Failed
gpkit.tests.from_paths.TestFiles.test_gpkitmodels_SP_SimPleAC_SimPleAC_multimission_py_mosek_cli (from gpkit.tests.from_paths.TestFiles-20210802120742)
Failing for the past 1 build
(Since Failed
)
Error Message
Solver failed for an unknown reason. Relaxing constraints/constants, bounding variables, or using a different solver might fix it. Running `.debug()` or increasing verbosity may pinpoint the trouble.
Stacktrace
Traceback (most recent call last): File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/solvers/mosek_cli.py", line 86, in optimize for logline in check_output(["mskexpopt", filename, "-sol", File "/usr/local/Cellar/python@3.9/3.9.6/Frameworks/Python.framework/Versions/3.9/lib/python3.9/subprocess.py", line 424, in check_output return run(*popenargs, stdout=PIPE, timeout=timeout, check=True, File "/usr/local/Cellar/python@3.9/3.9.6/Frameworks/Python.framework/Versions/3.9/lib/python3.9/subprocess.py", line 528, in run raise CalledProcessError(retcode, process.args, subprocess.CalledProcessError: Command '['mskexpopt', '/var/folders/qk/9zkf0syn149fvhw9mh7hgd5w0000gp/T/tmp7_pn8sv6/gpkit_mosek', '-sol', '/var/folders/qk/9zkf0syn149fvhw9mh7hgd5w0000gp/T/tmp7_pn8sv6/gpkit_mosek.sol']' returned non-zero exit status 26. The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/gp.py", line 211, in solve solver_out = solverfn(c=self.cs, A=self.A, meq_idxs=self.meq_idxs, File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/solvers/mosek_cli.py", line 95, in optimize raise UnknownInfeasible() from e gpkit.exceptions.UnknownInfeasible The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/tests/helpers.py", line 55, in test testfn(name, import_dict, path)(self) File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/tests/from_paths.py", line 48, in <lambda> lambda self: getattr(self, name)())) # pylint:disable=undefined-variable File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/tests/from_paths.py", line 37, in test_fn mod.test() File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gplibrary/gpkitmodels/SP/SimPleAC/SimPleAC_multimission.py", line 68, in test sol = m.localsolve(verbosity=0) File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/prog_factories.py", line 133, in solvefn result = progsolve(solver, verbosity=verbosity, **kwargs) File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/sgp.py", line 159, in localsolve solver_out = gp.solve(solver, verbosity=verbosity-1, File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/gp.py", line 250, in solve raise infeasibility.__class__(msg) from infeasibility gpkit.exceptions.UnknownInfeasible: Solver failed for an unknown reason. Relaxing constraints/constants, bounding variables, or using a different solver might fix it. Running `.debug()` or increasing verbosity may pinpoint the trouble.
Standard Output
Starting a sequence of GP solves for 4 free variables in 1 locally-GP constraints and for 21 free variables in 22 posynomial inequalities. GP Solve 1 Using solver 'mosek_cli' for 21 free variables in 22 posynomial inequalities. Solving took 0.0327 seconds. Solved cost was 5717. GP Solve 2 Using solver 'mosek_cli' for 21 free variables in 22 posynomial inequalities. Solving took 0.0278 seconds. Solved cost was 4538. GP Solve 3 Using solver 'mosek_cli' for 21 free variables in 22 posynomial inequalities. Solving took 0.0275 seconds. Solved cost was 4536. GP Solve 4 Using solver 'mosek_cli' for 21 free variables in 22 posynomial inequalities. Solving took 0.0309 seconds. Solved cost was 4536. Solving took 0.125 seconds and 4 GP solves. Starting a sequence of GP solves for 4 free variables in 1 locally-GP constraints and for 21 free variables in 22 posynomial inequalities. GP Solve 1 Using solver 'mosek_conif' for 21 free variables in 22 posynomial inequalities. Solving took 0.0132 seconds. Solved cost was 5717. GP Solve 2 Using solver 'mosek_conif' for 21 free variables in 22 posynomial inequalities. Solving took 0.0112 seconds. Solved cost was 4538. GP Solve 3 Using solver 'mosek_conif' for 21 free variables in 22 posynomial inequalities. Solving took 0.0112 seconds. Solved cost was 4536. GP Solve 4 Using solver 'mosek_conif' for 21 free variables in 22 posynomial inequalities. Solving took 0.0111 seconds. Solved cost was 4536. Solving took 0.0498 seconds and 4 GP solves.
Standard Error
/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/sgp.py:174: UserWarning: SGP not convergent: Cost rose by 6.1% (1588.61 to 1685.18) on GP solve 2. Details can be found in `m.program.results` or by solving at a higher verbosity. Note convergence is not guaranteed for models with SignomialEqualities. pywarnings.warn( /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/sgp.py:174: UserWarning: SGP not convergent: Cost rose by 6.1% (1588.61 to 1685.18) on GP solve 2. Details can be found in `m.program.results` or by solving at a higher verbosity. Note convergence is not guaranteed for models with SignomialEqualities. pywarnings.warn( /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/sgp.py:174: UserWarning: SGP not convergent: Cost rose by 25% (3053.31 to 3816.14) on GP solve 2. Details can be found in `m.program.results` or by solving at a higher verbosity. Note convergence is not guaranteed for models with SignomialEqualities. pywarnings.warn( /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/sgp.py:174: UserWarning: SGP not convergent: Cost rose by 0.32% (3808.98 to 3821.21) on GP solve 4. Details can be found in `m.program.results` or by solving at a higher verbosity. Note convergence is not guaranteed for models with SignomialEqualities. pywarnings.warn(