feat: made checkpoint directory an argument in eval

openfasoc/MLoptimization/eval.py

@@ -16,7 +16,7 @@ def unlookup(norm_spec, goal_spec):
     spec = -1*np.multiply((norm_spec+1), goal_spec)/(norm_spec-1)
     return spec
 
-def evaluate_model():
+def evaluate_model(checkpoint_dir: str = "./last_checkpoint"):
     specs = yaml.safe_load(Path('newnew_eval_3.yaml').read_text())
 
     #training set up
@@ -47,7 +47,7 @@ def evaluate_model():
     args = parser.parse_args()
     env = Envir(env_config=env_config)
 
-    agent = PPO.from_checkpoint("./last_checkpoint")
+    agent = PPO.from_checkpoint(checkpoint_dir)
 
     norm_spec_ref = env.global_g
     spec_num = len(env.specs)