def get_multiplier(self):
"""根据schedule定义分段线性函数
"""
schedule = sorted(self.schedule.items())
if schedule[0][0] != 0:
schedule = [(0, 0.)] + schedule
lr = K.constant(schedule[0][1], dtype='float32')
t = K.cast(self.iterations, 'float32')
for i in range(len(schedule)):
if i == len(schedule) - 1:
x = K.constant(schedule[i][1], dtype='float32')
t0 = schedule[i][0]
else:
dx = schedule[i + 1][1] - schedule[i][1]
dt = schedule[i + 1][0] - schedule[i][0]
k = 1. * dx / dt
t0 = schedule[i][0]
x0 = schedule[i][1]
x = x0 + k * (t - t0)
lr = K.switch(t >= t0, x, lr)
return lr
def __init__(self, docs_encode, **kwargs):
"""
余弦相似度层, 不适合大规模语料, 比如100w以上的问答对
:param docs_encode: np.array, bert-white vector of senence
:param kwargs:
"""
self.docs_encode = docs_encode
super(CosineLayer, self).__init__(**kwargs)
self.docs_vector = K.constant(self.docs_encode, dtype="float32")
self.l2_docs_vector = K.sqrt(
K.sum(K.maximum(K.square(self.docs_vector), 1e-12),
axis=-1)) # x_inv_norm
