Create evo_architecture.py

evo_architecture.py

@@ -0,0 +1,51 @@
+# evo_architecture.py
+
+import random
+import json
+import os
+
+GENOME_LOG = "genome_log.csv"
+
+def mutate_genome(base_config):
+    """Randomly mutates one architectural parameter from the base config."""
+    new_config = base_config.copy()
+
+    mutation_type = random.choice(["layers", "ffn_dim", "num_heads", "memory_enabled"])
+
+    if mutation_type == "layers":
+        new_config["num_layers"] = max(2, min(8, new_config["num_layers"] + random.choice([-1, 1])))
+    elif mutation_type == "ffn_dim":
+        new_config["ffn_dim"] = max(256, min(2048, new_config["ffn_dim"] + random.choice([-256, 256])))
+    elif mutation_type == "num_heads":
+        new_config["num_heads"] = max(2, min(12, new_config["num_heads"] + random.choice([-2, 2])))
+    elif mutation_type == "memory_enabled":
+        new_config["memory_enabled"] = not new_config["memory_enabled"]
+
+    return new_config
+
+def log_genome(config, performance=None):
+    """Logs the evolved genome and its score."""
+    header = ["num_layers", "ffn_dim", "num_heads", "memory_enabled", "score"]
+    row = [
+        config["num_layers"],
+        config["ffn_dim"],
+        config["num_heads"],
+        config["memory_enabled"],
+        performance if performance is not None else ""
+    ]
+
+    file_exists = os.path.exists(GENOME_LOG)
+    with open(GENOME_LOG, "a", newline='', encoding='utf-8') as f:
+        import csv
+        writer = csv.writer(f)
+        if not file_exists:
+            writer.writerow(header)
+        writer.writerow(row)
+
+def default_config():
+    return {
+        "num_layers": 6,
+        "ffn_dim": 1024,
+        "num_heads": 8,
+        "memory_enabled": True
+    }