def __init__(self, neg_emb, neg_layer, hidden_size, num_layers, p_layers, *args, **kwargs): self.neg_emb = neg_emb self.hidden_size = hidden_size self.num_layers = num_layers self.p_layers = p_layers if type(p_layers) == list else eval(p_layers) self.neg_layer = neg_layer if type(neg_layer) == list else eval(neg_layer) RecModel.__init__(self, *args, **kwargs)
def __init__(self, user_feature_num, item_feature_num, feature_dims, f_vector_size, cb_hidden_layers, attention_size, cs_ratio, *args, **kwargs): self.user_feature_num = user_feature_num self.item_feature_num = item_feature_num self.feature_dims = feature_dims self.f_vector_size = f_vector_size self.cb_hidden_layers = cb_hidden_layers if type( cb_hidden_layers) == list else eval(cb_hidden_layers) self.attention_size = attention_size self.cs_ratio = cs_ratio RecModel.__init__(self, *args, **kwargs)
def __init__(self, hash_u_num, hash_layers, tree_layers, transfer_att_size, cs_ratio, sample_max_n, sample_r_n, *args, **kwargs): self.hash_u_num = hash_u_num self.hash_layers = hash_layers if type(hash_layers) == list else eval( hash_layers) self.tree_layers = tree_layers if type(tree_layers) == list else eval( tree_layers) self.sample_max_n, self.sample_r_n = sample_max_n, sample_r_n self.transfer_att_size = transfer_att_size self.cs_ratio = cs_ratio self.rec_paras_record, self.hash_paras_record = {}, {} RecModel.__init__(self, *args, **kwargs)
def __init__(self, layers, p_layers, hash_u_num, hash_layers, tree_layers, transfer_att_size, cs_ratio, sample_max_n, sample_r_n, *args, **kwargs): self.layers = layers if type(layers) == list else eval(layers) self.p_layers = p_layers if type(p_layers) == list else eval(p_layers) self.hash_u_num = hash_u_num self.hash_layers = hash_layers if type(hash_layers) == list else eval( hash_layers) self.tree_layers = tree_layers if type(tree_layers) == list else eval( tree_layers) self.transfer_att_size = transfer_att_size self.sample_max_n, self.sample_r_n = sample_max_n, sample_r_n self.cs_ratio = cs_ratio RecModel.__init__(self, *args, **kwargs)
def __init__(self, user_feature_num, item_feature_num, feature_dims, f_vector_size, cb_hidden_layers, attention_size, cs_ratio, hash_u_num, hash_layers, tree_layers, transfer_att_size, sample_max_n, sample_r_n, *args, **kwargs): self.user_feature_num = user_feature_num self.item_feature_num = item_feature_num self.feature_dims = feature_dims self.f_vector_size = f_vector_size self.cb_hidden_layers = cb_hidden_layers if type(cb_hidden_layers) == list else eval(cb_hidden_layers) self.attention_size = attention_size self.cs_ratio = cs_ratio self.hash_u_num = hash_u_num self.hash_layers = hash_layers if type(hash_layers) == list else eval(hash_layers) self.tree_layers = tree_layers if type(tree_layers) == list else eval(tree_layers) self.transfer_att_size = transfer_att_size self.sample_max_n, self.sample_r_n = sample_max_n, sample_r_n RecModel.__init__(self, *args, **kwargs)
def __init__(self, class_num, feature_num, user_num, item_num, u_vector_size, i_vector_size, user_feature_num, item_feature_num, feature_dims, f_vector_size, cb_hidden_layers, attention_size, cs_ratio, random_seed, model_path): self.user_feature_num = user_feature_num self.item_feature_num = item_feature_num self.feature_dims = feature_dims self.f_vector_size = f_vector_size self.cb_hidden_layers = cb_hidden_layers self.attention_size = attention_size self.cs_ratio = cs_ratio RecModel.__init__(self, class_num=class_num, feature_num=feature_num, user_num=user_num, item_num=item_num, u_vector_size=u_vector_size, i_vector_size=i_vector_size, random_seed=random_seed, model_path=model_path)
def __init__(self, layers, p_layers, *args, **kwargs): self.layers = layers if type(layers) == list else eval(layers) self.p_layers = p_layers if type(p_layers) == list else eval(p_layers) RecModel.__init__(self, *args, **kwargs)