Merge branch 'main' of https://github.com/boettiger-lab/rl4caribou

.gitignore

@@ -158,3 +158,7 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
+
+# output
+saved_agents/
+*.zip

README.md

@@ -7,3 +7,21 @@ A DRL-based approach to Caribou conservation based on the methods of the
 
 A three-species foodweb is considered, including interactions between Caribou, Elk and Wolf populations.
 
+## Installation
+
+```
+git clone https://github.com/boettiger-lab/rl4caribou.git
+cd rl4caribou
+pip install .
+```
+## Train an agent
+
+```
+python scripts/train.py -f path/to/config/file.yml -id "string saving id" [-pb if you want a progress bar displayed]
+```
+
+An quick example:
+
+```
+python scripts/train.py -f hyperpars/example.yml -id "my_first_agent" -pb
+```

scripts/train.py

@@ -3,7 +3,7 @@
 parser = argparse.ArgumentParser()
 parser.add_argument("-f", "--file", help="Path config file", type=str)
 parser.add_argument("-pb", "--progress_bar", help="Use  progress bar for training", type=bool, default=True)
-parser.add_argument("-id", "--identifier", help="ID string for saving the agent", type=bool, default="0")
+parser.add_argument("-id", "--identifier", help="ID string for saving the agent", type=str, default="0")
 args = parser.parse_args()
 
 import rl4caribou
@@ -21,7 +21,11 @@
 # training
 #
 from rl4caribou.utils import sb3_train    
-model_save_id, train_options = sb3_train(abs_filepath, progress_bar=args.progress_bar)
+model_save_id, train_options = sb3_train(
+    abs_filepath, 
+    progress_bar=args.progress_bar, 
+    identifier=args.identifier,
+)
 model_save_id = model_save_id + "_id_" + args.identifier
 
 # hugging face

src/rl4caribou/utils/sb3.py

@@ -36,7 +36,8 @@ def algorithm(algo):
         'tqc': TQC,
     }
     return algos[algo]
-def sb3_train(config_file, **kwargs):
+
+def sb3_train(config_file, progress_bar=True, identifier="0", **kwargs):
     with open(config_file, "r") as stream:
         options = yaml.safe_load(stream)
         options = {**options, **kwargs}
@@ -65,15 +66,14 @@ def sb3_train(config_file, **kwargs):
     ALGO = algorithm(options["algo"])
     # if "id" in options:
     #     options["id"] = "-" + options["id"]
-    model_id = options["algo"] + "-" + options["env_id"] # + options.get("id", "")
+    model_id = options["algo"] + "-" + options["env_id"] + "_id_" + identifier
     save_id = os.path.join(options["save_path"], model_id)
 
     model = ALGO(
         env=env,
         **options['algo_config']
     )
 
-    progress_bar = options.get("progress_bar", False)
     model.learn(total_timesteps=options["total_timesteps"], tb_log_name=model_id, progress_bar=progress_bar)
 
     os.makedirs(options["save_path"], exist_ok=True)