gdn.py 文件源码

def _lower_bound(inputs, bound, name=None):
    """Same as tf.maximum, but with helpful gradient for inputs < bound.
    The gradient is overwritten so that it is passed through if the input is not
    hitting the bound. If it is, only gradients that push `inputs` higher than
    the bound are passed through. No gradients are passed through to the bound.
    Args:
      inputs: input tensor
      bound: lower bound for the input tensor
      name: name for this op
    Returns:
      tf.maximum(inputs, bound)
    """
    with tf.name_scope(name, 'GDNLowerBoundTefla', [inputs, bound]) as scope:
        inputs = tf.convert_to_tensor(inputs, name='inputs')
        bound = tf.convert_to_tensor(bound, name='bound')
        with tf.get_default_graph().gradient_override_map(
                {'Maximum': 'GDNLowerBoundTefla'}):
            return tf.maximum(inputs, bound, name=scope)