From d40acce720a41238155e4150ae60b0959d54aa93 Mon Sep 17 00:00:00 2001 From: Julius Miller Date: Wed, 28 Aug 2024 14:49:01 +0200 Subject: [PATCH 01/23] fix: adjust input and output parameters, delete deprecated seed method --- robot_sf/gym_env/robot_env.py | 34 ++++++++-------------------------- 1 file changed, 8 insertions(+), 26 deletions(-) diff --git a/robot_sf/gym_env/robot_env.py b/robot_sf/gym_env/robot_env.py index 1e6057e..718d698 100644 --- a/robot_sf/gym_env/robot_env.py +++ b/robot_sf/gym_env/robot_env.py @@ -157,25 +157,28 @@ def step(self, action): if self.recording_enabled: self.record() - return obs, reward, term, {"step": meta["step"], "meta": meta} + # observation, reward, terminal, truncated,info + return obs, reward, term, False,{"step": meta["step"], "meta": meta} - def reset(self): + def reset(self, seed=None, options=None): """ Reset the environment state to start a new episode. Returns: - obs: The initial observation after resetting the environment. """ + super().reset(seed=seed,options=options) # Reset internal simulator state self.simulator.reset_state() # Reset the environment's state and return the initial observation obs = self.state.reset() - # if recording is enabled, save the recording and reset the state list if self.recording_enabled: self.save_recording() - - return obs + + # info is necessary for the gym environment, but useless at the moment + info = {"info": "test"} + return obs, info def _prepare_visualizable_state(self): # Prepare action visualization, if any action was executed @@ -263,27 +266,6 @@ def save_recording(self, filename: str = None): logger.info("Reset state list") self.recorded_states = [] - def seed(self, seed=None): - """ - Set the seed for this env's random number generator(s). - - Note: - Some environments use multiple pseudorandom number generators. - We want to capture all such seeds used in order to ensure that - there aren't accidental correlations between multiple generators. - - Returns: - list: Returns the list of seeds used in this env's random - number generators. The first value in the list should be the - "main" seed, or the value which a reproducer should pass to - 'seed'. Often, the main seed equals the provided 'seed', but - this won't be true if seed=None, for example. - - TODO: validate this method - """ - self.np_random, seed = seeding.np_random(seed) - return [seed] - def exit(self): """ Clean up and exit the simulation UI, if it exists. From 2eba09b4a06d83c7c9f2391c36c39868e45cf4ce Mon Sep 17 00:00:00 2001 From: ll7 Date: Wed, 28 Aug 2024 19:56:25 +0200 Subject: [PATCH 02/23] add punish_action_reward - punish changes in the action to get a smoother policy --- robot_sf/gym_env/reward.py | 48 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 48 insertions(+) diff --git a/robot_sf/gym_env/reward.py b/robot_sf/gym_env/reward.py index dd0c4dc..8846611 100644 --- a/robot_sf/gym_env/reward.py +++ b/robot_sf/gym_env/reward.py @@ -1,3 +1,9 @@ +""" +This module defines the reward function for the robot environment. +""" + +import numpy as np + def simple_reward( meta: dict, max_episode_step_discount: float=-0.1, @@ -34,3 +40,45 @@ def simple_reward( reward += reach_waypoint_reward return reward + +def punish_action_reward( + meta: dict, + max_episode_step_discount: float=-0.1, + ped_coll_penalty: float=-5, + obst_coll_penalty: float=-2, + reach_waypoint_reward: float=1, + punish_action: bool=True, + punish_action_penalty: float=-0.1 + ) -> float: + """ + Calculate the reward for the robot's current state. + + Parameters: + meta (dict): Metadata containing information about the robot's current state. + max_episode_step_discount (float): Discount factor for each step in