def __init__(self, rule_num, base_num, base_rule_num, att_dim, mid_dim, res_dim):
super(AModel, self).__init__()
self.bms = [BModel(base_rule_num, att_dim, mid_dim) for _ in range(base_num)]
self.a = generate_variable((rule_num, base_num, mid_dim,))
self.d = generate_variable((base_num,))
self.b = generate_variable((rule_num, res_dim,))
self.r = generate_variable((rule_num,))
def __init__(self,
rule_num,
att_dim,
low,
high,
cat_dims,
res_dim,
junc,
name=None):
super(BaseM, self).__init__(name=name)
self.an = generate_variable(
(rule_num, att_dim),
initial_value=np.random.uniform(low, high, (
rule_num,
att_dim,
)))
self.o = generate_variable((att_dim, ),
initial_value=0.5 * (high - low))
self.dz = tf.constant(0.01 * (high - low))
self.ac = [
generate_variable((
rule_num,
cat_dim,
)) for cat_dim in cat_dims
]
self.b = generate_variable((
rule_num,
res_dim,
))
self.r = generate_variable((rule_num, ))
self.j = generate_junctive(junc)
self.tv = self.trainable_variables
def __init__(self, rule_num, att_dim, sub_dim, res_dim):
super(Modelz, self).__init__()
self.a = generate_variable((rule_num, att_dim,))
self.d = generate_variable((att_dim,))
self.b = generate_variable((rule_num, res_dim,))
self.r = generate_variable((rule_num,))
# self.s = generate_variable((rule_num, sub_dim,))
self.s = tf.Variable(tf.random.normal((rule_num, sub_dim,), 0.5, dtype=tf.float64))
self.z = generate_variable((res_dim,))
def __init__(self, rule_num, dis_num, dis_dim, res_dim, junc, name=None):
super(Dist, self).__init__(name=name)
self.a = generate_variable((
rule_num,
dis_num,
dis_dim,
))
self.b = generate_variable((rule_num, res_dim))
self.r = generate_variable((rule_num, ))
self.j = generate_junctive(junc)
def __init__(self, rule_num, cat_dims, res_dim, junc, name=None):
super(BaseC, self).__init__(name=name)
self.a = [
generate_variable((rule_num, cat_dim)) for cat_dim in cat_dims
]
self.b = generate_variable((
rule_num,
res_dim,
))
self.r = generate_variable((rule_num, ))
self.j = generate_junctive(junc)
self.tv = self.trainable_variables
def __init__(self, rule_num, att_dim, res_dim):
super(BModel, self).__init__()
self.a = generate_variable((rule_num, att_dim,))
self.d = generate_variable((att_dim,))
self.b = generate_variable((rule_num, res_dim,))
self.r = generate_variable((rule_num,))