gradient.py 文件源码

def disconnected_grad(x):
    """
    Consider an expression constant when computing gradients,
    while effectively not backpropagating through it.

    The expression itself is unaffected, but when its gradient is
    computed, or the gradient of another expression that this
    expression is a subexpression of, it will not be backpropagated
    through. This is effectively equivalent to truncating the gradient
    expression to 0, but is executed faster than zero_grad(), which stilll
    has to go through the underlying computational graph related to the
    expression.

    :param x: A Theano expression whose gradient should not be
              backpropagated through.

    :return: The expression is returned unmodified, but its gradient
        is now effectively truncated to 0.
    """
    return disconnected_grad_(x)