Stopping solver when total cost is below certain threshold

I am encountering some interesting behavior, when solving my problem in an receding horizon MPC routine.
When I update a new target pose, the first solution with GNMS takes 4 iterations and is shown below.
For that I set printSummary and debugPrint to true.
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 1.547365 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.002475 ms
[MultipleShooting]: prepareIteration() took 1.802402 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.184508 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 7.557204 ms
[MultipleShooting]: Line search took 0.310682 ms
[MultipleShooting]: finishIteration() took 8.339397 ms
NLOC Summary of iteration 0
==============================
interm. cost:	1.37565964361
final cost:	0
total cost:	1.37565964361
total merit:	1.37565964361
tot. defect L1:	0.212041106208
tot. defect L2:	0.0973813909403
box cstr.err:	0
gen cstr.err:	0
total lx norm:	26.319324674
total lu norm:	14.9739679897
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.608909 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.00051 ms
[MultipleShooting]: prepareIteration() took 0.635876 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.056361 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 5.166026 ms
[MultipleShooting]: Line search took 0.329641 ms
[MultipleShooting]: finishIteration() took 5.602459 ms
NLOC Summary of iteration 1
==============================
interm. cost:	1.31085060474
final cost:	0
total cost:	1.31085060474
total merit:	1.31085060474
tot. defect L1:	0.0141449671345
tot. defect L2:	0.00663556822773
box cstr.err:	0
gen cstr.err:	0
total lx norm:	5.41752561809
total lu norm:	2.80196187147
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 1.163349 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.0083 ms
[MultipleShooting]: prepareIteration() took 1.25171 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.132047 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 9.610376 ms
[MultipleShooting]: Line search took 0.325102 ms
[MultipleShooting]: finishIteration() took 10.132516 ms
NLOC Summary of iteration 2
==============================
interm. cost:	1.30993248119
final cost:	0
total cost:	1.30993248119
total merit:	1.30993248119
tot. defect L1:	0.000102134243653
tot. defect L2:	5.92240828319e-05
box cstr.err:	0
gen cstr.err:	0
total lx norm:	0.626441226336
total lu norm:	0.467186996374
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.824793 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000609 ms
[MultipleShooting]: prepareIteration() took 0.858036 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.086972 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 5.188592 ms
CONVERGED: Cost last iteration: 1.30993248119, current cost: 1.30992095926
CONVERGED: Cost improvement ratio was: 8.79581434371e-06x, which is lower than convergence criteria: 1e-05
[MultipleShooting]: Line search took 0.323568 ms
[MultipleShooting]: finishIteration() took 5.640796 ms
NLOC Summary of iteration 3
==============================
interm. cost:	1.30992095926
final cost:	0
total cost:	1.30992095926
total merit:	1.30992095926
tot. defect L1:	1.22957074048e-06
tot. defect L2:	5.56606391229e-07
box cstr.err:	0
gen cstr.err:	0
total lx norm:	0.0728548958297
total lu norm:	0.0599693717847
step-size:	1
                   ===========

When the new target is reached the iterations basically look like the one below, which take 2 iterations to converge.
The total cost is quite low, as the current position and the target position are nearly the same.
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.918522 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.001294 ms
[MultipleShooting]: prepareIteration() took 1.213108 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.110336 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 3.195401 ms
[MultipleShooting]: Line search took 0.203796 ms
[MultipleShooting]: finishIteration() took 3.71993 ms
NLOC Summary of iteration 0
==============================
interm. cost:	2.5547500451e-05
final cost:	0
total cost:	2.5547500451e-05
total merit:	2.5547500451e-05
tot. defect L1:	2.51634709028e-10
tot. defect L2:	1.43073956603e-10
box cstr.err:	0
gen cstr.err:	0
total lx norm:	0.0014577312921
total lu norm:	0.00149407034827
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.478999 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.001056 ms
[MultipleShooting]: prepareIteration() took 0.498655 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.082401 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.668408 ms
CONVERGED: Cost last iteration: 2.5547500451e-05, current cost: 2.55475004509e-05
CONVERGED: Cost improvement ratio was: 4.98097471319e-12x, which is lower than convergence criteria: 1e-05
[MultipleShooting]: Line search took 0.259802 ms
[MultipleShooting]: finishIteration() took 2.050324 ms
NLOC Summary of iteration 1
==============================
interm. cost:	2.55475004509e-05
final cost:	0
total cost:	2.55475004509e-05
total merit:	2.55475004509e-05
tot. defect L1:	9.6662586789e-15
tot. defect L2:	5.57313032555e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	3.23652730446e-07
total lu norm:	1.62208519741e-07
step-size:	1
                   ===========

After a while, when not updating the target pose, the total cost reaches values that are below 1e-20 and therefore the cost is basically zero. But from this point on with decreasing cost, the solver takes the maximum number of iterations which I allow him (in this case max_iterations 10) and does not converge. This is shown in the snippet below. It seems that the min_cost_improvement is higher than the set value of 1e-5. This seems like a strange behavior and I am not quite sure where this comes from. The extra iterations add computational burden, although the solution is already close to the optimal solution. Is there a way to tell the solver to stop, if the cost function is below a certain threshold?
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.47438 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000645 ms
[MultipleShooting]: prepareIteration() took 0.63293 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.053868 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.566991 ms
[MultipleShooting]: Line search took 0.293835 ms
[MultipleShooting]: finishIteration() took 2.093375 ms
NLOC Summary of iteration 0
==============================
interm. cost:	3.28868273545e-24
final cost:	0
total cost:	3.28868273545e-24
total merit:	3.28868273545e-24
tot. defect L1:	8.42533508239e-15
tot. defect L2:	4.26644419579e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	1.10425255353e-12
total lu norm:	7.82944425813e-13
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.583684 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.001324 ms
[MultipleShooting]: prepareIteration() took 0.619349 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.074126 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 2.2091 ms
[MultipleShooting]: Line search took 0.232863 ms
[MultipleShooting]: finishIteration() took 2.568211 ms
NLOC Summary of iteration 1
==============================
interm. cost:	3.28881634585e-24
final cost:	0
total cost:	3.28881634585e-24
total merit:	3.28881634585e-24
tot. defect L1:	2.45810316546e-15
tot. defect L2:	1.66204568742e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	3.25998057416e-14
total lu norm:	1.13660035377e-14
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.863663 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000267 ms
[MultipleShooting]: prepareIteration() took 0.925183 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.138291 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 2.634974 ms
[MultipleShooting]: Line search took 0.168189 ms
[MultipleShooting]: finishIteration() took 2.979734 ms
NLOC Summary of iteration 2
==============================
interm. cost:	3.28852413276e-24
final cost:	0
total cost:	3.28852413276e-24
total merit:	3.28852413276e-24
tot. defect L1:	1.58293517183e-15
tot. defect L2:	1.2237391438e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.41218172997e-14
total lu norm:	8.95038252024e-15
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.440116 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000263 ms
[MultipleShooting]: prepareIteration() took 0.453815 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.044917 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.251118 ms
[MultipleShooting]: Line search took 0.222637 ms
[MultipleShooting]: finishIteration() took 1.557543 ms
NLOC Summary of iteration 3
==============================
interm. cost:	3.28870013945e-24
final cost:	0
total cost:	3.28870013945e-24
total merit:	3.28870013945e-24
tot. defect L1:	1.65340831304e-15
tot. defect L2:	1.3163268746e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.38395660971e-14
total lu norm:	1.10918466669e-14
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.528867 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.00027 ms
[MultipleShooting]: prepareIteration() took 0.552437 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.056111 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.713249 ms
[MultipleShooting]: Line search took 0.200774 ms
[MultipleShooting]: finishIteration() took 2.023158 ms
NLOC Summary of iteration 4
==============================
interm. cost:	3.28851644819e-24
final cost:	0
total cost:	3.28851644819e-24
total merit:	3.28851644819e-24
tot. defect L1:	2.0554304786e-15
tot. defect L2:	1.47500058456e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.28980907349e-14
total lu norm:	1.06372254528e-14
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.531926 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000224 ms
[MultipleShooting]: prepareIteration() took 0.550905 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.051623 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.154027 ms
[MultipleShooting]: Line search took 0.190271 ms
[MultipleShooting]: finishIteration() took 1.425162 ms
NLOC Summary of iteration 5
==============================
interm. cost:	3.28871527512e-24
final cost:	0
total cost:	3.28871527512e-24
total merit:	3.28871527512e-24
tot. defect L1:	1.86114144929e-15
tot. defect L2:	1.32315381292e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.24836443448e-14
total lu norm:	1.09094994722e-14
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.431078 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000272 ms
[MultipleShooting]: prepareIteration() took 0.447214 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.046213 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.034877 ms
[MultipleShooting]: Line search took 0.148358 ms
[MultipleShooting]: finishIteration() took 1.251958 ms
NLOC Summary of iteration 6
==============================
interm. cost:	3.2885161854e-24
final cost:	0
total cost:	3.2885161854e-24
total merit:	3.2885161854e-24
tot. defect L1:	2.14650346109e-15
tot. defect L2:	1.42639357512e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.27114004542e-14
total lu norm:	1.10804170671e-14
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.470987 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000709 ms
[MultipleShooting]: prepareIteration() took 0.48419 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.048406 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.524463 ms
[MultipleShooting]: Line search took 0.186075 ms
[MultipleShooting]: finishIteration() took 1.787954 ms
NLOC Summary of iteration 7
==============================
interm. cost:	3.28872129738e-24
final cost:	0
total cost:	3.28872129738e-24
total merit:	3.28872129738e-24
tot. defect L1:	2.36833122558e-15
tot. defect L2:	1.58434773068e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.40905876824e-14
total lu norm:	1.13845519168e-14
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.60261 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.001238 ms
[MultipleShooting]: prepareIteration() took 0.644861 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.097242 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 4.771079 ms
[MultipleShooting]: Line search took 0.362574 ms
[MultipleShooting]: finishIteration() took 5.308231 ms
NLOC Summary of iteration 8
==============================
interm. cost:	3.28855135816e-24
final cost:	0
total cost:	3.28855135816e-24
total merit:	3.28855135816e-24
tot. defect L1:	1.97823528392e-15
tot. defect L2:	1.52524870452e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.26347477522e-14
total lu norm:	1.02842944755e-14
step-size:	1
                   ===========

