LoopVectorization returning zeros in @tturbo accelerated region

I have written a macro that generates a fast loop for interpolations. Without `@tturbo` and with `Threads.@threads` the code runs fine, but it fails with `@tturbo` which does not do any computations. I print the generated code to the screen, this is rather straightforward and I do not know what goes wrong here:

```julia
## Load the packages.
using LoopVectorization
using Interpolations
using Statistics
using BenchmarkTools
using PyPlot
using Printf

## Define the upsample functions.
macro upsample_lin_fast(suffix, ifac, jfac, kfac, ioff, joff, koff)
ex_inner = []
for kk in 0:kfac-1, jj in 0:jfac-1, ii in 0:ifac-1
push!(ex_inner, :(i_hi = $ifac*i+$ii+is_hi), :(j_hi = $jfac*j+$jj+js_hi), :(k_hi = $kfac*k+$kk+ks_hi))

i_pos = -1/2 + ioff + (1/2 - ioff + ii)/ifac
j_pos = -1/2 + joff + (1/2 - joff + jj)/jfac
k_pos = -1/2 + koff + (1/2 - koff + kk)/kfac

i_lo_off = floor(Int, i_pos) + is_lo
j_lo_off = floor(Int, j_pos) + js_lo
k_lo_off = floor(Int, k_pos) + ks_lo
push!(ex_inner, :(i_lo = i + $i_lo_off), :(j_lo = j + $j_lo_off), :(k_lo = k + $k_lo_off))

fi = mod(i_pos, 1)
fj = mod(j_pos, 1)
fk = mod(k_pos, 1)

coef = zeros(2, 2, 2)
coef[1, 1, 1] = (((1-fi)*fj+fi-1)*fk+(fi-1)*fj-fi+1)
coef[2, 1, 1] = ((fi*fj-fi)*fk-fi*fj+fi)
coef[1, 2, 1] = ((fi-1)*fj*fk+(1-fi)*fj)
coef[2, 2, 1] = (fi*fj-fi*fj*fk)
coef[1, 1, 2] = ((fi-1)*fj-fi+1)*fk
coef[2, 1, 2] = (fi-fi*fj)*fk
coef[1, 2, 2] = (1-fi)*fj*fk
coef[2, 2, 2] = fi*fj*fk

rhs_list = []
for kc in 1:2, jc in 1:2, ic in 1:2
if !(coef[ic, jc, kc] ≈ 0)
push!(rhs_list, :( $(coef[ic, jc, kc])*lo[i_lo+$(ic-1), j_lo+$(jc-1), k_lo+$(kc-1)] ))
end
end

rhs = Expr(:call, :+, rhs_list...)

push!(ex_inner, :(hi[i_hi, j_hi, k_hi] = $rhs))
end

ex_inner_block = Expr(:block, ex_inner...)

name = Symbol(@sprintf "upsample_lin_%s!" suffix)
ex = quote
function $name(hi, lo, itot, jtot, ktot, is_hi, js_hi, ks_hi, is_lo, js_lo, ks_lo)
# THIS WORKS WELL
# Threads.@threads for k in 0:ktot-1
# for j in 0:jtot-1
# @inbounds @simd for i in 0:itot-1
# $ex_inner_block
# end
# end
# end
@tturbo for k in 0:ktot-1
for j in 0:jtot-1
for i in 0:itot-1
$ex_inner_block
end
end
end
end
end
println("FAILING CODE START")
println(ex)
println("FAILING END")

return esc(ex)
end

function upsample_lin_ref!(hi, lo, x_hi, y_hi, z_hi, x_lo, y_lo, z_lo, is_hi, js_hi, ks_hi, ie_hi, je_hi, ke_hi)
interp = interpolate((x_lo, y_lo, z_lo), lo, (Gridded(Linear()), Gridded(Linear()), Gridded(Linear())))
hi[is_hi:ie_hi, js_hi:je_hi, ks_hi:ke_hi] .= interp(x_hi[is_hi:ie_hi], y_hi[js_hi:je_hi], z_hi[ks_hi:ke_hi])
end

