SciML / SciMLSensitivity.jl

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
https://docs.sciml.ai/SciMLSensitivity/stable/
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sensealg in solve is ignored #1110

Open daviehh opened 2 months ago

daviehh commented 2 months ago

Describe the bug 🐞

The sensealg in solve is ignored, currently it only follows the sensealg defined in the problem

Looks like, the sensealg is not in the prob.kwargs, and is ignored in the solve_up call

https://github.com/SciML/DiffEqBase.jl/blob/6b1191f2993f163f09e8b718b28599ac1b3f16e3/src/solve.jl#L993-L1007

https://github.com/SciML/DiffEqBase.jl/blob/6b1191f2993f163f09e8b718b28599ac1b3f16e3/src/solve.jl#L1066-L1083

Expected behavior

allow the sensealg in solve to work

Minimal Reproducible Example 👇

using OrdinaryDiffEq
using SciMLSensitivity, ForwardDiff

function lotka_volterra!(du, u, p, t)
    du[1] = dx = p[1] * u[1] - p[2] * u[1] * u[2]
    du[2] = dy = -p[3] * u[2] + p[4] * u[1] * u[2]
end

p = [1.5, 1.0, 3.0, 1.0];
u0 = [1.0; 1.0];
tspan = (0.0, 10.0)

#A
let
    s_prob = ODEForwardSensitivityProblem(lotka_volterra!, u0, tspan, p)
    s_sol = solve(s_prob, Tsit5(), sensealg=ForwardDiffSensitivity())
    x, dp = extract_local_sensitivities(s_sol, 4.0)
    dp[end]
end

#B
let
    s_prob = ODEForwardSensitivityProblem(lotka_volterra!, u0, tspan, p)
    s_sol = solve(s_prob, Tsit5(), sensealg=ForwardSensitivity())
    x, dp = extract_local_sensitivities(s_sol, 4.0)
    dp[end]
end

#C
let
    s_prob = ODEForwardSensitivityProblem(lotka_volterra!, u0, tspan, p, sensealg=ForwardDiffSensitivity())
    s_sol = solve(s_prob, Tsit5())
    x, dp = extract_local_sensitivities(s_sol, 4.0)
    dp[end]
end

Error & Stacktrace ⚠️

A and B gives same result, different from C, or, s_sol = solve(s_prob, Tsit5(), sensealg=1) would actually run without any error messages.

Environment (please complete the following information):

Status `~/test/Project.toml`
  [f6369f11] ForwardDiff v0.10.36
  [1dea7af3] OrdinaryDiffEq v6.89.0
  [1ed8b502] SciMLSensitivity v7.66.2
Status `~/test/Manifest.toml`
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Julia Version 1.11.0-rc3
Commit 616e45539db (2024-08-26 15:46 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: macOS (arm64-apple-darwin22.4.0)
  CPU: 10 × Apple M1 Pro
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, apple-m1)
Threads: 8 default, 0 interactive, 4 GC (on 8 virtual cores)

Additional context

The last example at https://docs.sciml.ai/SciMLSensitivity/stable/tutorials/direct_sensitivity/ uses the sensealg in the solve call, might be confusing

jClugstor commented 2 months ago

Yeah, it looks like extract_local_sensitivities only uses the sensealg in the problem construction, inside of sol.prob.problem_type.sensealg. It also seems like adjoint_sensitivities also ignores sensealg inside of the solve call.

ChrisRackauckas commented 1 month ago

@jClugstor did you ever get around to this?

jClugstor commented 1 month ago

Not yet, but should be an easy fix, I'll look at it this week.

Question: if both solve and the problem definition have sensealg, which one to respect?

ChrisRackauckas commented 1 month ago

solve.

jClugstor commented 1 month ago

I'm not actually sure this is possible without having the kwargs to solve being part of the solution object.

ChrisRackauckas commented 1 month ago

why would that be the case? It's in the prob and only called forward.

jClugstor commented 1 month ago

If you call extract_local_sensitivities(s_sol, 4.0) and s_sol doesn't have information on what sensealg was used in solve, extract_local_sensitivities can't use the solve sensealg. extract_local_sensitivities already uses the sensealg from s_sol.prob.