[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.989535 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000959 ms
[MultipleShooting]: prepareIteration() took 1.047483 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.125472 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 4.230373 ms
[MultipleShooting]: Line search took 0.217366 ms
[MultipleShooting]: finishIteration() took 4.630155 ms
NLOC Summary of iteration 9
==============================
interm. cost:	3.2887120875e-24
final cost:	0
total cost:	3.2887120875e-24
total merit:	3.2887120875e-24
tot. defect L1:	2.25644156138e-15
tot. defect L2:	1.67321335857e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.46348231876e-14
total lu norm:	1.12360887914e-14
step-size:	1
                   ===========

I use HPIPM and my solver settings are:
solver_settings
{
    nlocp_algorithm GNMS
    integrator EulerCT
    useSensitivityIntegrator false
    discretization Forward_euler
    timeVaryingDiscretization false
    dt 0.04
    K_sim 1
    K_shot 5
    epsilon 0
    max_iterations 3
    fixedHessianCorrection false
    recordSmallestEigenvalue false
    min_cost_improvement 1e-5
    maxDefectSum 1e-5
    meritFunctionRho 0.0
    meritFunctionRhoConstraints 0.0
    nThreads 1
    nThreadsEigen 1
    printSummary true
    debugPrint true
    ; logToMatlab 0

    line_search
    {
        type NONE
        adaptive false
        maxIterations 10
        alpha_0 1.0
        n_alpha 0.5
        debugPrint true
    }
}

Hi, my recommendation is to run only a single iteration in every mpc cycle!

