def METHOD_NAME():
    if te_installed and torch.cuda.get_device_capability()[0] >= 9:
        from transformer_engine.common.recipe import Format
        precision_config = {
            'fp8_format': Format.HYBRID,
            'amax_history_len': 16,
            'amax_compute_algo': 'max',
        }
        trainer = get_trainer(Precision.AMP_FP8, precision_config=precision_config)
        with get_precision_context(trainer.state.precision, trainer.state.precision_config):
            fp8_recipe = te.fp8.get_fp8_recipe()
            for k, v in precision_config.items():
                assert getattr(fp8_recipe, k) == v