Update evo_transformer.py

evo_transformer.py

@@ -1,16 +1,20 @@
 # evo_transformer.py
 import random
-import json
 
 class EvoTransformer:
     def __init__(self, config=None):
-        self.config = config or {
+        self.default_config = {
             "layers": 4,
             "attention_heads": 4,
             "ffn_dim": 1024,
             "dropout": 0.1,
             "memory": False,
         }
+        self.config = config or self.default_config.copy()
+        self.history = [self.config.copy()]
+
+    def reset(self):
+        self.config = self.default_config.copy()
         self.history = [self.config.copy()]
 
     def mutate(self):
@@ -43,15 +47,4 @@ class EvoTransformer:
         return {"accuracy": score, "params": self.estimate_params()}
 
     def estimate_params(self):
-        return round(self.config["layers"] * self.config["ffn_dim"] * 0.001, 2)
-
-    def save_history(self):
-        csv_path = "evo_history.csv"
-        json_path = "evo_history.json"
-        with open(csv_path, "w") as f:
-            f.write("generation,layers,attention_heads,ffn_dim,dropout,memory\n")
-            for i, cfg in enumerate(self.history):
-                f.write(f"{i+1},{cfg['layers']},{cfg['attention_heads']},{cfg['ffn_dim']},{cfg['dropout']},{cfg['memory']}\n")
-        with open(json_path, "w") as f:
-            json.dump(self.history, f, indent=2)
-        return csv_path, json_path
+        return round(10 + self.config["layers"] * self.config["ffn_dim"] * 1.0, 2)