Is there a way I can tell Zygote to automatically apply `Zygote.dropgrad()`

for all function numerical arguments that are non-differentiable?

Example:

```
julia> import Zygote
julia> # naiively defining my function, and using Zygote to calculate the gradient
f(n::Integer,x::Real) = sin(n*x)
f (generic function with 1 method)
julia> Zygote.gradient(f, 100, π)
(3.141592653589793, 100.0)
```

Zygote performs automatic differentiation with respect to `n`

, although `n`

is an integer and `f`

can’t be differentiated with respect to `n`

.

I hope Zygote can apply `Zygote.dropgrad()`

to all arguments that are Integers, like `n`

:

```
julia> f(n::Integer,x::Real) = sin(Zygote.dropgrad(n) * x)
f (generic function with 1 method)
julia> Zygote.gradient(f, 100, π)
(nothing, 100.0)
```