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Move the with_stack hack inside of the DCM code #526

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merged 4 commits into from
Jan 12, 2025
Merged

Move the with_stack hack inside of the DCM code #526

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fbacadc
move the `with_stack` hack inside of the DCM code
MasonProtter Jan 10, 2025
fb3ee65
don't use `with_stack` on the DCM test
MasonProtter Jan 10, 2025
0a24934
Merge branch 'master' into with_stack-hack
MasonProtter Jan 10, 2025
61ec426
Merge branch 'master' into with_stack-hack
harisorgn Jan 12, 2025
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8 changes: 8 additions & 0 deletions src/datafitting/spDCM_VL.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -460,7 +460,15 @@ function setup_sDCM(data, model, initcond, csdsetup, priors, hyperpriors, indice
return (vlstate, vlsetup)
end

with_stack(f, n) = fetch(schedule(Task(f, n)));

function run_sDCM_iteration!(state::VLState, setup::VLSetup)
with_stack(5_000_000) do
_run_sDCM_iteration!(state, setup)
end
end

function _run_sDCM_iteration!(state::VLState, setup::VLSetup)
(;μθ_po, λ, v, ϵ_θ, dFdθ, dFdθθ) = state

f = setup.model_at_x0
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44 changes: 18 additions & 26 deletions test/datafitting.jl
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Expand Up @@ -84,19 +84,16 @@ using MAT

# HACK: on machines with very small amounts of RAM, Julia can run out of stack space while compiling the code called in this loop
# this should be rewritten to abuse the compiler less, but for now, an easy solution is just to run it with more allocated stack space.
with_stack(f, n) = fetch(schedule(Task(f,n)))

with_stack(5_000_000) do # 5MB of stack space
for iter in 1:max_iter
state.iter = iter
run_sDCM_iteration!(state, setup)
print("iteration: ", iter, " - F:", state.F[end] - state.F[2], " - dF predicted:", state.dF[end], "\n")
if iter >= 4
criterion = state.dF[end-3:end] .< setup.tolerance
if all(criterion)
print("convergence\n")
break
end
for iter in 1:max_iter
state.iter = iter
run_sDCM_iteration!(state, setup)
print("iteration: ", iter, " - F:", state.F[end] - state.F[2], " - dF predicted:", state.dF[end], "\n")
if iter >= 4
criterion = state.dF[end-3:end] .< setup.tolerance
if all(criterion)
print("convergence\n")
break
end
end
end
Expand Down Expand Up @@ -239,21 +236,16 @@ end
csdsetup = (mar_order = 8, freq = freq, dt = dt);

(state, setup) = setup_sDCM(data, fullmodel, initcond, csdsetup, priors, hyperpriors, indices, modelparam, "LFP");
# HACK: on machines with very small amounts of RAM, Julia can run out of stack space while compiling the code called in this loop
# this should be rewritten to abuse the compiler less, but for now, an easy solution is just to run it with more allocated stack space.
with_stack(f, n) = fetch(schedule(Task(f,n)))

with_stack(5_000_000) do # 5MB of stack space
for iter in 1:128
state.iter = iter
run_sDCM_iteration!(state, setup)
print("iteration: ", iter, " - F:", state.F[end] - state.F[2], " - dF predicted:", state.dF[end], "\n")
if iter >= 4
criterion = state.dF[end-3:end] .< setup.tolerance
if all(criterion)
print("convergence\n")
break
end
for iter in 1:128
state.iter = iter
run_sDCM_iteration!(state, setup)
print("iteration: ", iter, " - F:", state.F[end] - state.F[2], " - dF predicted:", state.dF[end], "\n")
if iter >= 4
criterion = state.dF[end-3:end] .< setup.tolerance
if all(criterion)
print("convergence\n")
break
end
end
end
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