the episode. + ped_coll_penalty (float): Penalty for colliding with a pedestrian. + obst_coll_penalty (float): Penalty for colliding with an obstacle. + reach_waypoint_reward (float): Reward for reaching a waypoint. + punish_action (bool): Whether to punish the robot for taking actions. + punish_action_penalty (float): Penalty for taking actions. + + Returns: + float: The calculated reward. + """ + + # Initialize reward with a discount based on the maximum simulation steps + reward = simple_reward( + meta, + max_episode_step_discount, + ped_coll_penalty, + obst_coll_penalty, + reach_waypoint_reward + ) + + # punish the robot taking a different action from the last action + if punish_action and meta["last_action"] is not None: + action_diff = np.linalg.norm(np.array(meta["action"]) - np.array(meta["last_action"])) + if action_diff > 0: + reward += punish_action_penalty * action_diff + + return reward From 13ef7ecf26ec6e7711171512c9728ce7adf9930e Mon Sep 17 00:00:00 2001 From: ll7 Date: Wed, 28 Aug 2024 19:57:05 +0200 Subject: [PATCH 03/23] extend the reward dictionary to include information about the action taken by the robot --- robot_sf/gym_env/robot_env.py | 16 +++++++++++++--- 1 file changed, 13 insertions(+), 3 deletions(-) diff --git a/robot_sf/gym_env/robot_env.py b/robot_sf/gym_env/robot_env.py index 718d698..84d95d4 100644 --- a/robot_sf/gym_env/robot_env.py +++ b/robot_sf/gym_env/robot_env.py @@ -147,18 +147,26 @@ def step(self, action): # Get updated observation obs = self.state.step() # Fetch metadata about the current state - meta = self.state.meta_dict() + reward_dict = self.state.meta_dict() + # add the action space to dict + reward_dict["action_space"] = self.action_space + # add action to dict + reward_dict["action"] = action + # Add last_action to reward_dict + reward_dict["last_action"] = self.last_action # Determine if the episode has reached terminal state term = self.state.is_terminal # Compute the reward using the provided reward function - reward = self.reward_func(meta) + reward = self.reward_func(reward_dict) + # Update last_action for next step + self.last_action = action # if recording is enabled, record the state if self.recording_enabled: self.record() # observation, reward, terminal, truncated,info - return obs, reward, term, False,{"step": meta["step"], "meta": meta} + return obs, reward, term, False,{"step": reward_dict["step"], "meta": reward_dict} def reset(self, seed=None, options=None): """ @@ -168,6 +176,8 @@ def reset(self, seed=None, options=None): - obs: The initial observation after resetting the environment. """ super().reset(seed=seed,options=options) + # Reset last_action + self.last_action = None # Reset internal simulator state self.simulator.reset_state() # Reset the environment's state and return the initial observation From b4e41885a3ad0576d7f7363eaa3e2680b665e7aa Mon Sep 17 00:00:00 2001 From: ll7 Date: Wed, 28 Aug 2024 19:57:38 +0200 Subject: [PATCH 04/23] create new train script for ppo with action punish --- .../PPO_training/train_ppo_punish_action.py | 56 +++++++++++++++++++ 1 file changed, 56 insertions(+) create mode 100644 scripts/PPO_training/train_ppo_punish_action.py diff --git a/scripts/PPO_training/train_ppo_punish_action.py b/scripts/PPO_training/train_ppo_punish_action.py new file mode 100644 index 0000000..d6271c3 --- /dev/null +++ b/scripts/PPO_training/train_ppo_punish_action.py @@ -0,0 +1,56 @@ +from stable_baselines3 import PPO +from stable_baselines3.common.env_util import make_vec_env +from stable_baselines3.common.vec_env import SubprocVecEnv +from stable_baselines3.common.callbacks import CheckpointCallback, CallbackList + +from robot_sf.gym_env.robot_env import RobotEnv +from robot_sf.gym_env.env_config import EnvSettings +from robot_sf.feature_extractor import DynamicsExtractor +from robot_sf.tb_logging import DrivingMetricsCallback +from robot_sf.gym_env.reward import punish_action_reward + + +def training(): + n_envs = 32 + ped_densities = [0.01, 0.02, 0.04, 0.08] + difficulty = 2 + + + def make_env(): + config = EnvSettings() + config.sim_config.ped_density_by_difficulty = ped_densities + config.sim_config.difficulty = difficulty + return RobotEnv( + config, + reward_func=punish_action_reward + ) + + env = make_vec_env(make_env, n_envs=n_envs, vec_env_cls=SubprocVecEnv) + + policy_kwargs = dict(features_extractor_class=DynamicsExtractor) + model = PPO( + "MultiInputPolicy", + env, + tensorboard_log="./logs/ppo_logs/", + policy_kwargs=policy_kwargs + ) + save_model_callback = CheckpointCallback( + 500_000 // n_envs, + "./model/backup", + "ppo_model" + ) + collect_metrics_callback = DrivingMetricsCallback(n_envs) + combined_callback = CallbackList( + [save_model_callback, collect_metrics_callback] + ) + + model.learn( + total_timesteps=10_000, + progress_bar=True, + callback=combined_callback + ) + model.save("./model/ppo_model") + + +if __name__ == '__main__': + training() From d876549ef049addfb777bed9fb55bb76c2724844 Mon Sep 17 00:00:00 2001 From: ll7 Date: Wed, 28 Aug 2024 20:06:25 +0200 Subject: [PATCH 05/23] remove setting last action too early --- robot_sf/gym_env/robot_env.py | 1 - 1 file changed, 1 deletion(-) diff --git a/robot_sf/gym_env/robot_env.py b/robot_sf/gym_env/robot_env.py index 84d95d4..8bc44a2 100644 --- a/robot_sf/gym_env/robot_env.py +++ b/robot_sf/gym_env/robot_env.py @@ -141,7 +141,6 @@ def step(self, action): """ # Process the action through the simulator action = self.simulator.robots[0].parse_action(action) - self.last_action = action # Perform simulation step self.simulator.step_once([action]) # Get updated observation From e85ac16c92e3cd29c7616e6ecd75c94ea64fac07 Mon Sep 17 00:00:00 2001 From: ll7 Date: Wed, 28 Aug 2024 20:06:44 +0200 Subject: [PATCH 06/23] increase timesteps to be trained --- scripts/PPO_training/train_ppo_punish_action.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/PPO_training/train_ppo_punish_action.py b/scripts/PPO_training/train_ppo_punish_action.py index d6271c3..f085b72 100644 --- a/scripts/PPO_training/train_ppo_punish_action.py +++ b/scripts/PPO_training/train_ppo_punish_action.py @@ -45,7 +45,7 @@ def make_env(): ) model.learn( - total_timesteps=10_000, + total_timesteps=10_000_000, progress_bar=True, callback=combined_callback ) From eec41b09d627f65c16b623b59a35cdbfeee94f6c Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Wed, 11 Sep 2024 15:43:39 +0200 Subject: [PATCH 07/23] Add git_submodule.sh script for recursive submodule update --- git_submodule.sh | 4 ++++ 1 file changed, 4 insertions(+) create mode 100755 git_submodule.sh diff --git a/git_submodule.sh b/git_submodule.sh new file mode 100755 index 0000000..97ad086 --- /dev/null +++ b/git_submodule.sh @@ -0,0 +1,4 @@ +#!/bin/bash +# if you forgot to clone recursively, run this script + +git submodule update --init --recursive \ No newline at end of file From 9778259b000efa286fb239e1e42b8f03b9863a37 Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Wed, 11 Sep 2024 15:44:14 +0200 Subject: [PATCH 08/23] chore: Add SLURM user queue script This commit adds a new script, `user_queue.sh`, to the SLURM directory. The script allows users to view their own job queue by running the `squeue -u $USER` command. --- SLURM/user_queue.sh | 3 +++ 1 file changed, 3 insertions(+) create mode 100755 SLURM/user_queue.sh diff --git a/SLURM/user_queue.sh b/SLURM/user_queue.sh new file mode 100755 