Update evo_transformer.py

evo_transformer.py

@@ -1,5 +1,6 @@
+# evo_transformer.py
 import random
-import matplotlib.pyplot as plt
+import json
 
 class EvoTransformer:
     def __init__(self, config=None):
@@ -15,7 +16,7 @@ class EvoTransformer:
     def mutate(self):
         new_config = self.config.copy()
         trait = random.choice(list(new_config.keys()))
-
+        
         if trait == "layers":
             new_config[trait] = max(1, new_config[trait] + random.choice([-1, 1]))
         elif trait == "attention_heads":
@@ -30,7 +31,7 @@ class EvoTransformer:
         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()
 
@@ -38,38 +39,19 @@ class EvoTransformer:
         return self.history
 
     def evaluate(self):
-        # Simulated accuracy for demo
         score = round(random.uniform(0.85, 0.95), 4)
-        return {
-            "accuracy": score,
-            "params": self.estimate_params()
-        }
+        return {"accuracy": score, "params": self.estimate_params()}
 
     def estimate_params(self):
         return round(10 + self.config["layers"] * self.config["ffn_dim"] * 0.001, 2)
 
-    def plot_evolution(self):
-        layers = [cfg["layers"] for cfg in self.history]
-        heads = [cfg["attention_heads"] for cfg in self.history]
-        ffn_dims = [cfg["ffn_dim"] for cfg in self.history]
-
-        plt.figure(figsize=(10, 6))
-        plt.plot(layers, label="Layers", marker='o', color='orange')
-        plt.plot(heads, label="Attention Heads", marker='s', color='blue')
-        plt.plot(ffn_dims, label="FFN Dim", marker='^', color='green')
-        plt.xlabel("Generation")
-        plt.ylabel("Value")
-        plt.title("Evolution of Traits")
-        plt.legend()
-        plt.grid(True)
-        plt.tight_layout()
-        plt.show()
-
+    def export_csv(self):
+        headers = list(self.history[0].keys())
+        lines = [",".join(headers)]
+        for config in self.history:
+            line = ",".join([str(config[h]) for h in headers])
+            lines.append(line)
+        return "\n".join(lines)
 
-# Run test locally
-if __name__ == "__main__":
-    evo = EvoTransformer()
-    evo.evolve(generations=8)
-    evo.plot_evolution()
-    print("Final Config:", evo.config)
-    print("Evaluation:", evo.evaluate())
+    def export_json(self):
+        return json.dumps(self.history, indent=2)