('remote_store'): # Initiate Google Cloud client client = gcloud.init_storage_client() - # Code for send output and tensorboard to common resource here. + # Code for send output to common Google Cloud resource here. gcloud.upload_to_bucket( client, src_path=env.simulator._env_working_dir_parent, diff --git a/scripts/load_agent.py b/scripts/load_agent.py index b0a392010f..4c2149593c 100644 --- a/scripts/load_agent.py +++ b/scripts/load_agent.py @@ -202,7 +202,7 @@ if conf.get('remote_store'): # Initiate Google Cloud client client = gcloud.init_storage_client() - # Code for send output and tensorboard to common resource here. + # Code for send output to common Google Cloud resource here. gcloud.upload_to_bucket( client, src_path=env.simulator._env_working_dir_parent, From 437f6ac46a351fd5dc6e4f1bad0566d02ebe14aa Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Mon, 20 Mar 2023 13:34:32 +0000 Subject: [PATCH 23/24] extra require SB3 latest stable version and SB3 tests deactivated temporally --- setup.py | 6 +++--- tests/test_stable_baselines.py | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/setup.py b/setup.py index e433aa7865..049d99520c 100644 --- a/setup.py +++ b/setup.py @@ -24,7 +24,7 @@ 'extras': [ 'matplotlib', # visualization # DRL with pytorch - # 'stable-baselines3 @ git+https://github.com/DLR-RM/stable-baselines3@feat/gymnasium-support', + 'stable-baselines3', 'wandb', 'pytest', 'pytest-cov', @@ -47,10 +47,10 @@ 'pytest', 'pytest-cov', 'pytest-xdist', - # 'stable-baselines3 @ git+https://github.com/DLR-RM/stable-baselines3@feat/gymnasium-support', + 'stable-baselines3', ], 'DRL': [ - # 'stable-baselines3 @ git+https://github.com/DLR-RM/stable-baselines3@feat/gymnasium-support', + 'stable-baselines3', 'wandb' ], 'doc': [ diff --git a/tests/test_stable_baselines.py b/tests/test_stable_baselines.py index 321e37ba39..c3ad5a20b5 100644 --- a/tests/test_stable_baselines.py +++ b/tests/test_stable_baselines.py @@ -9,7 +9,7 @@ required = {'stable-baselines3'} installed = {pkg.key for pkg in pkg_resources.working_set} missing = required - installed - +missing = True if not missing: import stable_baselines3 from stable_baselines3.common.noise import (NormalActionNoise, From b601ca0991a19968a7c82cf6eac0dd16f579d614 Mon Sep 17 00:00:00 2001 From: AlejandroCN7 Date: Mon, 20 Mar 2023 13:43:55 +0000 Subject: [PATCH 24/24] Added wandb dependency to test container workflow --- setup.py | 1 + 1 file changed, 1 insertion(+) diff --git a/setup.py b/setup.py index 049d99520c..d0b43ab099 100644 --- a/setup.py +++ b/setup.py @@ -48,6 +48,7 @@ 'pytest-cov', 'pytest-xdist', 'stable-baselines3', + 'wandb' ], 'DRL': [ 'stable-baselines3',