Am 25.02.2021 um 14:19 schrieb awa152<EMAIL_ADDRESS>
I am encountering some interesting behavior, when solving my problem in an receding horizon MPC routine.
When I update a new target pose, the first solution with GNMS takes 4 iterations and is shown below.
For that I set printSummary and debugPrint to true.
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 1.547365 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.002475 ms
[MultipleShooting]: prepareIteration() took 1.802402 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.184508 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 7.557204 ms
[MultipleShooting]: Line search took 0.310682 ms
[MultipleShooting]: finishIteration() took 8.339397 ms
NLOC Summary of iteration 0
interm. cost:	1.37565964361
final cost:	0
total cost:	1.37565964361
total merit:	1.37565964361
tot. defect L1:	0.212041106208
tot. defect L2:	0.0973813909403
box cstr.err:	0
gen cstr.err:	0
total lx norm:	26.319324674
total lu norm:	14.9739679897
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.608909 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.00051 ms
[MultipleShooting]: prepareIteration() took 0.635876 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.056361 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 5.166026 ms
[MultipleShooting]: Line search took 0.329641 ms
[MultipleShooting]: finishIteration() took 5.602459 ms
NLOC Summary of iteration 1
interm. cost:	1.31085060474
final cost:	0
total cost:	1.31085060474
total merit:	1.31085060474
tot. defect L1:	0.0141449671345
tot. defect L2:	0.00663556822773
box cstr.err:	0
gen cstr.err:	0
total lx norm:	5.41752561809
total lu norm:	2.80196187147
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 1.163349 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.0083 ms
[MultipleShooting]: prepareIteration() took 1.25171 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.132047 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 9.610376 ms
[MultipleShooting]: Line search took 0.325102 ms
[MultipleShooting]: finishIteration() took 10.132516 ms
NLOC Summary of iteration 2
interm. cost:	1.30993248119
final cost:	0
total cost:	1.30993248119
total merit:	1.30993248119
tot. defect L1:	0.000102134243653
tot. defect L2:	5.92240828319e-05
box cstr.err:	0
gen cstr.err:	0
total lx norm:	0.626441226336
total lu norm:	0.467186996374
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.824793 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000609 ms
[MultipleShooting]: prepareIteration() took 0.858036 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.086972 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 5.188592 ms
CONVERGED: Cost last iteration: 1.30993248119, current cost: 1.30992095926
CONVERGED: Cost improvement ratio was: 8.79581434371e-06x, which is lower than convergence criteria: 1e-05
[MultipleShooting]: Line search took 0.323568 ms
[MultipleShooting]: finishIteration() took 5.640796 ms
NLOC Summary of iteration 3
interm. cost:	1.30992095926
final cost:	0
total cost:	1.30992095926
total merit:	1.30992095926
tot. defect L1:	1.22957074048e-06
tot. defect L2:	5.56606391229e-07
box cstr.err:	0
gen cstr.err:	0
total lx norm:	0.0728548958297
total lu norm:	0.0599693717847
step-size:	1
===========
When the new target is reached the iterations basically look like the one below, which take 2 iterations to converge.
The total cost is quite low, as the current position and the target position are nearly the same.
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.918522 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.001294 ms
[MultipleShooting]: prepareIteration() took 1.213108 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.110336 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 3.195401 ms
[MultipleShooting]: Line search took 0.203796 ms
[MultipleShooting]: finishIteration() took 3.71993 ms
NLOC Summary of iteration 0
interm. cost:	2.5547500451e-05
final cost:	0
total cost:	2.5547500451e-05
total merit:	2.5547500451e-05
tot. defect L1:	2.51634709028e-10
tot. defect L2:	1.43073956603e-10
box cstr.err:	0
gen cstr.err:	0
total lx norm:	0.0014577312921
total lu norm:	0.00149407034827
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.478999 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.001056 ms
[MultipleShooting]: prepareIteration() took 0.498655 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.082401 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.668408 ms
CONVERGED: Cost last iteration: 2.5547500451e-05, current cost: 2.55475004509e-05
CONVERGED: Cost improvement ratio was: 4.98097471319e-12x, which is lower than convergence criteria: 1e-05
[MultipleShooting]: Line search took 0.259802 ms
[MultipleShooting]: finishIteration() took 2.050324 ms
NLOC Summary of iteration 1
interm. cost:	2.55475004509e-05
final cost:	0
total cost:	2.55475004509e-05
total merit:	2.55475004509e-05
tot. defect L1:	9.6662586789e-15
tot. defect L2:	5.57313032555e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	3.23652730446e-07
total lu norm:	1.62208519741e-07
step-size:	1
===========
After a while, when not updating the target pose, the total cost reaches values that are below 1e-20 and therefore the cost is basically zero. But from this point on with decreasing cost, the solver takes the maximum number of iterations which I allow him (in this case max_iterations 10) and does not converge. This is shown in the snippet below. It seems that the min_cost_improvement is higher than the set value of 1e-5. This seems like a strange behavior and I am not quite sure where this comes from. The extra iterations add computational burden, although the solution is already close to the optimal solution. Is there a way to tell the solver to stop, if the cost function is below a certain threshold?
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.47438 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000645 ms
[MultipleShooting]: prepareIteration() took 0.63293 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.053868 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.566991 ms
[MultipleShooting]: Line search took 0.293835 ms
[MultipleShooting]: finishIteration() took 2.093375 ms
NLOC Summary of iteration 0
interm. cost:	3.28868273545e-24
final cost:	0
total cost:	3.28868273545e-24
total merit:	3.28868273545e-24
tot. defect L1:	8.42533508239e-15
tot. defect L2:	4.26644419579e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	1.10425255353e-12
total lu norm:	7.82944425813e-13
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.583684 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.001324 ms
[MultipleShooting]: prepareIteration() took 0.619349 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.074126 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 2.2091 ms
[MultipleShooting]: Line search took 0.232863 ms
[MultipleShooting]: finishIteration() took 2.568211 ms
NLOC Summary of iteration 1
interm. cost:	3.28881634585e-24
final cost:	0
total cost:	3.28881634585e-24
total merit:	3.28881634585e-24
tot. defect L1:	2.45810316546e-15
tot. defect L2:	1.66204568742e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	3.25998057416e-14
total lu norm:	1.13660035377e-14
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.863663 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000267 ms
[MultipleShooting]: prepareIteration() took 0.925183 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.138291 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 2.634974 ms
[MultipleShooting]: Line search took 0.168189 ms
[MultipleShooting]: finishIteration() took 2.979734 ms
NLOC Summary of iteration 2
interm. cost:	3.28852413276e-24
final cost:	0
total cost:	3.28852413276e-24
total merit:	3.28852413276e-24
tot. defect L1:	1.58293517183e-15
tot. defect L2:	1.2237391438e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.41218172997e-14
total lu norm:	8.95038252024e-15
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.440116 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000263 ms
[MultipleShooting]: prepareIteration() took 0.453815 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.044917 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.251118 ms
[MultipleShooting]: Line search took 0.222637 ms
[MultipleShooting]: finishIteration() took 1.557543 ms
NLOC Summary of iteration 3
interm. cost:	3.28870013945e-24
final cost:	0
total cost:	3.28870013945e-24
total merit:	3.28870013945e-24
tot. defect L1:	1.65340831304e-15
tot. defect L2:	1.3163268746e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.38395660971e-14
total lu norm:	1.10918466669e-14
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.528867 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.00027 ms
[MultipleShooting]: prepareIteration() took 0.552437 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.056111 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.713249 ms
[MultipleShooting]: Line search took 0.200774 ms
[MultipleShooting]: finishIteration() took 2.023158 ms
NLOC Summary of iteration 4
interm. cost:	3.28851644819e-24
final cost:	0
total cost:	3.28851644819e-24
total merit:	3.28851644819e-24
tot. defect L1:	2.0554304786e-15
tot. defect L2:	1.47500058456e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.28980907349e-14
total lu norm:	1.06372254528e-14
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.531926 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000224 ms
[MultipleShooting]: prepareIteration() took 0.550905 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.051623 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.154027 ms
[MultipleShooting]: Line search took 0.190271 ms
[MultipleShooting]: finishIteration() took 1.425162 ms
NLOC Summary of iteration 5
interm. cost:	3.28871527512e-24
final cost:	0
total cost:	3.28871527512e-24
total merit:	3.28871527512e-24
tot. defect L1:	1.86114144929e-15
tot. defect L2:	1.32315381292e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.24836443448e-14
total lu norm:	1.09094994722e-14
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.431078 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000272 ms
[MultipleShooting]: prepareIteration() took 0.447214 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.046213 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.034877 ms
[MultipleShooting]: Line search took 0.148358 ms
[MultipleShooting]: finishIteration() took 1.251958 ms
NLOC Summary of iteration 6
interm. cost:	3.2885161854e-24
final cost:	0
total cost:	3.2885161854e-24
total merit:	3.2885161854e-24
tot. defect L1:	2.14650346109e-15
tot. defect L2:	1.42639357512e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.27114004542e-14
total lu norm:	1.10804170671e-14
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.470987 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000709 ms
[MultipleShooting]: prepareIteration() took 0.48419 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.048406 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 1.524463 ms
[MultipleShooting]: Line search took 0.186075 ms
[MultipleShooting]: finishIteration() took 1.787954 ms
NLOC Summary of iteration 7
interm. cost:	3.28872129738e-24
final cost:	0
total cost:	3.28872129738e-24
total merit:	3.28872129738e-24
tot. defect L1:	2.36833122558e-15
tot. defect L2:	1.58434773068e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.40905876824e-14
total lu norm:	1.13845519168e-14
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.60261 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.001238 ms
[MultipleShooting]: prepareIteration() took 0.644861 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.097242 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 4.771079 ms
[MultipleShooting]: Line search took 0.362574 ms
[MultipleShooting]: finishIteration() took 5.308231 ms
NLOC Summary of iteration 8
interm. cost:	3.28855135816e-24
final cost:	0
total cost:	3.28855135816e-24
total merit:	3.28855135816e-24
tot. defect L1:	1.97823528392e-15
tot. defect L2:	1.52524870452e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.26347477522e-14
total lu norm:	1.02842944755e-14
step-size:	1
===========
[MultipleShooting]: computing LQ Approximation from index 5 to N-1 took 0.989535 ms
[MultipleShooting]: Solving prepare stage of LQOC Problem
[MultipleShooting]: Prepare phase of LQOC problem took 0.000959 ms
[MultipleShooting]: prepareIteration() took 1.047483 ms
[MultipleShooting]: computing LQ approximation for first multiple-shooting interval took 0.125472 ms
[MultipleShooting]: Finish phase LQOC Problem
[MultipleShooting]: Finish solving LQOC problem took 4.230373 ms
[MultipleShooting]: Line search took 0.217366 ms
[MultipleShooting]: finishIteration() took 4.630155 ms
NLOC Summary of iteration 9
interm. cost:	3.2887120875e-24
final cost:	0
total cost:	3.2887120875e-24
total merit:	3.2887120875e-24
tot. defect L1:	2.25644156138e-15
tot. defect L2:	1.67321335857e-15
box cstr.err:	0
gen cstr.err:	0
total lx norm:	2.46348231876e-14
total lu norm:	1.12360887914e-14
step-size:	1
===========
I use HPIPM and my solver settings are:
solver_settings
{
nlocp_algorithm GNMS
integrator EulerCT
useSensitivityIntegrator false
discretization Forward_euler
timeVaryingDiscretization false
dt 0.04
K_sim 1
K_shot 5
epsilon 0
max_iterations 3
fixedHessianCorrection false
recordSmallestEigenvalue false
min_cost_improvement 1e-5
maxDefectSum 1e-5
meritFunctionRho 0.0
meritFunctionRhoConstraints 0.0
nThreads 1
nThreadsEigen 1
printSummary true
debugPrint true
; logToMatlab 0
line_search
{
    type NONE
    adaptive false
    maxIterations 10
    alpha_0 1.0
    n_alpha 0.5
    debugPrint true
}

}
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Hi @markusgft,
thank you for the fast answer. If we don't consider the computational effort for a moment, wouldn't be a single iteration to little for the solver to come close to an optimal solution?
Also I noticed that despite giving the MPC class a NLOptConSettings instance with a max_iterations count of greater than one, it always seems to make only a single iteration. At least it always prints out an Iteration count of 0 when I set printSummary to true. I don't know if this is intended like this.
That's why I use NLOptConSolver directly and if needed the solver takes the amount of iterations set in max_iterations.

Doing only iteration is a very Standard approach in MPC. You can use the additional bandwidth to send controller updates more frequently

Am 26.02.2021 um 10:37 schrieb awa152<EMAIL_ADDRESS>
Hi @markusgft,
thank you for the fast answer. If we don't consider the computational effort for a moment, wouldn't be a single iteration to little for the solver to come close to an optimal solution?
Also I noticed that despite giving the MPC class a NLOptConSettings instance with a max_iterations count of greater than one, it always seems to make only a single iteration. At least it always prints out an Iteration count of 0 when I set printSummary to true. I don't know if this is intended like this.
That's why I use NLOptConSolver directly and if needed the solver takes the amount of iterations set in max_iterations.
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Thank you for the input @markusgft


Backport "HBASE-25653 Add units and round off region size to 2 digits after decimal (#3046)" to branch-2.3

Signed-off-by: stack<EMAIL_ADDRESS>Reviewed-by: Viraj Jasani<EMAIL_ADDRESS>

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[ISSUE #406] Github Actions: Resource not accessible by integration

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Admin only Swarm master

Running three containers on a three host cluster, with spread strategy, shows the following output:
CONTAINER ID        IMAGE                                  COMMAND                CREATED              STATUS              PORTS                           NAMES
7351d1490c5c        arungupta/wildfly-mysql-javaee7:host   "/opt/jboss/wildfly/   About a minute ago   Up About a minute   <IP_ADDRESS>:8081->8080/tcp   swarm-master/mywildfly2
fd49a228591d        arungupta/wildfly-mysql-javaee7:host   "/opt/jboss/wildfly/   5 minutes ago        Up 4 minutes        <IP_ADDRESS>:8080->8080/tcp   swarm-node-02/mywildfly
b49d627a0431        mysql:latest                           "/entrypoint.sh mysq   About an hour ago    Up About an hour    <IP_ADDRESS>:3306->3306/tcp   swarm-node-01/mysqldb

A container is started one each on master and two other nodes. It would be beneficial where Swarm master can be made purely admin-only, where no containers are deployed on it.

