Update evo_transformer.py

evo_transformer.py

@@ -1,6 +1,6 @@
 # evo_transformer.py
+
 import random
-import pandas as pd
 import json
 
 class EvoTransformer:
@@ -25,31 +25,38 @@ class EvoTransformer:
         elif trait == "ffn_dim":
             new_config[trait] = random.choice([512, 1024, 2048])
         elif trait == "dropout":
-            new_config[trait] = round(min(max(0.0, new_config[trait] + random.uniform(-0.05, 0.05)), 0.5), 2)
+            change = round(random.uniform(-0.05, 0.05), 2)
+            new_config[trait] = round(min(max(0.0, new_config[trait] + change), 0.5), 2)
         elif trait == "memory":
             new_config[trait] = not new_config[trait]
 
         self.config = new_config
         self.history.append(new_config.copy())
 
-    def evolve(self, generations=5):
+    def evolve(self, generations=3):
         for _ in range(generations):
             self.mutate()
 
+    def get_history(self):
+        return self.history
+
     def evaluate(self):
-        # Simulated accuracy and parameter estimate
-        accuracy = round(random.uniform(0.85, 0.95), 4)
-        params = self.estimate_params()
-        return accuracy, params
+        # Simulated accuracy and parameter count
+        accuracy = round(0.8 + random.uniform(0.01, 0.15), 4)
+        return {
+            "accuracy": accuracy,
+            "params": self.estimate_params()
+        }
 
     def estimate_params(self):
-        return round(10 + self.config["layers"] * self.config["ffn_dim"] * 0.001, 2)
+        # Lightweight param estimate formula (not real count)
+        multiplier = 1.0 + (0.5 if self.config["memory"] else 0.0)
+        return int(self.config["layers"] * self.config["ffn_dim"] * multiplier)
 
-    def get_history_df(self):
-        return pd.DataFrame(self.history)
+    def export_csv(self):
+        import pandas as pd
+        df = pd.DataFrame(self.history)
+        return df.to_csv(index=False)
 
-    def get_history_json(self):
+    def export_json(self):
         return json.dumps(self.history, indent=2)
-
-    def get_final_config(self):
-        return self.config