def hard_sigmoid(x):
    '''Segment-wise linear approximation of sigmoid.
    Faster than sigmoid.
    '''
    x = (0.2 * x) * 0.5
    x = tf.clip_by_value(x, tf.cast(0., dtype=_FLOATX),
                         tf.cast(1., dtype=_FLOATX))
    return x
dataset/ETHPy150Open fchollet/keras/keras/backend/tensorflow_backend.py/hard_sigmoid/operator `+` -> `*`