@arun-gupta Are you using docker-machine? In this case the Swarm Master will also have a Swarm Agent running on this same machine. It makes sense to have the Master "being" a Swarm Agent so you can use spare resources from the Master to schedule containers onto it.
If you want the master to be admin only, you can use docker-machine to create your regular Swarm agents VMs (the same way you did here), and then at the end, launch a non-swarm docker machine and setup the Swarm Manager the usual way.

@arun-gupta you can always use -e node!=swarm-master when you do a docker run ;)

Having an admin-only Swarm master would be a usual design pattern and should be supported easily.

@arun-gupta It's supported out of the box, actually, that's the default. You are explicitly running swarm join on the swarm-master machine, which is effectively putting the master into the rotation.

@aluzzardi The cluster is created as:
docker-machine create -d virtualbox --swarm --swarm-master --swarm-discovery token://e59c8e65543eb2e7e9e90164c288cc61 swarm-master

What should be the updated command?

@arun-gupta Did you run something like docker-machine create -d virtualbox --swarm join on the swarm-master? If you did, you shouldn't have to in order to achieve what you want.

I'm having this same problem. I would like docker-machine to create the swarm-master without having it join the swarm as a node eligible for receiving containers. In fact I was sure this is how docker-machine worked in 0.2.0. However since upgrading to 0.3.0 this behavior seems to have changed. @vieux may have the best option for the moment.
I think this output below shows that it runs a 'join' container when it shouldn't?
docker-machine create --driver virtualbox --swarm --swarm-master --swarm-discovery token://a1433143888ea2ae299efa8f656a5c93 localmaster
Creating VirtualBox VM...
Creating SSH key...
Starting VirtualBox VM...
Starting VM...
To see how to connect Docker to this machine, run: docker-machine env localmaster
~  eval "$(docker-machine env localmaster)"
~  docker ps -a
CONTAINER ID        IMAGE               COMMAND                CREATED             STATUS              PORTS                              NAMES
646ab3a5bb95        swarm:latest        "/swarm join --addr    16 seconds ago      Up 13 seconds       2375/tcp                           swarm-agent
caa4c50e15f8        swarm:latest        "/swarm manage --tls   16 seconds ago      Up 13 seconds       2375/tcp, <IP_ADDRESS>:3376->3376/tcp   swarm-agent-master

@nathanleclaire Is it possible to create a VM with docker-machine with only a Swarm Manager running on it as per 0.5.0? Seems to me that we always create an Agent alongside the Manager right?

@abronan So far, yes.  https://github.com/docker/machine/issues/2302#issuecomment-157553786 proposes one possible solution to the issue.

Closing in favor of docker/machine#2302. Let's continue the discussion here as this is related to docker-machine.


Crash Report: update failed for AnAction(nl.rubensten.texifyidea.action.sumatra.ForwardSearchAction) with ID=texify.sumatra.ForwardSearch

Description
Stacktrace
Please paste the full stacktrace from the IDEA error popup

Thank you for reporting! This is a duplicate of #432, please use that issue for any additional comments and updates.


Schema and table name for sheet name

Would be nice to have the sheet name parsed into table and schema name.
if there is dot notation, we can do something like this:
dev.dinosaurs --> `dev`.`dinosaurs`

Done with last commit.


Add storage store and get for b256

Currently, store and get from the storage library in lib-std only allow basic copy types as they use srw and sww under the hood (read/write 1 word). It would be useful to also allow reading/writing a b256 using srwq/swwq. Even though the new storage syntax (via the storage keyword) is now implemented, it is still not possible to use it for mappings. Therefore, something like store_b256 and get_b256 would be useful to implement b256 -> b256 mappings.
E.g. (courtesy of @SilentCicero):
library storage_b256;

pub fn store_b256(key: b256, value: b256) {
    asm(r1: key, r2: value) {
        swwq r1 r2;
    };
}

pub fn get_b256(key: b256) -> b256 {
    asm(r1: key, r2) {
        srwq r2 r1;
        r2: T
    }
}

More generally, the store<T> and get<T> functions would accept a b256, but that would require checking wheter T is a b256 before deciding what to do. The is_reference_type<T> function may come in handy here.

Note that this was one of the primary motivations of #1119: https://github.com/FuelLabs/sway/issues/1119#issuecomment-1084539569
No store_xxx is needed, since store is already generic.

@adlerjohn so should the above library be implemented for now?
Just until we can depreciate with proper reference checking where we can just use store get with proper generics?

No, it should not. See the above-linked issue for what should be implemented.


[Ubuntu] Document tar version

Description
Related issue: https://github.com/actions/runner-images/issues/6387
Check list

[X] Related issue / work item is attached
[ ] Tests are written (if applicable)
[ ] Documentation is updated (if applicable)
[ ] Changes are tested and related VM images are successfully generated

/azp run ubuntu1804,ubuntu2004,ubuntu2204


IPv6

Not sure if this fits the issue category as it is more of a general question (but it might result in a feature request).
Is it possible to block IPv6 in addition to IPv4?
I.e., in addition to <IP_ADDRESS>, map domains to :: (or ::/0 ?).
As far as I can see, I can only do either one or the other via the -R option.
Best, Oli

It is possible to generate a hosts file with both IPv4 and IPv6 entries but I don't quite understand the point of this, why do you need to have both entries? In principle with either of them in the hosts file you should block access to the domain.
To do this you can ignore the -R option and directly use the following template with the -T option.
hblock -T '<IP_ADDRESS> %D\n:: %D' -O ./hosts

Hi Hector,
sorry, I forgot to mention that this is macOS-specific.
I'm really far from an expert in this, but according to https://macnative.com/why-is-macos-ignoring-hosts-file-entries/ macOS prefers IPv6 over IPv4, including DNS queries, when configured accordingly. This is what I experienced ("normal" ping to a blocked domain: Socket not connected, ping6: host resolved and responding) after I had set up IPv6 support in my local environment (client devices/router etc.).
Thank you very much for the template. While I know that this is really not optimal as it basically doubles the file size, this makes the "blocking" work again with IPv6 enabled.
Best, Oli

I'm glad this solved your use case. Also thanks for your sponsorship on GitHub!

Slight correction (saw #113 just by chance, will comment there as well):
For macOS, the command needs to be
hblock -T '<IP_ADDRESS> %D\n:: %D' -O
otherwise the hosts file is created in the root of the macOS user home folder.
By omitting to explicitly set the  output file ./hosts, the default macOS path for the hosts file /etc/hosts is used.


Data loss when using jdbc batch insert to ReplicatedMergeTree engine.

Describe the bug
The data was loss when using jdbc batch insert into ReplicatedMergeTree engine based table. there was no Exception and Error . Be there any suggestions for following code fragments , Thanks .
private def batchLoad(pendingMap: HashMap[String, ListBuffer[AsdBase]], maxPendingSize: Int, config: Config): Unit = {
pendingMap.foreach(tuple => {
  val (tableName, pendingBuffer) = (tuple._1, tuple._2)
  if (pendingBuffer.size >= maxPendingSize) {
    val clickHouseURL = config.getString("clickhouse.url")
    val dataSource = new BalancedClickhouseDataSource(clickHouseURL)
    dataSource.scheduleActualization(3, java.util.concurrent.TimeUnit.SECONDS)
    val connection = dataSource.getConnection

    val insertSql = s"INSERT INTO ${tableName} (request_time, advertiser_id, order_id, exe_lineitem_id, lineitem_path, deal_id, pyid, platform, city_id, mobile_device_type, os) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)".stripMargin
    val statement = connection.prepareStatement(insertSql)

    pendingBuffer.map(asdBase => {
      statement.setString(1, asdBase.requestTime)
      statement.setLong(2, asdBase.advertiserId)
      statement.setLong(3, asdBase.orderId)
      statement.setLong(4, asdBase.exeCampaignId)
      statement.setString(5, asdBase.lineItemPath)
      statement.setLong(6, asdBase.dealId)
      statement.setString(7, asdBase.pyid)
      statement.setString(8, asdBase.platform)
      statement.setLong(9, asdBase.cityId)
      statement.setString(10, asdBase.mobileDeviceType)
      statement.setString(11, asdBase.os)
      statement.addBatch()
    })

    try {
      statement.executeBatch()
      println(s"loading ${pendingBuffer.size} records into ck table: $tableName")
      pendingBuffer.clear()

    } catch {
      case e: Exception => {
        e.printStackTrace()
      }
    } finally {
      statement.close()
      connection.close()
    }
  }
})

}

Did you check *Replicated data deduplication ?
Try the same with simple MergeTree
https://clickhouse.yandex/docs/en/operations/table_engines/replication/?highlight=deduplicated
Data blocks are deduplicated. For multiple writes of the same data block (data blocks of the same size containing the same rows in the same order), the block is only written once. The reason for this is in case of network failures when the client application doesn't know if the data was written to the DB, so the INSERT query can simply be repeated. It doesn't matter which replica INSERTs were sent to with identical data. INSERTs are idempotent. Deduplication parameters are controlled by merge_tree server settings.

