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quantize_onnx.py

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+#!/usr/bin/env python3
+"""
+Generate fp16 and int8 variants of formantnet.onnx.
+Run in onnxconv env.
+"""
+import os, sys
+import numpy as np
+import onnx
+import onnxruntime as ort
+from onnxconverter_common import float16
+from onnxruntime.quantization import quantize_dynamic, QuantType
+
+SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
+fp32_path  = os.path.join(SCRIPT_DIR, 'formantnet.onnx')
+fp16_path  = os.path.join(SCRIPT_DIR, 'formantnet_fp16.onnx')
+int8_path  = os.path.join(SCRIPT_DIR, 'formantnet_int8.onnx')
+
+# Reference output for parity checks
+np.random.seed(42)
+x = np.random.randn(1, 200, 257).astype(np.float32)
+ref_sess = ort.InferenceSession(fp32_path, providers=['CPUExecutionProvider'])
+input_name = ref_sess.get_inputs()[0].name
+ref_out = ref_sess.run(None, {input_name: x})[0]
+
+def check(path, label, abs_thr, rel_thr):
+    sess = ort.InferenceSession(path, providers=['CPUExecutionProvider'])
+    iname = sess.get_inputs()[0].name
+    out = sess.run(None, {iname: x.astype(np.float32)})[0]
+    max_abs = float(np.abs(ref_out - out).max())
+    max_rel = float((np.abs(ref_out - out) / (np.abs(ref_out) + 1e-8)).max())
+    size_mb = os.path.getsize(path) / 1e6
+    ok = max_abs < abs_thr and max_rel < rel_thr
+    status = "✓" if ok else "✗"
+    print(f"  {label:6s}  {size_mb:.2f} MB  max_abs={max_abs:.2e}  max_rel={max_rel:.2e}  {status}")
+    return ok
+
+print(f"Source: {fp32_path}  ({os.path.getsize(fp32_path)/1e6:.2f} MB)\n")
+
+# --- fp16 ---
+print("Generating fp16...")
+model_fp32 = onnx.load(fp32_path)
+model_fp16 = float16.convert_float_to_float16(model_fp32, keep_io_types=True)
+onnx.save(model_fp16, fp16_path)
+print(f"  Saved → {fp16_path}")
+check(fp16_path, 'fp16', abs_thr=0.005, rel_thr=0.05)
+
+# --- int8 dynamic quantization ---
+print("\nGenerating int8 (dynamic quantization)...")
+quantize_dynamic(fp32_path, int8_path, weight_type=QuantType.QInt8)
+print(f"  Saved → {int8_path}")
+check(int8_path, 'int8', abs_thr=0.15, rel_thr=999.0)  # gate on abs only; rel can spike near zero (same as DeepFormants-onnx int8)
+
+print("\nDone.")