iRNNCellAbs.py 文件源码

def __call__(self, inputs, state, scope=None):
    """Most basic RNN: output = new_state = activation(W * input + U * state + B)."""
    with vs.variable_scope(scope or type(self).__name__):  # "BasicRNNCell"
        state_out = linearTransformIdentityInit(state, self._num_units)

        if self._bottom == True:
            input_out = linearTransformWithBias([inputs], self._num_units, bias=False, scope=scope)
        else:
            input_out = linearTransformIdentityInit(inputs, self._num_units, scope=scope)
        bias = vs.get_variable(
            "input_bias", [self._num_units],
            dtype=tf.float32,
            initializer=init_ops.constant_initializer(dtype=tf.float32))

    output = tf.abs(state_out + input_out + bias)
    return output, output