How to use the deepctr.layers.Hash function in deepctr

def get_embedding_vec_list(embedding_dict, input_dict, sparse_fg_list,return_feat_list=(),mask_feat_list=()):
    embedding_vec_list = []
    for fg in sparse_fg_list:
        feat_name = fg.name
        if len(return_feat_list) == 0  or feat_name in return_feat_list:
            if fg.hash_flag:
                lookup_idx = Hash(fg.dimension,mask_zero=(feat_name in mask_feat_list))(input_dict[feat_name])
            else:
                lookup_idx = input_dict[feat_name]

            embedding_vec_list.append(embedding_dict[feat_name](lookup_idx))

    return embedding_vec_list

def get_varlen_embedding_vec_dict(embedding_dict, sequence_input_dict, sequence_fg_list):
    varlen_embedding_vec_dict = {}
    for fg in sequence_fg_list:
        feat_name = fg.name
        if fg.hash_flag:
            lookup_idx = Hash(fg.dimension, mask_zero=True)(sequence_input_dict[feat_name])
        else:
            lookup_idx = sequence_input_dict[feat_name]
        varlen_embedding_vec_dict[feat_name] = embedding_dict[feat_name](lookup_idx)
    return varlen_embedding_vec_dict