def METHOD_NAME(input_feature_options):
    # build input feature config
    input_feature_configs = list()
    input_feature_configs.append({"name": "input_feature_1", "type": input_feature_options.feature_type})
    input_feature_configs[0].update(input_feature_options.feature_options)
    input_feature_configs.append({"name": "input_feature_2", "type": input_feature_options.feature_type})
    input_feature_configs[1].update(input_feature_options.feature_options)
    # add tied option to the second feature
    if input_feature_options.tie_features:
        input_feature_configs[1]["tied"] = "input_feature_1"
    config_obj = ModelConfig.from_dict(
        {"input_features": input_feature_configs, "output_features": [{"name": "dummy_feature", "type": "binary"}]}
    )
    input_features = BaseModel.build_inputs(input_feature_configs=config_obj.input_features)
    if input_feature_options.tie_features:
        # should be same encoder
        assert input_features["input_feature_1"].encoder_obj is input_features["input_feature_2"].encoder_obj
    else:
        # no tied parameter, encoders should be different
        assert input_features["input_feature_1"].encoder_obj is not input_features["input_feature_2"].encoder_obj