

def grad(self, inp, grads):
    (x,) = inp
    (gz,) = grads
    if (cst.type in complex_types):
        raise NotImplementedError()
    if (self(x).type in discrete_types):
        if (x.type in discrete_types):
            return [x.zeros_like(dtype=theano.config.floatX)]
        else:
            return [x.zeros_like()]
    cst = numpy.asarray((numpy.sqrt(numpy.pi) / 2.0), dtype=upcast(x.type.dtype, gz.type.dtype))
    return (((gz * cst) * exp((erfinv(x) ** 2))),)

dataset/ETHPy150Open rizar/attention-lvcsr/libs/Theano/theano/scalar/basic_scipy.py Erfinv.grad/VarMisuse@30/32 `x`->`cst`