def load_model_config_from_hf()

in docker_images/mindspore/app/pipelines/image_classification.py [0:0]

• 22 lines of code
• 4 McCabe index (conditional complexity)

def load_model_config_from_hf(model_id):
    repo_path = snapshot_download(model_id)
    config_json_file = os.path.join(repo_path, "config.json")
    if not os.path.exists(config_json_file):
        raise EnvironmentError(
            f"The path of the config.json file {config_json_file} doesn't exist!"
        )
    config = load_config(config_json_file)
    architecture = config.get("architecture")
    if architecture not in ALLOWED_MODEL:
        raise EnvironmentError(f"Currently doesn't supports {model} model!")
    net_func = ALLOWED_MODEL.get(architecture)
    class_num = config.get("num_classes")
    net = net_func(class_num=class_num, is_training=False)
    ms_model = model.Model(net)
    model_file = os.path.join(repo_path, "mindspore_model.ckpt")
    if not os.path.exists(model_file):
        raise EnvironmentError(
            f"The path of the model file {model_file} doesn't exist!"
        )
    ms_model.load_checkpoint(model_file)
    return ms_model, config