No , I didn't . I want to save the logs they are repeatable when using ReplicatedMergeTree engine . " Deduplication parameters are controlled by merge_tree server settings " , Do you mean I should reduce the " replicated_deduplication_window " parameter ?

I meant need to understand the root cause. Try to reproduce the issue against MergeTree.

@Giant1 did you find the problem?


Add TD Waterhouse to Investing

For example, you will not be able to access any of our secured sites as cookies are used for security and multi-factor authentication [...]
- http://www.tdwaterhouse.ca/popup/privategiving/privacypolicy.jsp (Our use of Cookies)

Something you know + something you have. I'm guessing that's two factors then (even though it's not a very good method...)

I'm going with @ESWAT on this one. Cookies are not TFA. Cookies should not be used as part of a TFA solution since they can be modified by the client. So someone could bypass the TFA on my account by just crafting a cookie saying they'd already provided the second factor. If they have an actual TFA implementation, I'd want to see proper documentation, not a reference to it in the site's privacy policy.

But that's kinda like most other TFA providers solutions. If one sent a maliciously crafted post request to some provider's API, let's say Transakt, they would go ahead and accept that user.
It's something you have isn't it? Just like MFA schemes and usb keys. Just because it isn't a good solution doesn't mean it isn't a solution. MFA schemes can be modified by the client. Apps can be modified by the client. REST-like http requests can be modified by the client.
I don't think they use it to let the user bypass logins but use it to store a 'secret' key to use when logging in.

So what happens if I don't have those cookies? How would I get those cookies in the 1st place?
Perhaps we should not accept "isn't a good solution" as 2fa. Do it right or don't project false sense of security.

As they say in that post, you wouldn't get in to your online banking page.
Okay I'm down for adding cookies to a blacklist.

I still don't understand. I have a brand new computer, it doesn't have any cookies, how would I login then?

Yeah I don't get it either.

I think their text is misleading. All you need to log into their "secured sites" is a username and password, and I guess the cookie they’re referring to is generated after that since to perform specific actions may require another factor (or I don’t understand how generating a cookie before authentication would help).

They won’t let you log in if you have cookies disabled (just tried this).

Most people (including Google) use cookies and local storage to authenticate computers that are "trusted", but it doesn't make sense if TD doesn't have any second factor required in the first place.


Test optional props after new DB indexing is finished

data v detailu
(Subject Entity Type, valency props, statement text etc.)

db imported


Add Lidl E14 model for CCT quirk

https://github.com/zigpy/zha-device-handlers/issues/643#issuecomment-751415102
(Should be tested first by @mwsimmonite)
("instructions" here: https://github.com/zigpy/zha-device-handlers/issues/643#issuecomment-748688320)

Codecov Report

Merging #672 (c90ed1f) into dev (b97c196) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##              dev     #672   +/-   ##
=======================================
  Coverage   81.17%   81.17%
=======================================
  Files         166      166
  Lines        3767     3767
=======================================
  Hits         3058     3058
  Misses        709      709

Impacted Files
Coverage Δ

zhaquirks/lidl/cct.py
100.00% <ø> (ø)

Continue to review full report at Codecov.

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Pull Request Test Coverage Report for Build 446398865

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 81.179%

Totals

Change from base Build 438478310:
0.0%

Covered Lines:
3058

Relevant Lines:
3767

💛  - Coveralls

I have tested this and it works in my config, correcting the E14 bulbs as the previous fix did the E27 ones


A little mistake

"At least 50 images per label for the training set are recommended as a starting point. With fewer images, there's a strong risk that you're overfitting."
Did you mean underfitting ?

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: fdb2597d-a612-4cd2-3005-85ab51574f01
Version Independent ID: 84c078ba-b424-e81d-4dd1-1eb14b11d378
Content: Improving your classifier - Custom Vision Service
Content Source: articles/cognitive-services/Custom-Vision-Service/getting-started-improving-your-classifier.md
Service: cognitive-services
GitHub Login: @PatrickFarley
Microsoft Alias: pafarley

@Slaaaap
Thanks for the feedback! We are currently investigating and will update you shortly.

@Slaaaap Hi, for here overfitting is right. Overfitting is a modeling error which occurs when a function is too closely fit to a limited set of data points. Fewer data will bring more bias problems, since the model represents a small model well but will not work well a bigger model. If the model fit in fewer than 50 photos well, which means that it fit in a small model. That small volume training examples can not represent most of the real world photos. Compare to a real world( a big model with more details and feature), it is overfitting.

@Slaaaap Hi, for here overfitting is right. Overfitting is a modeling error which occurs when a function is too closely fit to a limited set of data points. Fewer data will bring more bias problems, since the model represents a small model well but will not work well a bigger model. If the model fit in fewer than 50 photos well, which means that it fit in a small model. That small volume training examples can not represent most of the real world photos. Compare to a real world( a big model with more details and feature), it is overfitting.


Update README.md

Update android readme to the correct directory of setup.py

seen. Thank you
On Mon, Jun 29, 2020 at 7:17 PM Shivay Lamba<EMAIL_ADDRESS>wrote:

@shivaylamba approved this pull request.
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TypeError when calling AudioConfig.fromWavFileInput in the JS SDK.

In my index.html I have the following scripts which are largely taken from the JS browser sample.
<!-- Speech SDK REFERENCE -->
<script src="https://aka.ms/csspeech/jsbrowserpackageraw"></script>

<!-- Speech SDK presence check -->
<script>
  // On document load resolve the Speech SDK dependency
  function Initialize(onComplete) {
      if (!!window.SpeechSDK) {
          onComplete(window.SpeechSDK);
      }
  }
</script>

<script>
  document.addEventListener("DOMContentLoaded", function () {
    var SpeechSDK;

    Initialize(function (speechSdk) {
        SpeechSDK = speechSdk;
    });
  });
</script>

<script>
  const speechTranslationConfig = SpeechSDK.SpeechTranslationConfig.fromSubscription("subscriptionkey", "region");
  const audioConfig = SpeechSDK.AudioConfig.fromWavFileInput("classroom-german.wav");
</script>

I get the following error.
Uncaught TypeError: Cannot read properties of undefined (reading 'slice')
    at FileAudioSource.readHeader (jsbrowserpackageraw:29862:36)
    at new FileAudioSource (jsbrowserpackageraw:29775:44)
    at Function.AudioConfig.fromWavFileInput (jsbrowserpackageraw:4479:36)
    at index.html:52:49

The line throwing the error is line 202 from FileAudioSource.ts: processHeader(h.buffer.slice(h.byteOffset, h.byteOffset + h.byteLength));
My package.json is as follows.
{
  "name": "speech-web-app",
  "version": "0.1.0",
  "private": true,
  "dependencies": {
    "microsoft-cognitiveservices-speech-sdk": "^1.20"
  }
}

From a browser you'll need to pass a File object and not a file name. The SDK won't try to read arbitrary files, and the support for file names is for use from NodeJS.
There should be a better error message for that scenario, thought.

From a browser you'll need to pass a File object and not a file name. The SDK won't try to read arbitrary files, and the support for file names is for use from NodeJS.
There should be a better error message for that scenario, thought.

Thanks, that was the problem.


localtunnel is down?

Hi @TheBoroer ,
Seems like localtunnel is not accessible. I am getting this error when I try to access the site:

Would appreciate your help in checking this. Thanks! 🙇

Yes, I guess localtunnel is down. Not able to access it.

Hey! The server will be back up shortly.
I was performing some maintenance to the underlying physical host.

Is the Local tunnel back online @TheBoroer ??

Hey! thank you for your great project and efforts. is there any estimation about the time that the project is back online?

Getting 404 error even after running tunnel.

Yes, there is no usual output "your url is:" from the client. No output at all.

Seems not yet up. With enabled debug output:
localtunnel:client tunnel server offline: Request failed with status code 502, retry 1s +2s

I think it started working

I think it started working
I don't think so.

I think it started working
I don't think so.

Can you please try to restart that?

localtunnel:client tunnel server offline: Hostname/IP does not match certificate's altnames: Host: localtunnel.me. is not in the cert's altnames: DNS:*.loca.lt, DNS:loca.lt, retry 1s +2s

Still down. I am also getting the cert warning like @vagran

It is Fixed. 💯

Hey everyone! it should be up and working now :)  lmk if theres any issues

Seems like it's fixed! Thank you! 🎉

I still can't access the website....

