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convert_to_onnx.py

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+#!/usr/bin/env python3
+import sys, os
+
+# FN_* modules use relative imports; run from repo/User
+SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
+USER_DIR = os.path.join(SCRIPT_DIR, 'repo', 'User')
+sys.path.insert(0, USER_DIR)
+os.chdir(USER_DIR)
+
+import tensorflow as tf
+import tf2onnx
+import FN_configuration
+import FN_model
+
+cfg = FN_configuration.configuration()
+cfg.configure(None)
+
+print(f"Model input:  (None, None, {cfg.SPECTRUM_NPOINTS})")
+print(f"Model output: (None, None, {cfg.NPARAMS})")
+
+model = FN_model.define_model(cfg)
+
+ckpt = os.path.join(SCRIPT_DIR, 'expdir', 'mvt33_f6z1sTpF10', 'weights.sigmoid195-20.143')
+print(f"\nLoading weights: {ckpt}")
+model.load_weights(ckpt).expect_partial()
+print("Weights loaded.")
+
+input_sig = [tf.TensorSpec([None, None, cfg.SPECTRUM_NPOINTS], tf.float32, name='input')]
+
+output_path = os.path.join(SCRIPT_DIR, 'formantnet.onnx')
+print(f"\nConverting to ONNX (opset 15) → {output_path}")
+
+model_proto, _ = tf2onnx.convert.from_keras(
+    model,
+    input_signature=input_sig,
+    opset=15,
+    output_path=output_path,
+)
+
+print(f"Done. ONNX graph has {len(model_proto.graph.node)} nodes.")
+print(f"Output: {output_path}")