File size: 1,696 Bytes
76ec265 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | from pathlib import Path
import onnx
from onnxconverter_common import convert_float_to_float16
DATA_DIR = Path(__file__).parent.parent / "data"
FP32_PATH = DATA_DIR / "mobilevit.onnx"
FP16_PATH = (
DATA_DIR / "mobilevit_quant.onnx"
) # Keep the _quant name for frontend loading compatibility
def main():
if not FP32_PATH.exists():
print(
f"Error: FP32 MobileViT ONNX model not found at {FP32_PATH}. Please train and export first."
)
return
print(f"Converting model {FP32_PATH} to FP16 half-precision for WebGPU acceleration...")
try:
# Load the ONNX model
model = onnx.load(str(FP32_PATH))
# Convert model to Float16
# This reduces file size by 50% and dramatically speeds up WebGPU shader executions.
model_fp16 = convert_float_to_float16(model)
# Save the FP16 model
onnx.save(model_fp16, str(FP16_PATH))
# Verify sizes
fp32_size = FP32_PATH.stat().st_size / 1024
fp16_size = FP16_PATH.stat().st_size / 1024
print("FP16 Conversion complete!")
print(f"Original FP32 model size: {fp32_size:.2f} KB (~{fp32_size / 1024:.2f} MB)")
print(
f"Converted FP16 model size: {fp16_size:.2f} KB (~{fp16_size / 1024:.2f} MB) (Reduction: {(1 - fp16_size / fp32_size) * 100:.1f}%)"
)
# Simple structural integrity check
onnx.checker.check_model(onnx.load(str(FP16_PATH)))
print("ONNX FP16 model structure check passed.")
except Exception as e:
print(f"FP16 Conversion failed with error: {e}")
if __name__ == "__main__":
main()
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