import tensorflow as tf

        if self.inputs.get_shape().ndims != 2:
            raise Exception("The input dimension must be rank 2")
        n_in = int(self.inputs.get_shape()[-1])
        self.n_units = n_units

        with tf.variable_scope(name):
            W = tf.get_variable(name='W', shape=(n_in, n_units), initializer=W_init, dtype=LayersConfig.tf_dtype, **W_init_args)
            b = tf.get_variable(name='b', shape=(n_units), initializer=b_init, dtype=LayersConfig.tf_dtype, **b_init_args)
            # self.outputs = act(tf.matmul(self.inputs, W) + b)

