def create_header_file(name, tensor_name, tensor_data, output_path):
    """
    This function generates a header file containing the data from the numpy array provided.
    """
    file_path = pathlib.Path(f"{output_path}/" + name).resolve()
    # Create header file with npy_data as a C array
    raw_path = file_path.with_suffix(".h").resolve()
    with open(raw_path, "a") as header_file:
        header_file.write(
            "\n" + f"const size_t {tensor_name}_len = {tensor_data.size};\n" +
            f'__attribute__((section(".data.tvm"), aligned(16))) float {tensor_name}[] = '
        )

        header_file.write("{")
        for i in np.ndindex(tensor_data.shape):
            header_file.write(f"{tensor_data[i]}, ")
        header_file.write("};\n\n")

    This function generates a header file containing the data from the numpy array provided.
    
deploy/third_engine/demo_avh/convert_image.py