index 0000000..08fe4f1 --- /dev/null +++ b/SLURM/user_queue.sh @@ -0,0 +1,3 @@ +#! /bin/bash + +squeue -u $USER From 904d4fe7245c1332a4903a83e61923e9713f2feb Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Wed, 11 Sep 2024 15:44:59 +0200 Subject: [PATCH 09/23] chore: Add SLURM training script This commit adds a new SLURM training script, `slurm_train.sl`, which includes the necessary SLURM directives and commands to run a Python training script on a GPU node. The script sets the job name, partition, time limit, memory per CPU, number of CPUs, and GPU resources. It also loads the required modules and activates the specified conda environment. Finally, it runs the `slurm_PPO_robot_sf.py` Python script using `srun`. --- SLURM/slurm_train.sl | 30 ++++++++++++++++++++++++++++++ 1 file changed, 30 insertions(+) create mode 100644 SLURM/slurm_train.sl diff --git a/SLURM/slurm_train.sl b/SLURM/slurm_train.sl new file mode 100644 index 0000000..f83594d --- /dev/null +++ b/SLURM/slurm_train.sl @@ -0,0 +1,30 @@ +#!/usr/bin/env bash + +#SBATCH --job-name=pyton-test-job +#SBATCH --partition=epyc-gpu-test +#SBATCH --time=05:00:00 + +# Request memory per CPU +#SBATCH --mem-per-cpu=2G +# Request n CPUs for your task. +#SBATCH --cpus-per-task=64 +# Request GPU Ressources (model:number) +#SBATCH --gpus=a100:1 + +# Clear all interactively loaded modules +module purge + +# Load a python package manager +module load cuda anaconda # or micromamba or condaforge + +# Activate a certain environment +conda activate conda_env + +# set number of OpenMP threads (i.e. for numpy, etc...) +# export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK +# if you are adding your own level of parallelzation, you +# probably want to set OMP_NUM_THREADS=1 instead, in order +# to prevent the creation of too many threads (massive slowdown!) + +# No need to pass number of tasks to srun +srun python3 slurm_PPO_robot_sf.py From 1e1c3a443526a0e2cec0f8c34996e8d55210be19 Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Wed, 11 Sep 2024 15:45:58 +0200 Subject: [PATCH 10/23] chore: Update SLURM training script to include PPO training for robot_sf The SLURM training script `slurm_PPO_robot_sf.py` has been added to the repository. This script is used to train a PPO model on the robot_sf environment. It includes the necessary SLURM directives and commands to run the training script on a GPU node. The script sets the job name, partition, time limit, memory per CPU, number of CPUs, and GPU resources. It also loads the required modules and activates the specified conda environment. Finally, it runs the PPO training with the specified parameters. --- SLURM/slurm_PPO_robot_sf.py | 70 +++++++++++++++++++++++++++++++++++++ 1 file changed, 70 insertions(+) create mode 100644 SLURM/slurm_PPO_robot_sf.py diff --git a/SLURM/slurm_PPO_robot_sf.py b/SLURM/slurm_PPO_robot_sf.py new file mode 100644 index 0000000..ed50811 --- /dev/null +++ b/SLURM/slurm_PPO_robot_sf.py @@ -0,0 +1,70 @@ +"train a robot in robot_sf on Licca Server" + +""" +This script is used to train a PPO model on the CartPole-v1 environment. +""" +import sys +from datetime import datetime + +import gymnasium as gym +from loguru import logger + +from stable_baselines3 import PPO +from stable_baselines3.common.env_util import make_vec_env +from stable_baselines3.common.vec_env import SubprocVecEnv +from stable_baselines3.common.callbacks import CheckpointCallback, CallbackList + +from robot_sf.gym_env.robot_env import RobotEnv +from robot_sf.gym_env.env_config import EnvSettings +from robot_sf.feature_extractor import DynamicsExtractor +from robot_sf.tb_logging import DrivingMetricsCallback + + +def training(): + n_envs = 64 + ped_densities = [0.01, 0.02, 0.04, 0.08] + difficulty = 2 + + + def make_env(): + config = EnvSettings() + config.sim_config.ped_density_by_difficulty = ped_densities + config.sim_config.difficulty = difficulty + return RobotEnv(config) + + env = make_vec_env(make_env, n_envs=n_envs, vec_env_cls=SubprocVecEnv) + + policy_kwargs = dict(features_extractor_class=DynamicsExtractor) + model = PPO( + "MultiInputPolicy", + env, + tensorboard_log="./logs/ppo_logs/", + policy_kwargs=policy_kwargs + ) + save_model_callback = CheckpointCallback( + 500_000 // n_envs, + "./model/backup", + "ppo_model" + ) + collect_metrics_callback = DrivingMetricsCallback(n_envs) + combined_callback = CallbackList( + [save_model_callback, collect_metrics_callback] + ) + + logger.info("start learning") + model.learn( + total_timesteps=6_000_000, + progress_bar=True, + callback=combined_callback + ) + logger.info("save model") + model.save("./model/ppo_model") + + +if __name__ == '__main__': + logger.info(f"python path: {sys.executable}") + logger.info(f"python version: {sys.version}") + + logger.info("start training") + training() + logger.info("end training") From 0a76b3eade9b5a8c22f3755bd59c66d1bb0de5d9 Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Wed, 11 Sep 2024 15:46:52 +0200 Subject: [PATCH 11/23] feat: Update SLURM training script to specify slurm server for robot_sf training --- SLURM/slurm_PPO_robot_sf.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/SLURM/slurm_PPO_robot_sf.py b/SLURM/slurm_PPO_robot_sf.py index ed50811..ff0c861 100644 --- a/SLURM/slurm_PPO_robot_sf.py +++ b/SLURM/slurm_PPO_robot_sf.py @@ -1,4 +1,4 @@ -"train a robot in robot_sf on Licca Server" +"train a robot in robot_sf on a slurm server" """ This script is used to train a PPO model on the CartPole-v1 environment. From 964b073776c541c738f9583e5c134d2812a69ab1 Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Wed, 11 Sep 2024 15:47:33 +0200 Subject: [PATCH 12/23] chore: Add .gitignore file for SLURM directory for *.out files --- SLURM/.gitignore | 1 + 1 file changed, 1 insertion(+) create mode 100644 SLURM/.gitignore diff --git a/SLURM/.gitignore b/SLURM/.gitignore new file mode 100644 index 0000000..fa92975 --- /dev/null +++ b/SLURM/.gitignore @@ -0,0 +1 @@ +*.out \ No newline at end of file From 0e3ba9d0db57adfdadb302e399ca846d06057f0e Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Wed, 11 Sep 2024 15:47:52 +0200 Subject: [PATCH 13/23] chore: Add SLURM load_module.sh script --- SLURM/load_module.sh | 8 ++++++++ 1 file changed, 8 insertions(+) create mode 100755 SLURM/load_module.sh diff --git a/SLURM/load_module.sh b/SLURM/load_module.sh new file mode 100755 index 0000000..016b127 --- /dev/null +++ b/SLURM/load_module.sh @@ -0,0 +1,8 @@ +#! /bin/bash + +module purge + +module load anaconda cuda + +conda activate conda_env + From 09d72697eaadddcd6a998ccde9ec8f18797e2ee9 Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Fri, 13 Sep 2024 16:15:10 +0200 Subject: [PATCH 14/23] train 10m steps --- SLURM/slurm_PPO_robot_sf.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/SLURM/slurm_PPO_robot_sf.py b/SLURM/slurm_PPO_robot_sf.py index ff0c861..e2b99d1 100644 --- a/SLURM/slurm_PPO_robot_sf.py +++ b/SLURM/slurm_PPO_robot_sf.py @@ -53,7 +53,7 @@ def make_env(): logger.info("start learning") model.learn( - total_timesteps=6_000_000, + total_timesteps=10_000_000, progress_bar=True, callback=combined_callback ) From c280e3b0056744d56e5ae50253c687661ec40a76 Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Fri, 13 Sep 2024 16:15:24 +0200 Subject: [PATCH 15/23] add sbatch note --- SLURM/readme.md | 5 +++++ 1 file changed, 5 insertions(+) create mode 100644 SLURM/readme.md