

def gbmClassificationFittingTest(self, nRows, nColumns, depth, nThreads, maxBoosts):
    s3 = InMemoryS3Interface.InMemoryS3InterfaceFactory()
    (result, simulation) = InMemoryCumulusSimulation.computeUsingSeveralWorkers(self.dataGenerationScript(nRows, nColumns), s3, 1, timeout=360, memoryLimitMb=(30 * 1024), threadCount=nColumns, returnSimulation=True, useInMemoryCache=False)
    try:
        self.assertTrue(result.isResult())
        (dfPredictors, dfResponse) = result.asResult.result
        fitter = simulation.compute(self.classificationScript(depth, 1), timeout=360, dfResponse=dfResponse, dfPredictors=dfPredictors).asResult.result
        t0 = time.time()
        for nBoosts in range(1, maxBoosts):
            testName = self.getTestName(nRows, nColumns, depth, nBoosts, nThreads)
            predictions = simulation.compute('fitter.pseudoResidualsAndRegressionValues()', timeout=360, fitter=fitter)
            logging.info(('predictions = %s' % predictions))
            logging.info(('predictions.asResult.result = %s' % predictions.asResult.result))
            predictions = predictions.asResult.result
            totalTimeToReturnResult = (time.time() - t0)
            PerformanceTestReporter.recordTest((testName + '_predict'), totalTimeToReturnResult, None)
            fitter = simulation.compute('fitter.nextGivenPseudoResidualsAndRegressionValues(predictions)', timeout=360, fitter=fitter, predictions=predictions)
            logging.info(('fitter = %s' % fitter))
            logging.info(('fitter.asResult.result = %s' % fitter.asResult.result))
            fitter = fitter.asResult.result
            totalTimeToReturnResult = (time.time() - t0)
            PerformanceTestReporter.recordTest(testName, totalTimeToReturnResult, None)
    finally:
        simulation.teardown()

dataset/ETHPy150Open ufora/ufora/test_scripts/bigbox_perf/gradientBoostingClassification/testGbmClassification.py GbmClassificationPerformanceTest.gbmClassificationFittingTest/VarMisuse@65/103 `nThreads`->`nColumns`