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)
