(self, input_size, hidden_size, num_layers=1,
                 init_scale=0.1)
init
init
init
def __init__(self, input_size, hidden_size, num_layers=1,
                 init_scale=0.1):
        """
            init
        """
        self.weight_1_arr = []
        self.bias_1_arr = []
        for i in range(num_layers):
            weight_1 = fluid.layers.create_parameter(
                    [input_size + hidden_size, hidden_size * 4],
                    dtype="float32",
                    name="fc_weight1_" + str(i),
                    default_initializer=fluid.initializer.UniformInitializer(
                            low=-init_scale,
                            high=init_scale))
            input_size = hidden_size
            self.weight_1_arr.append(weight_1)
            bias_1 = fluid.layers.create_parameter(
                [hidden_size * 4],
                dtype="float32",
                name="fc_bias1_" + str(i),
                default_initializer=fluid.initializer.Constant(0.0))
            self.bias_1_arr.append(bias_1)

        self.num_layers = num_layers
        self.hidden_size = hidden_size
def __init__ ( self , input_size , hidden_size , num_layers = 1 , init_scale = 0.1 ) : self . weight_1_arr = [ ] self . bias_1_arr = [ ] for i in range ( num_layers ) : weight_1 = fluid . layers . create_parameter ( [ input_size + hidden_size , hidden_size * 4 ] , dtype = "float32" , name = "fc_weight1_" + str ( i ) , default_initializer = fluid . initializer . UniformInitializer ( low = - init_scale , high = init_scale ) ) input_size = hidden_size self . weight_1_arr . append ( weight_1 ) bias_1 = fluid . layers . create_parameter ( [ hidden_size * 4 ] , dtype = "float32" , name = "fc_bias1_" + str ( i ) , default_initializer = fluid . initializer . Constant ( 0.0 ) ) self . bias_1_arr . append ( bias_1 ) self . num_layers = num_layers self . hidden_size = hidden_size