[petsc-users] TAO: armijo condition not fulfilled
Jason Sarich
jason.sarich at gmail.com
Thu Jun 11 15:03:54 CDT 2015
Hi Andreas,
I don't see anything obviously wrong. If the function is very flat, you can
try setting -tao_ls_armijo_sigma to a smaller number. If you continue to
have problems, please let me know. It would definitely help if you have an
example you could send me that reproduces this behavior.
Jason
On Thu, Jun 11, 2015 at 1:12 PM, Andreas Mang <andreas at ices.utexas.edu>
wrote:
> Hey Jason:
>
> The line search fails. If I use Armijo I get
>
> TaoLineSearch Object:
> type: armijo
> maxf=30, ftol=1e-10, gtol=0.0001
> Armijo linesearch : alpha=1 beta=0.5 sigma=0.0001
> memsize=1
> maximum function evaluations=30
> tolerances: ftol=0.0001, rtol=1e-10, gtol=0.9
> total number of function evaluations=1
> total number of gradient evaluations=1
> total number of function/gradient evaluations=0
> Termination reason: 0
>
> The parameters seem to be the default ones also suggested by Nocedal and
> Wright. So I did not change anything. The termination reason is equivalent
> to TAOLINESEARCH_CONTINUE_ITERATING. I am not checking the reason directly.
> I guess it starts reducing the step size after that. I can see that my
> objective function get’s evaluated (as expected); however, the objective
> values increase (from what I see when monitoring the evaluations of my
> objective). This leads to a failure in the line search and made (still
> makes) me believe there is a bug on my side (which I have not found yet).
> However, if I use a unit step it converges (relative change of the gradient
> e.g. to 1E-9; see bottom of this email). If I use More & Thuente, same
> thing. No reduction in step size necessary.
>
> If you suggest that I should do some further testing on simpler
> problems, I’m happy to do so. After looking at the code, I just felt like
> there obviously is something wrong in the line-search implementation.
>
> Thanks for your help.
> /Andreas
>
> *Here’s the output after the first iteration (where the Armijo line
> search fails):*
>
> TaoLineSearch Object:
> type: armijo
> maxf=30, ftol=1e-10, gtol=0.0001
> Armijo linesearch : alpha=1 beta=0.5 sigma=0.0001
> memsize=1
> maximum function evaluations=30
> tolerances: ftol=0.0001, rtol=1e-10, gtol=0.9
> total number of function evaluations=1
> total number of gradient evaluations=1
> total number of function/gradient evaluations=0
> Termination reason: 0
> TaoLineSearch Object:
> type: armijo
> maxf=30, ftol=1e-10, gtol=0.0001
> Armijo linesearch : alpha=1 beta=0.5 sigma=0.0001
> memsize=1
> maximum function evaluations=30
> tolerances: ftol=0.0001, rtol=1e-10, gtol=0.9
> total number of function evaluations=30
> total number of gradient evaluations=0
> total number of function/gradient evaluations=0
> Termination reason: 4
>
> *With final output (end of optimization):*
>
> Tao Object: 1 MPI processes
> type: nls
> Newton steps: 1
> BFGS steps: 0
> Scaled gradient steps: 0
> Gradient steps: 1
> nls ksp atol: 0
> nls ksp rtol: 1
> nls ksp ctol: 0
> nls ksp negc: 0
> nls ksp dtol: 0
> nls ksp iter: 0
> nls ksp othr: 0
> TaoLineSearch Object: 1 MPI processes
> type: armijo
> KSP Object: 1 MPI processes
> type: cg
> total KSP iterations: 21
> convergence tolerances: fatol=0, frtol=0
> convergence tolerances: gatol=0, steptol=0, gttol=0.0001
> Residual in Function/Gradient:=0.038741
> Objective value=0.639121
> total number of iterations=0, (max: 50)
> total number of function evaluations=31, max: 10000
> total number of gradient evaluations=1, max: 10000
> total number of function/gradient evaluations=1, (max: 10000)
> total number of Hessian evaluations=1
> Solver terminated: -6 Line Search Failure
>
> *This is without line-search (unit step size):*
>
> Tao Object: 1 MPI processes
> type: nls
> Newton steps: 3
> BFGS steps: 0
> Scaled gradient steps: 0
> Gradient steps: 0
> nls ksp atol: 0
> nls ksp rtol: 3
> nls ksp ctol: 0
> nls ksp negc: 0
> nls ksp dtol: 0
> nls ksp iter: 0
> nls ksp othr: 0
> TaoLineSearch Object: 1 MPI processes
> type: unit
> KSP Object: 1 MPI processes
> type: cg
> total KSP iterations: 71
> convergence tolerances: fatol=0, frtol=0
> convergence tolerances: gatol=0, steptol=0, gttol=0.0001
> Residual in Function/Gradient:=1.91135e-11
> Objective value=0.160914
> total number of iterations=3, (max: 50)
> total number of function/gradient evaluations=4, (max: 10000)
> total number of Hessian evaluations=3
> Solution converged: ||g(X)||/||g(X0)|| <= gttol
>
>
>
> On Jun 11, 2015, at 12:44 PM, Jason Sarich <jason.sarich at gmail.com>
> wrote:
>
> Hi Andreas,
>
> Yes it looks like a bug that the reason is never set, but the line
> should still terminate. Is the problem you are having with the line search
> itself, or is it failing because you are checking this ls->reason directly?
>
> Jason Sarich
>
>
> On Thu, Jun 11, 2015 at 9:53 AM, Andreas Mang <andreas at ices.utexas.edu>
> wrote:
>
>> Hi guys:
>>
>> I have a problem with the TAO Armijo line search (petsc-3.5.4). My
>> algorithm works if I use the More & Thuente line search (default). I have
>> numerically checked the gradient of my objective. It’s correct. I am happy
>> to write a small snippet of code and do an easy test if you guys disagree,
>> but from what I’ve seen in the line search code it seems obvious to me that
>> there is a bug. Am I missing something or are you not setting
>>
>> ls->reason
>>
>> to
>>
>> TAOLINESEARCH_SUCCESS
>>
>> if the Armijo condition is fulfilled (TaoLineSearchApply_Armijo in
>> armijo.c; line 118 - 302)?!
>>
>> It seems to me that ls->reason is and will remain to be set to
>>
>> TAOLINESEARCH_CONTINUE_ITERATING
>>
>> if everything works (i.e. I don’t hit one of the exceptions). Does this
>> make sense? If not I’ll invest the time and put together a simple test case
>> and, if that works, continue to check my code.
>>
>> /Andreas
>>
>>
>>
>
>
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