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Update a few libraries #1971
Update a few libraries #1971
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Job Mingw Test on 2a3658a : invalidated by @joshua-cogliati-inl failed in fetch |
Hm, some of the regolds look like notable changes to me. Does anyone know how "analytic" or not those gold files were? |
The clustering/datamining ones probably are not very analytic. |
Tests affected:
|
Comments on differences: The tests/framework/PostProcessors/DataMiningPostProcessor/DimensionalityReduction/SpectralEmbedding is mostly due to a few points being fairly different.
versus:
The tests/framework/PostProcessors/LimitSurface/testLimitSurfaceIntegralPPWithBoundingError differences are solely due to the EventProbability_err being different. I am wondering if this is being calculated by subtracting two numbers that very close. The tests/framework/PostProcessors/TemporalDataMiningPostProcessor/Clustering/MiniBatchKMeans look quantitatively similar: @wangcj05 or @PaulTalbot-INL any more questions? |
I think def collectOutput(self, finishedJob, output):
"""
Function to place all of the computed data into the output object
@ In, finishedJob, JobHandler External or Internal instance, A JobHandler object that is in charge of running this post-processor
@ In, output, dataObjects, The object where we want to place our computed results
@ Out, None
"""
evaluation = finishedJob.getEvaluation()
pb, boundError = evaluation[1]
lms = evaluation[0][0]
if output.type == 'PointSet':
# we store back the limitsurface
dataSet = lms.asDataset()
loadDict = {key: dataSet[key].values for key in lms.getVars()}
loadDict[self.computationPrefix] = np.full(len(lms), pb)
if self.computeErrrorBounds:
if self.computationPrefix+"_err" not in output.getVars():
self.raiseAWarning('ERROR Bounds have been computed but the output DataObject does not request the variable: "', self.computationPrefix+"_err", '"!')
else:
loadDict[self.computationPrefix+"_err"] = np.full(len(lms), boundError)
output.load(loadDict,'dict')
else:
self.raiseAnError(Exception, self.type + ' accepts PointSet only') |
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Changes are good, I just have one question about ray. @joshua-cogliati-inl
@@ -60,7 +60,7 @@ Note all install methods after "main" take | |||
<nomkl os='linux' skip_check='True'/> | |||
<numexpr os='linux'/> | |||
<cmake skip_check='True' optional='True'/> | |||
<ray source="pip" pip_extra="[default]">1.12</ray> | |||
<ray source="pip" pip_extra="[default]">1.13</ray> |
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There is a ray 2.0 release, do you have a chance to take a look? I saw there was some fix for hanging jobs.
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I will make another branch and see what happens if we switch to ray 2.0
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It worked, so I switched this pull request to use ray 2.0
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Hm, ray 2.0 seems to be causing random failures in InternalParallel tests.
Job Test Ubuntu 18 PIP on f28fa11 : invalidated by @joshua-cogliati-inl FAILED: Failed tests/framework/InternalParallelTests/ROMscikit |
Job Test Ubuntu 18-2 Python 3 on f28fa11 : invalidated by @joshua-cogliati-inl FAILED: Failed tests/framework/ensembleModelTests/testEnsembleModelNonLinearParallel |
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Job Test Ubuntu 20-2 Optional on 2a3658a : invalidated by @joshua-cogliati-inl FAILED: Diff tests/framework/PostProcessors/LimitSurface/testLimitSurfacePostProcessor |
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changes are good.
Checklist is good. Test are green. PR can be merged. |
@joshua-cogliati-inl Could you send out an email to user group since there are libraries update, and the users need to update their libraries also. |
Pull Request Description
What issue does this change request address?
#1972
What are the significant changes in functionality due to this change request?
Updates scikit-learn, statsmodels and ray
Removes using some deprecated python features.
For Change Control Board: Change Request Review
The following review must be completed by an authorized member of the Change Control Board.
<internalParallel>
to True.raven/tests/framework/user_guide
andraven/docs/workshop
) have been changed, the associated documentation must be reviewed and assured the text matches the example.