minor changes

config.yaml

@@ -18,6 +18,7 @@ slurm:
 runner: debug
 
 scheduler:
+  total_timesteps: 10000
   repetitions: 3
   agents_per_job: 3
   reps_per_agent: 1
@@ -51,7 +52,6 @@ env:
 
 algo:
   name: PPO
-  total_timesteps: 10000
   policy_name: MlpPolicy
   n_steps: 4096
   vf_coef: 1.0e-5
@@ -67,15 +67,45 @@ pca:
   skip_conditioning: True
   Base_Noise: WHITE
   init_std: 1.0
----
+
 sweep:
-  enable: True
-  method: random,
-  metric:
-    goal: minimize,
-    name: score
+  enable: False
+  method: random
+  #metric:
+  #  goal: minimize
+  #  name: score
   parameters:
-    lel: lol
+    algo.learning_rate:
+      min: 0.0001
+      max: 0.1
+---
+name: sweep
+import: $
+sweep.enable: True
+scheduler.reps_per_agent: 3
+---
+name: McNamo
+import: :DEFAULT
+
+video:
+  length: 10
+
+env:
+  env_args:
+    more_obs: False
+
+algo.name: TRPL
+leaf: False
+---
+name: Leaf
+
+vars:
+  leaf: True
+---
+name: Weird
+import: :McNamo,:Leaf
+
+leaf: True
 ---
 ablative:
   task:

main.py

@@ -1,10 +1,10 @@
-import fancy_gym
-from stable_baselines3 import PPO
-from stable_baselines3.common.monitor import Monitor
-from stable_baselines3.common.vec_env import DummyVecEnv, VecVideoRecorder
+#import fancy_gym
+#from stable_baselines3 import PPO
+#from stable_baselines3.common.monitor import Monitor
+#from stable_baselines3.common.vec_env import DummyVecEnv, VecVideoRecorder
 import wandb
 from wandb.integration.sb3 import WandbCallback
-import gymnasium as gym
+#import gymnasium as gym
 import yaml
 import os
 import random
@@ -31,22 +31,26 @@ PCA = None
 
 
 def load_config(filename, name):
-    config = _load_config(filename, name)
+    config, stack = _load_config(filename, name)
+    print('[i] Merged Configs: ', stack)
     deep_expand_vars(config, config=config)
     consume(config, 'vars', {})
     return config
 
 
-def _load_config(filename, name):
+def _load_config(filename, name, stack=[]):
+    stack.append(f'{filename}:{name}')
     with open(filename, 'r') as f:
         docs = yaml.safe_load_all(f)
         for doc in docs:
             if 'name' in doc:
                 if doc['name'] == name:
                     if 'import' in doc:
-                        imports = reversed(doc['import'].split(','))
+                        imports = doc['import'].split(',')
                         del doc['import']
                         for imp in imports:
+                            if imp[0] == ' ':
+                                imp = imp[1:]
                             if imp == "$":
                                 imp = ':DEFAULT'
                             rel_path, *opt = imp.split(':')
@@ -55,29 +59,22 @@ def _load_config(filename, name):
                             elif len(opt) == 1:
                                 nested_name = opt[0]
                             else:
-                                raise Exception('Malformed import statement. Must be <import file:exp>, <import .:exp> or <import file> for file:DEFAULT.')
+                                raise Exception('Malformed import statement. Must be <import file:exp>, <import :exp>, <import file> for file:DEFAULT or <import $> for :DEFAULT.')
                             nested_path = os.path.normpath(os.path.join(os.path.dirname(filename), rel_path)) if len(rel_path) else filename
-                            child = _load_config(nested_path, nested_name)
+                            child, stack = _load_config(nested_path, nested_name, stack=stack)
                             doc = deep_update(child, doc)
-                    return doc
+                    return doc, stack
         raise Exception(f'Unable to find experiment <{name}> in <{filename}>')
 
 
-def deep_update_old(d, u):
-    for k, v in u.items():
-        if isinstance(v, collections.abc.Mapping):
-            d[k] = deep_update_old(d.get(k, {}), v)
-        else:
-            d[k] = v
-    return d
-
-
 def deep_update(d, u):
     for kstr, v in u.items():
         ks = kstr.split('.')
         head = d
         for k in ks:
             last_head = head
+            if k not in head:
+                head[k] = {}
             head = head[k]
         if isinstance(v, collections.abc.Mapping):
             last_head[ks[-1]] = deep_update(d.get(k, {}), v)
@@ -107,8 +104,8 @@ def deep_expand_vars(dict, **kwargs):
     apply_nested(dict, lambda x: expand_vars(x, **kwargs))
 
 
-def consume(conf, keys, default=None):
-    keys_arr = keys.split('.')
+def consume(conf, key, default=None):
+    keys_arr = key.split('.')
     if len(keys_arr) == 1:
         k = keys_arr[0]
         if default != None:
@@ -133,7 +130,7 @@ def run_local(filename, name, job_num=None):
             project=project
         )
         runnerName, wandbC = consume(config, 'runner'), consume(config, 'wandb', {})
-        wandb.agent(sweep_id, function=partial(run_from_sweep, config, runnerName, project, wandbC), count=config['scheduler']['reps_per_agent'])
+        wandb.agent(sweep_id, function=partial(run_from_sweep, config, runnerName, project, wandbC), count=config['run']['reps_per_agent'])
     else:
         consume(config, 'sweep', {})
         run_single(config)
@@ -232,7 +229,7 @@ def sb3_runner(run, config):
     assert consume(algoC, 'name') == 'PPO'
     policy_name = consume(algoC, 'policy_name')
 
-    total_timesteps = consume(algoC, 'total_timesteps')
+    total_timesteps = config.get('run', {}).get('total_timesteps', {})
 
     model = PPO(policy_name, env, **algoC)
 
@@ -267,8 +264,6 @@ def make_env_func(env_conf):
 Runners = {
     'sb3': sb3_runner,
     'debug': debug_runner
-
-
 }
 
 if __name__ == '__main__':