@andremourasantos
Could you give me more details on what your having problems with (feel free to open another issue)? e.g. are you having trouble accessing the localtunnel service homepage/domain, or are you seeing errors, etc?

@andremourasantos Could you give me more details on what your having problems with (feel free to open another issue)? e.g. are you having trouble accessing the localtunnel service homepage/domain, or are you seeing errors, etc?

I can't open the localtunnel.me website: my browser says "This site can’t be reached".

I've tried the VS Code extension too, but it simply doesn't do anything when I do "start", even the port number and domain setup steps appear, but after that, nothing happens... No errors or something to share tho

It might be a dns or firewall/web-filtering issue on your end (or with your ISP).
What IP do you see when you ping localtunnel.me?
This shows that http and https works worldwide:
http://port.ping.pe/localtunnel.me:443
http://port.ping.pe/localtunnel.me:80
RE: vscode extension
I can't really troubleshoot this one since it's a community made product. Please try the localtunnel cli command. If it works, then you extension should work too.

The ip address that I got is: <IP_ADDRESS>.
I tried to run it directly from the terminal too, but nothing happens:

That's the right IP. Could you try running DEBUG=localtulpfile.jsunnel:client lt --port 8080 and check the output for any errors? Feel free to attach the logs

Seems like it couldn't run the command and it take way too long to get on it:

The only log file that I've here is this, it's from morning and I'm not sure what's it:
2021-11-29T15_41_33_512Z-debug.log
I'm a newbie and I'm trying to figure out how to do the things to help 😅

Thanks for that. The server is definitely online, with over 2000 active tunnels at the moment and seems to be working fine.
This looks like a firewall/content filtering issue on your end that's blocking access to the LT server.
Maybe try disabling any firewall/content filtering software or try another internet connection?

I tried to access it from my mobile data connection (on the computer), but the same error happens, even when I tried to access from my browser on mobile...


Hello, how do I run it?

Hello, how do I run it on an html page or a php page?

hi,
as this is a MagicMirror module, it won‘t work without the platform‘s infrastructure. Some code modifications would be necessary.
You would have to change the way how the generated elements are placed in the DOM.


Heapster not logging kubernetes events

We have a new GKE cluster setup and are using the InfluxDB sink with heapster. We see cpu, filesystem, network, memory, and uptime measurements as well as series in those measurements. However we do not have an events measurement. Heapster does not appear to be collecting k8s events.
We've tried doing several different things to generate events, which we do see in the k8s dashboard, but we do not see any logging that indicates an error with Heapster event collection and writing to InfluxDB and subsequently no measurement named events.
Is there any additional configuration that needs to be done to enable k8s collection by Heapster, so these events are written to the appropriate measurement in InfluxDB?

We realized that eventer needs to run as a separate container and have done so. We are now getting event data in InfluxDB. So this can be closed.
However, we only realized this after a lot of googling, because we could not find any mention of needing to do this in the heapster documentation. Relevant link that helped get the right manifest created for heapster: https://github.com/kubernetes/kubernetes/blob/master/cluster/addons/cluster-monitoring/influxdb/heapster-controller.yaml#L55


feat(updates): test updates

:tada: This PR is included in version 1.0.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Document the AKS Terraform module in README

# Summary
The created AKS module will need to be documented in its README.md file before we can port it to the official Jenkins X documentation.
Terraform modules documentation usually follow a defined structure. An example can be found in the terraform eks module:
https://github.com/terraform-aws-modules/terraform-aws-eks/blob/master/README.md
We'd need the following sections:

Assumptions: Any assumption on the current state of the Azure account, permissions etc.
Usage: how to use this module either by other Terraform scripts or a way to run it directly by Terraform.
Providers and their versions
Inputs
Outputs

The last three can be generated with https://github.com/segmentio/terraform-docs.
Acceptance Criteria
A README.md with all the required sections.

/close

@dgozalo would you please close this issue? It seems I don't have permission to do so

Closed by #23


feat: Amber, Lime and Yellow palettes and swatches

Closes #49

@rultor release, tag is 0.0.8

@rultor release, tag is 0.0.8

@rafamizes OK, I will release it now. Please check the progress here

@rultor release, tag is 0.0.8

@rafamizes Done! FYI, the full log is here (took me 2min)


This article should answer what you DONT support also

(I was looking for specifics on Azure AD but this could apply here aswell)
I think it could be helpful if this page take not if http artifact binding is supported or not.

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: e45e65a0-74ae-440c-0064-2a0b1c6bb0d9
Version Independent ID: a50f705d-ab3f-ca2b-aedd-9ab37bea3d3f
Content: Azure AD Connect: Use a SAML 2.0 Identity Provider for Single Sign On - Azure
Content Source: articles/active-directory/hybrid/how-to-connect-fed-saml-idp.md
Service: active-directory
Sub-service: hybrid
GitHub Login: @billmath
Microsoft Alias: billmath

@andreas-eg
Thanks for your feedback! We will investigate and update as appropriate.

@andreas-eg Thank you for the feedback.  Unfortunately it is not a common to document what is not supported as this can be quite exhaustive and detract from the purpose.  Thanks!
#please-close


Invalid access token

Hi ,i have got invalid access token please help me out for the same
API---> https://api.linkedin.com/v2/me/
{serviceErrorCode: 65600, message: "Invalid access token", status: 401}
message: "Invalid access token"
serviceErrorCode: 65600
status: 401
}

The token obtained from onSuccess of LinkedInModal contains the real access_token.
Try accessing the real token using:
token.access_token


Multiple Registrations w Same Name

This patch enhances Gofig to support multiple registrations using the same name. If two registrations both register the same key, only the first key is used.

Coverage decreased (-11.4%) to 79.885% when pulling 46f304a051a9b2451d1f9c192b6b6d2878daf9a0 on feature/multi-regs into e403cdba84cf4fbf931bf7bf5d86066dbab5b850 on master.


Create redirects from old API docs to new resource-oriented pages

Implement redirects from old pages (including anchors) to the new structure. For example: /docs/reference/pkg/nodejs/pulumi/aws/s3/#Bucket => /docs/reference/pkg/pulumi/aws/s3/Bucket/ (or whatever structure we end up with.

We don't need to do this anymore since we will link to these docs from the new cloud resource reference page.


Rednose breaks tests, multiple inheritance

Hi, I've run into a bizarre issue with rednose, python 3.5.2, Ubuntu 16.04.
Problem: when multiple inheritance is used rednose discards the failure. It depends on the order of defining test classes/methods.
The code to reproduce the problem:
$ cat test_rednose.py
import unittest

class FrontendCase(unittest.TestCase):
    pass

class BackendCase(unittest.TestCase):
    pass

class BackendUserCase(BackendCase):
    pass

class ExistingBackendUserCase(BackendUserCase):
    pass

class FrontendUserCase(FrontendCase, BackendUserCase):
    pass

class ExistingFrontendUserCase(FrontendUserCase, ExistingBackendUserCase):
    pass

class Test_0(FrontendUserCase):
    def test_dummy(self):
        pass

class Test_1(ExistingFrontendUserCase):
    def test_assertion(self):
        print("Should fail")
        self.assertTrue(False)

$ cat nosetests.cfg
[nosetests]
verbosity = 1
with-doctest = 0
logging-level = DEBUG
logging-format = "%(asctime)s %(name)-12s %(levelname)-8s %(module)s:%(lineno)s %(message)s"
nocapture = 1
nologcapture = 1
rednose = 1
processes = 1

Run it:

$ nosetests -c nosetests.cfg test_rednose.py
Should fail
.
----------------------------------------------------------------------
Ran 1 test in 0.031s

OK

Now, comment out rednose in nosetests.cfg and run again:
$ grep -v rednose nosetests.cfg > nosetests.without_rednose.cfg
$ nosetests -c nosetests.without_rednose.cfg test_rednose.py
.F
======================================================================
FAIL: test_assertion (test_rednose.Test_1)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "./test_rednose.py", line 30, in test_assertion
    self.assertTrue(False)
AssertionError: False is not true

----------------------------------------------------------------------
Ran 2 tests in 0.020s

FAILED (failures=1)

Voila, finally assertTrue(False) fails as it should.
This issue doesn't seem to be related to "--processes" in nosetests.
What is really bizarre is that:
a) if we just remove Test_0::test_dummy method (leaving Test_0 class empty), the assertion will properly fail.
b) The test method in Test_1 class is actually executed up to that assertion point.
I didn't debug rednose itself.
$ python -V
Python 3.5.2
$ uname -rmpov
4.4.0-62-generic #83-Ubuntu SMP Wed Jan 18 14:10:15 UTC 2017 x86_64 x86_64 GNU/Linux

I'll try to reproduce this later this week using your code and dig into it! Thanks for the bug report, what an odd bug.

hmmm cannot reproduce on mac on python3.6, I'll get 3.5 and see if I can. Might give you something with logging to run if I cannot reproduce it.

ohh wait
--rednose worked, but using the cfg didn't.

if I remove processes = 1 then it runs even with rednose.

hmmm it does seem like it works with everything but that library, the test output isn't even colored with processes = 1

[nosetests]
rednose = 1
processes = 1

alone breaks it.

