thsno02

def add_normalization_to_onnx(model_path: str, first_node_name: str, mean: list, std: list):
    '''
    Edit the exported onnx model => add preprocess layer: sub mean and div std
    '''

    model = onnx.load(model_path)
    onnx.save(model, model_path.replace('inference', 'raw_inference'))

    # Assuming the input of your model is a single tensor of shape (batch_size, num_channels, height, width)
    input_tensor = model.graph.input[0]

thsno02

Related Issues

• https://huggingface.co/decapoda-research/llama-7b-hf/discussions/3
• tatsu-lab/stanford_alpaca#64
• huggingface/transformers#21955

Prerequisites

ENV