diff --git a/SLURM/readme.md b/SLURM/readme.md new file mode 100644 index 0000000..d4c5c89 --- /dev/null +++ b/SLURM/readme.md @@ -0,0 +1,5 @@ +# SLURM + +```bash +sbatch slurm_train.sl +``` From 39c81aeeb385e010d2487b2d465b23acab003315 Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Tue, 17 Sep 2024 16:59:33 +0200 Subject: [PATCH 16/23] chore: Add .cursorrules file The `.cursorrules` file has been added to the repository. This file contains a description of the AI assistant's approach to Python development, including project structure, modular design, configuration management, error handling, testing, documentation, and more. --- .cursorrules | 1 + 1 file changed, 1 insertion(+) create mode 100644 .cursorrules diff --git a/.cursorrules b/.cursorrules new file mode 100644 index 0000000..9118145 --- /dev/null +++ b/.cursorrules @@ -0,0 +1 @@ +You are an AI assistant specialized in Python development. Your approach emphasizes: Clear project structure with separate directories for source code, tests, docs, and config.Modular design with distinct files for models, services, controllers, and utilities.Configuration management using environment variables. Robust error handling and logging, including context capture. Comprehensive testing with pytest. Detailed documentation using docstrings and README files.Dependency management via requirements.txt and virtual environments. CI/CD implementation with GitHub Actions friendly coding practices: You provide code snippets and explanations tailored to these principles, optimizing for clarity and AI-assisted development. Follow the following rules:For any python file, be sure to ALWAYS add typing annotations to each function or class. Be sure to include return types when necessary. Add descriptive docstrings to all python functions and classes as well. Please use pep257 convention. Update existing docstrings if need be. Make sure you keep any comments that exist in a file. When writing tests, make sure that you ONLY use pytest or pytest plugins, do NOT use the unittest module. All tests should have typing annotations as well. All tests should be in ./tests. Be sure to create all necessary files and folders. If you are creating files inside of ./tests, be sure to make a init.py file if one does not exist. All tests should be fully annotated and should contain docstrings. \ No newline at end of file From 155252ec041925276e2b00edfe05ecd3cc304126 Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Tue, 17 Sep 2024 16:59:59 +0200 Subject: [PATCH 17/23] chore: Update SLURM training script to specify job name and partition for robot_sf training --- SLURM/slurm_train.sl | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/SLURM/slurm_train.sl b/SLURM/slurm_train.sl index f83594d..87800c5 100644 --- a/SLURM/slurm_train.sl +++ b/SLURM/slurm_train.sl @@ -1,8 +1,8 @@ #!/usr/bin/env bash -#SBATCH --job-name=pyton-test-job -#SBATCH --partition=epyc-gpu-test -#SBATCH --time=05:00:00 +#SBATCH --job-name=robot-sf +#SBATCH --partition=epyc-gpu +#SBATCH --time=10:00:00 # Request memory per CPU #SBATCH --mem-per-cpu=2G From 42aa3a2b282f372dcb65a8590a7b4509727e4b4c Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Tue, 17 Sep 2024 17:07:19 +0200 Subject: [PATCH 18/23] add retrained 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z4)YVv!dfFPw!mIeOpxUNnE~sh6W=Y%W)ZZ^e^JzraFxT3fsvsyVuJKX5&i(jim#j@ z_a`nWILv>!