I will look into it.

for example,
(rednose) josephkahn (2017-02-15 18:00:18)>~/dev/rednose (master)$ nosetests --rednose test_files/new_tests.py  --processes=1
.
----------------------------------------------------------------------
Ran 1 test in 0.235s

OK
(rednose) josephkahn (2017-02-15 18:00:31)>~/dev/rednose (master)$ nosetests --rednose test_files/new_tests.py
......

-----------------------------------------------------------------------------
6 tests run in 0.178 seconds (6 tests passed)

I started taking a look and this is non-trivial so I'm not sure I'll have time to do a crazy deep dive on it, it's an artifact of a really awful plugin api for nose. Colorizing the output shouldn't affect this at all, but it does.

I can comment all of rednose, except for
    def prepareTestResult(self, result):  # noqa
        """Required to prevent others from monkey patching the add methods."""
        return result

and it still breaks the multiprocess package but I can't see why that is.

Fixed in here: https://github.com/JBKahn/rednose/pull/22

I'm not sure it actually works, I think it might just be you cannot use them together and it's running only one of the two now.


get_matches() got 3 but has_match() only 1

Doing exercise from here
f) For the given list, filter all elements having a line starting with 'den' or ending with 'ly'.
items = ['love', '1\ndentist', 'fly\nfar', 'dent']
word = Indefinite(AnyLetter())
start_with_den = MatchAtLineStart("den" + word)
end_with_ly = MatchAtLineEnd(word + "ly")
pre = Either(start_with_den, end_with_ly)

The strange thing is that get_matches() finds 3, but . . .
for i, item in enumerate(items):
    print(i, pre.get_matches(item))

# 3 founds at item 1,2,3
0 []
1 ['dentist']
2 ['fly']
3 ['dent']

. . . while has_match() failed with some of the 3 founds!!
for i, item in enumerate(items):
    print(i, pre.has_match(item), item)

# only one True at item 3 ! <------- Problem should be 3 True
0 False love
1 False 1
dentist
2 False fly
far
3 True dent

That's definitely a bug, thanks for reporting it! I will make sure to fix it in the next version. For now, just try executing pre.compile() before executing pre.has_match so that you get the correct results :)

Yes! Add one line has really fixed the problem.
pre.compile()  # <--- add one line
for i, item in enumerate(items):
    print(i, pre.has_match(item), item)

# correct
0 False love
1 True 1
dentist
2 True fly
far
3 True dent

Yep! It's just that I've forgot to include some necessary RegEx flags when the pattern has not been compiled. Consider it fixed in the next version!

Closing this issue as it was fixed with the release of v2.3.3


Too many WebGL contexts error

Nothing bad seems to happen when I got it, but in the past, it would result in the editor going blank blue.

Is this in the Visual Editor or the website? The latter would make sense because we do spin up individual renderers for boards, but we shouldn't see it in the Visual Editor because we should be using a single context the whole time.

Yep, in Visual Editor

Ah, I figured out what it is. It's because when you close a tab we disconnect the graph renderer but we don't dispose of the Pixi app, which means the context sticks around. I'll sort a fix.

Fixed


Introduction

http://localhost/TechNotes/wp-admin/post.php?post=1533&action=edit
VSC:
http://localhost/lab/python/utilities/study_codes/opencodes.php?f=/Users/wtsang/Lab/python/jose_python_finance/

Errors
-bash: jupyter: command not found
-- solution https://stackoverflow.com/questions/39779744/after-installing-anaconda-command-not-found-jupyter


Determinism requirements list changed from any to all

The list of requirements for computed column determinism incorrectly states that "one or more" of the requirements must be met.  But in fact any of them will prevent determinism.

@davidbaxterbrowne : Thanks for your contribution! The author, @MikeRayMSFT, has been notified to review your proposed change.

@davidbaxterbrowne - thank you for this submission.
@joesackmsft or @kfarlee - would you mind validating this submission? Thank you.

@davidbaxterbrowne thank you for the submission.  #sign-off


Database Refactor: Remove UsedBy/Config from Projects

This adds the last chunk of changes needed for the v2 generator, and is currently in use by Projects.

Removes UsedBy and Config fields from db.Project.
Moves db/projects.go to use the version=2 generator.
Updates generator to support a references key, allowing for generation of Config and Devices methods on each entity.
Adds generated GetProjectConfig and CreateProjectConfig methods, generated as part of GetMany and Create generator comments, specified via references=Config.
Adds a URL method to api.Project.
Updates project.ToAPI() to accept a transaction argument to fill the config field.
Uses api.Project or explicitly passing in the config type map[string]string where we need to access the config.
adds projectUsedBy helper to lxd/api_projects.go and changes projectIsEmpty to return immediately if we know a project is used, rather than waiting for the result of projectUsedBy.

@markylaing The changes to lxd/db/generate/db/method_v2.go are likely going to be the final form of ClusterTx method generation for the db generator. We will likely want to avoid using anything in method.go and instead use v2 going forward.

@masnax unit tests are failing im afraid

@tomponline sorry about that, just a stubborn file that I deleted, which got resurrected by a rebase :)

@tomponline what's the state on this one?

@stgraber waiting for @masnax to make the changes then I'll look again.

@tomponline sorry, forgot to mention the changes have been made. Should be good to go.

@tomponline sorry, forgot to mention the changes have been made. Should be good to go.

Cheers, looking now.


Allow customisation of autocut value

Description
Window retriever uses weaviate autocut(1). It delivers too few results for my use case, and probably others. It would be good if this was please customisable between like 1-3. Or just maybe setting traditional score cut off, and max number of chunk windows retrieved.
It would be good to also surface the score of each result in the web ui.
Is this a bug or a feature?

[ ] Bug
[x] Feature

Yes, I agree! Good idea, we'll add it to the list

Added the configuration to the newest release!


Perform TCP connection via IPv6 and IPv4 in parallel threads

Current TCP connection function has these drawbacks.

Only first addresses (one IPv4 + one IPv6) from the resolver are used
Always connect via IPv4 first and fallback to IPv6 only if IPv4 has failed

Changes proposed in this pull request:

All addresses returned by the resolver are saved and cached
Run IPv6 and IPv4 connection in two parallel threads
Each thread makes connection attempts serially over a list of addresses
IPv4 thread starts with a 250ms delay to prioritize IPv6 (as per RFC 6555)
If IPv6 thread is not available or has failed, IPv4 thread starts without any delay

I have tested on Windows and Linux with IPv6/IPv4/NAT-T. More tests and comments are welcome.

Awesome!

@davidebeatrici I just discovered one bug in Protocol.c with regard to how we save the server IP for route management. I fixed it in the third commit.
Since you have done some massive refactor in the file, I want to have your opinion on this.
Currently Session->ServerIP is only used in route management, so basically we want it to be the actual connection endpoint, being whether the server's address (in direct connection) or the proxy's.
What I don't get is that since RemoteIP already contains the actual endpoint, why don't we just use it in non-direct connections? You can see from the current code that in that scenario, hostname contains the proxy address so we end up resolving the proxy IP once again. It doesn't make sense.
Currently when the connection is direct IPv4, we get ServerIP from GetIP which does not guarantee to return the actual address. (Note that GetIP is now IPv6-first). That causes the route management not working properly.
I propose to use RemoteIP as ServerIP whenever it's available and I have tested in direct and proxy modes. It seems working well. What do you think?
diff --git a/src/Cedar/Protocol.c b/src/Cedar/Protocol.c
index 748d88bb..94f2a682 100644
--- a/src/Cedar/Protocol.c
+++ b/src/Cedar/Protocol.c
@@ -6403,7 +6403,7 @@ SOCK *ClientConnectGetSocket(CONNECTION *c, bool additional_connect)

        if (additional_connect == false || IsZeroIP(&sock->RemoteIP))
        {
-               if (((sock->IsRUDPSocket || sock->IPv6) && IsZeroIP(&sock->RemoteIP) == false && o->ProxyType == PROXY_DIRECT) || GetIP(&c->Session->ServerIP, hostname) == false)
+               if (IsZeroIP(&sock->RemoteIP) == false || (sock->IPv6 && GetIP6(&c->Session->ServerIP, hostname) == false) || (sock->IPv6 == false && GetIP4(&c->Session->ServerIP, hostname) == false))
                {
                        Copy(&c->Session->ServerIP, &sock->RemoteIP, sizeof(c->Session->ServerIP));
                }

Do NAT-T and R-UDP still work after the change? They are the only thing I can think of that would require a different endpoint address.

