def highway(self, layer1, layer2):
kernel_gate = glorot([self.dim, self.dim])
bias_gate = zeros([self.dim])
transform_gate = tf.matmul(layer1, kernel_gate) + bias_gate
transform_gate = tf.nn.sigmoid(transform_gate)
carry_gate = 1.0 - transform_gate
return transform_gate * layer2 + carry_gate * layer1
def get_input_layer(self):
ent_embeddings = glorot((self.ent_num, self.dim), "input")
return ent_embeddings
