def validate_custom_vector(field_content: dict, is_non_tensor_field: bool, index_model_dimensions: int):
    """
    Validates the field content if it is a custom vector field (dict)
    Args:
        field_content: the field content
        is_non_tensor_field: whether this is a non-tensor-field
        index_model_dimensions: the `dimensions` property of the index to be added to
    Returns:
        field_content if the validation passes
        "content" key will be added to the field_content as empty string if it is not provided.
    """

    validated_custom_vector = CustomVector(
        dict_data=field_content,
        dimension=index_model_dimensions,
        is_non_tensor_field=is_non_tensor_field
    )
    return validated_custom_vector.to_dict()

    Validates the field content if it is a custom vector field (dict)
    Args:
        field_content: the field content
        is_non_tensor_field: whether this is a non-tensor-field
        index_model_dimensions: the `dimensions` property of the index to be added to
    Returns:
        field_content if the validation passes
        "content" key will be added to the field_content as empty string if it is not provided.
    
src/marqo/tensor_search/validation.py