basic.py 文件源码

def grad(self, inputs, gout):
        (y, x) = inputs
        (gz,) = gout
        if gz.type in complex_types:
            raise NotImplementedError()
        else:
            if self(x, y).type in discrete_types:
                if x.type in discrete_types:
                    gx = x.zeros_like(dtype=theano.config.floatX)
                else:
                    gx = x.zeros_like()
                if y.type in discrete_types:
                    gy = y.zeros_like(dtype=theano.config.floatX)
                else:
                    gy = y.zeros_like()
                return [gx, gy]

            # If the output is float, the gradient should flow,
            # even if the inputs are ints
            return [gz * x / (sqr(x) + sqr(y)),
                    gz * neg(y) / (sqr(x) + sqr(y))]