|4QEw;T(QMus?;zinrA&{2RLUFM%K*VXplvAGJCKVdnkGd>Pj96~@}t Jp Date: Tue, 17 Sep 2024 17:07:36 +0200 Subject: [PATCH 19/23] do not ignore global models --- .gitignore | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index 94c06cc..2dc2938 100644 --- a/.gitignore +++ b/.gitignore @@ -11,7 +11,8 @@ build file.log images logs -model +# model +SLURM/model profile.json profiles pysf_tests From 0e4652917b7da45444c6ff1a062588c58ce52eb5 Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Tue, 17 Sep 2024 17:38:19 +0200 Subject: [PATCH 20/23] chore: Refactor SLURM training script for robot_sf The SLURM training script `slurm_PPO_robot_sf.py` has been refactored to improve code readability and maintainability. The unnecessary import statements have been removed, and the script now follows PEP 8 style guidelines. This refactor does not change the functionality of the script, but it enhances the overall quality of the codebase. --- SLURM/slurm_PPO_robot_sf.py | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/SLURM/slurm_PPO_robot_sf.py b/SLURM/slurm_PPO_robot_sf.py index e2b99d1..5053c48 100644 --- a/SLURM/slurm_PPO_robot_sf.py +++ b/SLURM/slurm_PPO_robot_sf.py @@ -1,12 +1,7 @@ -"train a robot in robot_sf on a slurm server" +"""train a robot in robot_sf on a slurm server""" -""" -This script is used to train a PPO model on the CartPole-v1 environment. -""" import sys -from datetime import datetime -import gymnasium as gym from loguru import logger from stable_baselines3 import PPO From defd7a5160044c6179ee04fea3e69a97b19c0113 Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Mon, 23 Sep 2024 08:38:35 +0200 Subject: [PATCH 21/23] chore: Update env_test.py to handle termination and truncation in test_can_simulate_with_pedestrians() --- tests/env_test.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/tests/env_test.py b/tests/env_test.py index db926e9..c14609d 100644 --- a/tests/env_test.py +++ b/tests/env_test.py @@ -13,7 +13,7 @@ def test_can_return_valid_observation(): drive_state_spec: spaces.Box = env.observation_space[OBS_DRIVE_STATE] lidar_state_spec: spaces.Box = env.observation_space[OBS_RAYS] - obs = env.reset() + obs, info = env.reset() assert isinstance(obs, dict) assert OBS_DRIVE_STATE in obs and OBS_RAYS in obs @@ -27,6 +27,7 @@ def test_can_simulate_with_pedestrians(): env.reset() for _ in range(total_steps): rand_action = env.action_space.sample() - _, _, done, _ = env.step(rand_action) + _, _, terminated, truncated, _ = env.step(rand_action) + done = terminated or truncated if done: env.reset() From 825c9ff150acd3165d1a64c933fb396466dc1bb5 Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Mon, 23 Sep 2024 08:38:42 +0200 Subject: [PATCH 22/23] Update sb3_test.py to include additional information in the observation variable during reset --- tests/sb3_test.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/sb3_test.py b/tests/sb3_test.py index 52c8fa7..054c529 100644 --- a/tests/sb3_test.py +++ b/tests/sb3_test.py @@ -23,7 +23,7 @@ def test_can_load_model_snapshot(): inf_env = RobotEnv() model2 = PPO.load(MODEL_PATH, env=inf_env) - obs = inf_env.reset() + obs, info = inf_env.reset() action, _ = model2.predict(obs, deterministic=True) assert action.shape == inf_env.action_space.shape From f4f0ce0cb5931df50c9eba2cc0db8fb0dfeb87c3 Mon Sep 17 00:00:00 2001 From: Lennart Luttkus Date: Mon, 23 Sep 2024 08:38:56 +0200 Subject: [PATCH 23/23] chore: Update robot_env.py --- robot_sf/gym_env/robot_env.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/robot_sf/gym_env/robot_env.py b/robot_sf/gym_env/robot_env.py index 8bc44a2..43a36e0 100644 --- a/robot_sf/gym_env/robot_env.py +++ b/robot_sf/gym_env/robot_env.py @@ -165,7 +165,7 @@ def step(self, action): self.record() # observation, reward, terminal, truncated,info - return obs, reward, term, False,{"step": reward_dict["step"], "meta": reward_dict} + return obs, reward, term, False, {"step": reward_dict["step"], "meta": reward_dict} def reset(self, seed=None, options=None): """