temp.py

from onnxruntime import optimizer

# Specify the models you want to optimize
models = [
    'onnx/decoder_model.onnx',
    'onnx/decoder_model_merged.onnx',
    'onnx/decoder_model_merged_quantized.onnx',
    'onnx/decoder_model_quantized.onnx',
    'onnx/decoder_with_past_model.onnx',
    'onnx/decoder_with_past_model_quantized.onnx',
    'onnx/encoder_model.onnx',
    'onnx/encoder_model_quantized.onnx'
]

for model_path in models:
    # Load and optimize the model
    optimized_model = optimizer.optimize_model(model_path)

    # Save the optimized model
    optimized_model.save_model_to_file(model_path.replace('.onnx', '_optimized.onnx'))