layers.py 文件源码

def step(self, hprev, x):
        if self.layer_normalization:
            ln = apply_ln(self)
            x_ru = ln(tf.matmul(x, self.W_x_ru), "x_ru")
            h_ru = ln(tf.matmul(hprev, self.W_h_ru), "h_ru")
            x_r, x_u = tf.split(split_dim=1, num_split=2, value=x_ru)
            h_r, h_u = tf.split(split_dim=1, num_split=2, value=h_ru)
            x_c = ln(tf.matmul(x, self.W_xc), "x_c")
            h_c = ln(tf.matmul(hprev, self.W_hc), "h_c")
            r = self.gate_nonlinearity(x_r + h_r)
            u = self.gate_nonlinearity(x_u + h_u)
            c = self.nonlinearity(x_c + r * h_c)
            h = (1 - u) * hprev + u * c
            return h
        else:
            xb_ruc = tf.matmul(x, self.W_x_ruc) + tf.reshape(self.b_ruc, (1, -1))
            h_ruc = tf.matmul(hprev, self.W_h_ruc)
            xb_r, xb_u, xb_c = tf.split(split_dim=1, num_split=3, value=xb_ruc)
            h_r, h_u, h_c = tf.split(split_dim=1, num_split=3, value=h_ruc)
            r = self.gate_nonlinearity(xb_r + h_r)
            u = self.gate_nonlinearity(xb_u + h_u)
            c = self.nonlinearity(xb_c + r * h_c)
            h = (1 - u) * hprev + u * c
            return h