gradient.py 文件源码

def grad_clip(x, lower_bound, upper_bound):
    """
    This op do a view in the forward, but clip the gradient.

    This is an elemwise operation.

    :param x: the variable we want its gradient inputs clipped
    :param lower_bound: The lower bound of the gradient value
    :param upper_bound: The upper bound of the gradient value.

    :examples:

        x = theano.tensor.scalar()

        z = theano.tensor.grad(grad_clip(x, -1, 1)**2, x)
        z2 = theano.tensor.grad(x**2, x)

        f = theano.function([x], outputs = [z, z2])

        print(f(2.0))  # output (1.0, 4.0)

    :note: We register an opt in tensor/opt.py that remove the GradClip.
       So it have 0 cost in the forward and only do work in the grad.

    """
    return GradClip(lower_bound, upper_bound)(x)