Modifies workflow scripts to generate random seed when seed=-1 (#1048)

# Description

This change adds support to the train.py workflow scripts to support
setting seed=-1 to generate a random seed. Previously, setting seed to
-1 would cause errors to be thrown from RL libraries due to negative
seed values.

## Type of change

- Bug fix (non-breaking change which fixes an issue)

## Checklist

- [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with
`./isaaclab.sh --format`
- [ ] I have made corresponding changes to the documentation
- [x] My changes generate no new warnings
- [ ] I have added tests that prove my fix is effective or that my
feature works
- [ ] I have updated the changelog and the corresponding version in the
extension's `config/extension.toml` file
- [x] I have added my name to the `CONTRIBUTORS.md` or my name already
exists there

source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py

@@ -81,7 +81,7 @@ class DirectMARLEnv:
 
         # set the seed for the environment
         if self.cfg.seed is not None:
-            self.seed(self.cfg.seed)
+            self.cfg.seed = self.seed(self.cfg.seed)
         else:
             carb.log_warn("Seed not set for the environment. The environment creation may not be deterministic.")
 

source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py

@@ -86,7 +86,7 @@ class DirectRLEnv(gym.Env):
 
         # set the seed for the environment
         if self.cfg.seed is not None:
-            self.seed(self.cfg.seed)
+            self.cfg.seed = self.seed(self.cfg.seed)
         else:
             carb.log_warn("Seed not set for the environment. The environment creation may not be deterministic.")
 

source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py

@@ -76,7 +76,7 @@ class ManagerBasedEnv:
 
         # set the seed for the environment
         if self.cfg.seed is not None:
-            self.seed(self.cfg.seed)
+            self.cfg.seed = self.seed(self.cfg.seed)
         else:
             carb.log_warn("Seed not set for the environment. The environment creation may not be deterministic.")
 

source/standalone/workflows/rl_games/train.py

@@ -47,6 +47,7 @@ simulation_app = app_launcher.app
 import gymnasium as gym
 import math
 import os
+import random
 from datetime import datetime
 
 from rl_games.common import env_configurations, vecenv
@@ -76,6 +77,10 @@ def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg | DirectMARLEnvCfg, agen
     env_cfg.scene.num_envs = args_cli.num_envs if args_cli.num_envs is not None else env_cfg.scene.num_envs
     env_cfg.sim.device = args_cli.device if args_cli.device is not None else env_cfg.sim.device
 
+    # randomly sample a seed if seed = -1
+    if args_cli.seed == -1:
+        args_cli.seed = random.randint(0, 10000)
+
     agent_cfg["params"]["seed"] = args_cli.seed if args_cli.seed is not None else agent_cfg["params"]["seed"]
     agent_cfg["params"]["config"]["max_epochs"] = (
         args_cli.max_iterations if args_cli.max_iterations is not None else agent_cfg["params"]["config"]["max_epochs"]

source/standalone/workflows/rsl_rl/cli_args.py

@@ -6,6 +6,7 @@
 from __future__ import annotations
 
 import argparse
+import random
 from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
@@ -68,6 +69,9 @@ def update_rsl_rl_cfg(agent_cfg: RslRlOnPolicyRunnerCfg, args_cli: argparse.Name
     """
     # override the default configuration with CLI arguments
     if hasattr(args_cli, "seed") and args_cli.seed is not None:
+        # randomly sample a seed if seed = -1
+        if args_cli.seed == -1:
+            args_cli.seed = random.randint(0, 10000)
         agent_cfg.seed = args_cli.seed
     if args_cli.resume is not None:
         agent_cfg.resume = args_cli.resume

source/standalone/workflows/sb3/train.py

@@ -46,6 +46,7 @@ simulation_app = app_launcher.app
 import gymnasium as gym
 import numpy as np
 import os
+import random
 from datetime import datetime
 
 from stable_baselines3 import PPO
@@ -71,6 +72,10 @@ from omni.isaac.lab_tasks.utils.wrappers.sb3 import Sb3VecEnvWrapper, process_sb
 @hydra_task_config(args_cli.task, "sb3_cfg_entry_point")
 def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg | DirectMARLEnvCfg, agent_cfg: dict):
     """Train with stable-baselines agent."""
+    # randomly sample a seed if seed = -1
+    if args_cli.seed == -1:
+        args_cli.seed = random.randint(0, 10000)
+
     # override configurations with non-hydra CLI arguments
     env_cfg.scene.num_envs = args_cli.num_envs if args_cli.num_envs is not None else env_cfg.scene.num_envs
     agent_cfg["seed"] = args_cli.seed if args_cli.seed is not None else agent_cfg["seed"]

source/standalone/workflows/skrl/train.py

@@ -63,6 +63,7 @@ simulation_app = app_launcher.app
 
 import gymnasium as gym
 import os
+import random
 from datetime import datetime
 
 import skrl
@@ -119,9 +120,14 @@ def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg | DirectMARLEnvCfg, agen
     if args_cli.ml_framework.startswith("jax"):
         skrl.config.jax.backend = "jax" if args_cli.ml_framework == "jax" else "numpy"
 
-    # set the environment seed
+    # randomly sample a seed if seed = -1
+    if args_cli.seed == -1:
+        args_cli.seed = random.randint(0, 10000)
+
+    # set the agent and environment seed from command line
     # note: certain randomization occur in the environment initialization so we set the seed here
-    env_cfg.seed = args_cli.seed if args_cli.seed is not None else agent_cfg["seed"]
+    agent_cfg["seed"] = args_cli.seed if args_cli.seed is not None else agent_cfg["seed"]
+    env_cfg.seed = agent_cfg["seed"]
 
     # specify directory for logging experiments
     log_root_path = os.path.join("logs", "skrl", agent_cfg["agent"]["experiment"]["directory"])