## Set up the grids.
itot_lo = 256; jtot_lo = 192; ktot_lo = 128
itot_hi = 512; jtot_hi = 384; ktot_hi = 256
igc_lo = 1; jgc_lo = 1; kgc_lo = 1
igc_hi = 1; jgc_hi = 1; kgc_hi = 1

# Derive dimensions
ifac = itot_hi÷itot_lo; jfac = jtot_hi÷jtot_lo; kfac = ktot_hi÷ktot_lo;
icells_lo = itot_lo + 2igc_lo; jcells_lo = jtot_lo + 2jgc_lo; kcells_lo = ktot_lo + 2kgc_lo
icells_hi = itot_hi + 2igc_hi; jcells_hi = jtot_hi + 2jgc_hi; kcells_hi = ktot_hi + 2kgc_hi
is_lo = igc_lo+1; js_lo = jgc_lo+1; ks_lo = kgc_lo+1
is_hi = igc_hi+1; js_hi = jgc_hi+1; ks_hi = kgc_hi+1
ie_lo = igc_lo+itot_lo; je_lo = jgc_lo+jtot_lo; ke_lo = kgc_lo+ktot_lo
ie_hi = igc_hi+itot_hi; je_hi = jgc_hi+jtot_hi; ke_hi = kgc_hi+ktot_hi

a_lo = rand(icells_lo, jcells_lo, kcells_lo)
a_hi_ref = zeros(icells_hi, jcells_hi, kcells_hi)
a_hi = zeros(icells_hi, jcells_hi, kcells_hi)
a_hi_fast = zeros(icells_hi, jcells_hi, kcells_hi)

dx_lo = 1/itot_lo; dy_lo = 1/jtot_lo; dz_lo = 1/ktot_lo
x_lo = collect(range(0.5-igc_lo, length=icells_lo)) .* dx_lo
y_lo = collect(range(0.5-jgc_lo, length=jcells_lo)) .* dy_lo
z_lo = collect(range(0.5-kgc_lo, length=kcells_lo)) .* dz_lo
xh_lo = collect(range(-igc_lo, length=icells_lo)) .* dx_lo
yh_lo = collect(range(-jgc_lo, length=jcells_lo)) .* dy_lo

dx_hi = 1/itot_hi; dy_hi = 1/jtot_hi; dz_hi = 1/ktot_hi
x_hi = collect(range(0.5-igc_hi, length=icells_hi)) .* dx_hi
y_hi = collect(range(0.5-jgc_hi, length=jcells_hi)) .* dy_hi
z_hi = collect(range(0.5-kgc_hi, length=kcells_hi)) .* dz_hi
xh_hi = collect(range(-igc_hi, length=icells_hi)) .* dx_hi
yh_hi = collect(range(-jgc_hi, length=jcells_hi)) .* dy_hi

## Compute a reference using Interpolations.jl
@btime upsample_lin_ref!(
a_hi_ref, a_lo, x_hi, y_hi, z_hi, x_lo, y_lo, z_lo,
is_hi, js_hi, ks_hi, ie_hi, je_hi, ke_hi)
@upsample_lin_fast("222", 2, 2, 2, 0, 0, 0)
@btime upsample_lin_222!(
a_hi_fast, a_lo, itot_lo, jtot_lo, ktot_lo,
is_hi, js_hi, ks_hi, is_lo, js_lo, ks_lo)

a_lo_int = @view a_lo[is_lo:ie_lo, js_lo:je_lo, ks_lo:ke_lo]
a_hi_ref_int = @view a_hi_ref[is_hi:ie_hi, js_hi:je_hi, ks_hi:ke_hi]
a_hi_int = @view a_hi[is_hi:ie_hi, js_hi:je_hi, ks_hi:ke_hi]
a_hi_fast_int = @view a_hi_fast[is_hi:ie_hi, js_hi:je_hi, ks_hi:ke_hi]

println("Fast equal to ref: ", a_hi_fast_int ≈ a_hi_ref_int)

## Plot the output.
x_lo_int = @view x_lo[is_lo:ie_lo]
x_hi_int = @view x_hi[is_hi:ie_hi]

figure()
plot(x_hi_int, a_hi_ref_int[:, 1, 1], "C0-^")
plot(x_hi_int, a_hi_fast_int[:, 1, 1], "C1-*")
plot(x_lo_int, a_lo_int[:, 1, 1], "k:+")
tight_layout()
display(gcf())
show()
```