Yes they work.

Okay, feel free to merge.

Merged. Thank you!


Add "namespace" option to i18n-js.yml

In some cases I'd like to export the I18n keys to a different Javascript namespace than I18n, to avoid conflicts. For example, I have a widget-type component which is embedded in third-party websites, and many of these sites already define the I18n namespace.
To do this, I have added an optional :namespace key to i18n-js.yml, which can be set per file.
Example:
translations:
  - file: "tmp/i18n-js/without_namespace.js"
    only: "*"
  - file: "tmp/i18n-js/with_namespace.js"
    namespace: "MyNamespace"
    only: "*"

This generates:
// tmp/i18n-js/with_namespace.js

MyNamespace.translations || (MyNamespace.translations = {});
MyNamespace.translations["en"] = {"test":"Test"};
MyNamespace.translations["fr"] = {"test":"Test2"};

In theory this should be a small change to implement, but the js.rb (exporter) code is written in a tightly-coupled fashion. I've refactored the code to extract a Segment class, which is extensible in case we'd like to add other similar options in the future. All tests are passing, and I've added additional tests specific to the new Segment class.
Note that I have not touched the Javascript here, only the Ruby-based exporter code. (JS could be a separate PR)

Closed in favor of #296


Add a "publish" branch of the GitHub repo, to be used instead of "master" for generating presentation data

This has been elaborated in a newer issue #330. So, I am closing this.


[WIP] Use Workspace to streamline project with quality

Codecov Report

Merging #52 into main will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##             main      #52   +/-   ##
=======================================
  Coverage   90.75%   90.75%
=======================================
  Files          31       31
  Lines         811      811
=======================================
  Hits          736      736
  Misses         75       75


The example area for this command is empty

The example area for this command is empty.

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 34c44e10-c678-ca4a-2a37-25d733c7c103
Version Independent ID: 5e931844-2def-11a9-fc57-eddb2216605b
Content: Test-CsInboundBlockedNumberPattern (skype)
Content Source: skype/skype-ps/skype/Test-CsInboundBlockedNumberPattern.md
Service: skypeforbusiness-powershell
GitHub Login: @tomkau
Microsoft Alias: tomkau

Thanks for noticing and reporting @sparkf1


[KYUUBI #1700] add wait lock thread count

Why are the changes needed?

Add KyuubiSyncThriftClient wait locks thread count
How was this patch tested?

[ ] Add some test cases that check the changes thoroughly including negative and positive cases if possible

[ ] Add screenshots for manual tests if appropriate

[x] Run test locally before make a pull request

can we update a report.json with offline test in the pr desc?

Codecov Report

Merging #1762 (349b859) into master (fbdbcb0) will decrease coverage by 0.18%.
The diff coverage is 100.00%.

@@             Coverage Diff              @@
##             master    #1762      +/-   ##
============================================
- Coverage     59.73%   59.55%   -0.19%
- Complexity      220      233      +13
============================================
  Files           267      268       +1
  Lines         13258    13309      +51
  Branches       1682     1688       +6
============================================
+ Hits           7920     7926       +6
- Misses         4660     4708      +48
+ Partials        678      675       -3

Impacted Files
Coverage Δ

...a/org/apache/kyuubi/metrics/MetricsConstants.scala
100.00% <ø> (ø)

.../apache/kyuubi/client/KyuubiSyncThriftClient.scala
91.80% <100.00%> (+0.13%)
:arrow_up:

...ache/kyuubi/engine/flink/FlinkProcessBuilder.scala
39.75% <0.00%> (-36.15%)
:arrow_down:

...rg/apache/kyuubi/operation/AbstractOperation.scala
62.68% <0.00%> (-7.32%)
:arrow_down:

...ain/scala/org/apache/kyuubi/engine/EngineRef.scala
79.00% <0.00%> (-7.00%)
:arrow_down:

...rg/apache/kyuubi/zookeeper/EmbeddedZookeeper.scala
86.66% <0.00%> (-0.44%)
:arrow_down:

...kyuubi/engine/spark/operation/SparkOperation.scala
82.89% <0.00%> (-0.24%)
:arrow_down:

...g/apache/kyuubi/engine/flink/result/Constants.java
50.00% <0.00%> (ø)

...ache/kyuubi/engine/flink/operation/GetTables.scala
86.48% <0.00%> (ø)

.../credentials/HadoopFsDelegationTokenProvider.scala
97.29% <0.00%> (+0.07%)
:arrow_up:

... and 6 more

Continue to review full report at Codecov.

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can we update a report.json with offline test in the pr desc?

Oh, It's always run as asynchronous mode, this metric is meaningless.


@link doesn't work with goog.module, unless the type has been goog.require-d

After changing to use goog.module for all classes instead of goog.provide, the @link taglets now only work when the type has been goog.required or defined within a given file.  Previously I was able to refer to types that are not goog.required.
As a workaround I can change the @link taglets to markdown-style references to the generated documentation.  For example instead of
{@link myphysicslab.lab.model.MassObject}

I need to write
[myphysicslab.lab.model.MassObject](myphysicslab.lab.model.MassObject.html).

I noticed this recently too. I know there hasn't been much activity on this project recently - I'm hoping to start working on it again soon. This bug is at the top of my TODO list too.


Create data structure for save data

Hold the actual binary data (serializable), timestamp (as filestamp from NIO.2), other convenient info

This is linked to #6

Moved to https://github.com/AlmasB/FXGL/wiki


SqliteException: SQLite Error 1:'no such table, in asp.net core2.2 mvc

This issue has been moved from a ticket on Developer Community.

I use sqlite in asp.net core 2.2 mvc, But I always get error. Even I use
private IHostingEnvironment _appHost;
public Startup(IHostEnvironment appHost){
_appHost=appHost;
}
and in ConfigurationServices,
options. UseSqlites(
$"DataSource={_appHost.ContentRootPath}/app.db"));
But the resuts don't have any change.
Does anyone have better solution?

Original Comments
Visual Studio Feedback System on 7/31/2019, 02:22 AM:
We have directed your feedback to the appropriate engineering team for further evaluation. The team will review the feedback and notify you about the next steps.
Visual Studio Feedback System on 8/2/2019, 00:18 AM:
Thank you for sharing your feedback! Our teams prioritize action on product issues with broad customer impact. See details at: https://docs.microsoft.com/en-us/visualstudio/ide/report-a-problem?view=vs-2017#faq. In case you need answers to common questions or need assisted support, be sure to use https://visualstudio.microsoft.com/vs/support/. We’ll keep you posted on any updates to this feedback.

Original Solutions
(no solutions)

How are you creating your database schema?

EF Team Triage: Closing this issue as the requested additional details have not been provided and we have been unable to reproduce it.
BTW this is a canned response and may have info or details that do not directly apply to this particular issue. While we'd like to spend the time to uniquely address every incoming issue, we get a lot traffic on the EF projects and that is not practical. To ensure we maximize the time we have to work on fixing bugs, implementing new features, etc. we use canned responses for common triage decisions.


unreleased-commits - Avoid wrapping

Test URLs
https://github.com/coronasafe/care_fe
Screenshot

fixes #7268

Yeah exactly, this issue is because there's no space on that line, so either something wraps or we need to hide something earlier than GitHub does.
Similar bug in the past with the feature that preceded unreleased-commits

https://github.com/refined-github/refined-github/issues/5071


pubspect error when folder name is number

> mkdir 2
> cd 2
> stagehand console-full

pubspec.yalm file result content:
name: 2 << ERROR : Error on line 1, column 7 of pubspec.yaml: "name" field must be a string.
description: A sample command-line application.
# version: 1.0.0
# homepage: https://www.example.com
# author: Your Name<EMAIL_ADDRESS>
environment:
  sdk: '>=2.1.0 <3.0.0'

Well, 2 is not a valid package name. So in that respect, this is "works as intended".
Valid follow-up, though:

should stagehand support overriding the pkg name via command line flag?
should the error here be better? (guessing we're hitting pubspec_parse issue or related)

I've run into problems like this many times before, where either the directory name wasn't a valid identifier or was the same as (or resolved to be the same as) the name of a package it depended on. E.g., if the directory name is angular-components, you can successfully create all the files, but pub get fails ("A package may not list itself as a dependency").
I think that stagehand could make the developer experience better by making sure that the package name is a valid identifier that isn't listed as a dependency.
If there's an issue, it could either suggest changing the directory name or allow the user to override the package name.