[fix] Non heuristic moves...

rl/export.py

@@ -0,0 +1,86 @@
+"""Export trained Keras model to TFLite (optionally int8-quantized) for ESP32."""
+
+import os
+import numpy as np
+
+from .game import ConnectFour, ROWS, COLS
+from .config import EXPORT_DIR, QUANTIZE_INT8
+
+
+def representative_dataset():
+    """Generate sample inputs for int8 calibration."""
+    game = ConnectFour()
+    for _ in range(200):
+        game.reset()
+        # Play random moves to get diverse board states
+        moves = np.random.randint(0, min(ROWS * COLS, 20))
+        for _ in range(moves):
+            legal = game.legal_moves()
+            if not legal or game.done:
+                break
+            game.step(np.random.choice(legal))
+        yield [game.get_state()[np.newaxis].astype(np.float32)]
+
+
+def export_tflite(model_path, quantize=None):
+    """Convert a saved Keras model to TFLite.
+
+    Args:
+        model_path: Path to the .keras model file.
+        quantize: Override quantization setting. If None, uses config.QUANTIZE_INT8.
+    """
+    import tensorflow as tf
+
+    if quantize is None:
+        quantize = QUANTIZE_INT8
+
+    os.makedirs(EXPORT_DIR, exist_ok=True)
+
+    model = tf.keras.models.load_model(model_path)
+
+    converter = tf.lite.TFLiteConverter.from_keras_model(model)
+
+    if quantize:
+        converter.optimizations = [tf.lite.Optimize.DEFAULT]
+        converter.representative_dataset = representative_dataset
+        converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
+        converter.inference_input_type = tf.int8
+        converter.inference_output_type = tf.int8
+        suffix = "_int8"
+    else:
+        suffix = "_f32"
+
+    tflite_model = converter.convert()
+
+    out_path = os.path.join(EXPORT_DIR, f"connect4{suffix}.tflite")
+    with open(out_path, "wb") as f:
+        f.write(tflite_model)
+
+    size_kb = len(tflite_model) / 1024
+    print(f"Exported: {out_path} ({size_kb:.1f} KB)")
+
+    # Also export as C header for direct embedding in firmware
+    header_path = os.path.join(EXPORT_DIR, f"connect4_model{suffix}.h")
+    _write_c_header(tflite_model, header_path)
+    print(f"C header: {header_path}")
+
+    return out_path
+
+
+def _write_c_header(model_bytes, path):
+    """Write TFLite model as a C byte array for ESP32 firmware inclusion."""
+    with open(path, "w") as f:
+        f.write("#pragma once\n\n")
+        f.write(f"// Auto-generated — {len(model_bytes)} bytes\n")
+        f.write(f"const unsigned int connect4_model_len = {len(model_bytes)};\n")
+        f.write("alignas(16) const unsigned char connect4_model[] = {\n")
+        for i in range(0, len(model_bytes), 12):
+            chunk = model_bytes[i:i + 12]
+            f.write("    " + ", ".join(f"0x{b:02x}" for b in chunk) + ",\n")
+        f.write("};\n")
+
+
+if __name__ == "__main__":
+    import sys
+    model_path = sys.argv[1] if len(sys.argv) > 1 else "rl/checkpoints/model_final.keras"
+    export_tflite(model_path)