diff --git a/dependencies.xml b/dependencies.xml index 7eb6335591..48f0088585 100644 --- a/dependencies.xml +++ b/dependencies.xml @@ -40,7 +40,7 @@ Note all install methods after "main" take 3.2 1.6 - 1.15 + 2.0 3 diff --git a/developer_tools/XSDSchemas/raven.xsd b/developer_tools/XSDSchemas/raven.xsd index 36f0f7e6ee..cefcccb7fa 100644 --- a/developer_tools/XSDSchemas/raven.xsd +++ b/developer_tools/XSDSchemas/raven.xsd @@ -95,6 +95,7 @@ + diff --git a/doc/user_guide/ravenRomTrainer.tex b/doc/user_guide/ravenRomTrainer.tex index 997ef81fe0..1663ceb3f5 100644 --- a/doc/user_guide/ravenRomTrainer.tex +++ b/doc/user_guide/ravenRomTrainer.tex @@ -178,8 +178,7 @@ \subsubsection{How to load and sample a ROM?} \textbf{Files} object to track the pickled ROM file. \xmlExample{framework/user_guide/ravenTutorial/RomLoad.xml}{Files} -In this example, the subtype \xmlString{NDinvDistWeight} of \xmlNode{ROM} is used instead of \xmlString{pickledROM}, -since the subtype of ROM is already known. +In this example, the subtype \xmlString{pickledROM} of \xmlNode{ROM} is used since the hyper-parameters of the ROM can not be changed once the ROM is loaded from a pickled (serialized) file. \xmlExample{framework/user_guide/ravenTutorial/RomLoad.xml}{Models} Two data objects are defined: 1) a \textbf{HistorySet} named ``inputPlaceHolder'' used as a placeholder input for diff --git a/doc/user_manual/runInfo.tex b/doc/user_manual/runInfo.tex index 091fdb2e14..f5cccd8bb5 100644 --- a/doc/user_manual/runInfo.tex +++ b/doc/user_manual/runInfo.tex @@ -59,6 +59,19 @@ \subsection{RunInfo: Input of Calculation Flow} % \default{mpiexec} + %%%%%% N THREADS +\item \xmlNode{threadParameter}, \xmlDesc{string, optional field}, specifies the command used to set the + number of threads. The ``%NUM_CPUS%'' is a wildcard that will be replaced by the number of threads + specified in the node \xmlNode{NumThreads}. In this way for commands + that require the number of threads to be inputted without a blank space after this command, + the user can specify the command attaching the wildcard above to the string reporting the command. + For example, $--my-nthreads=%NUM_CPUS%$ (e.g. $--my-nthreads=10$). In other cases, the command can be + inputted explicetely adding the blank space. For example, $-omp %NUM_CPUS%$ (e.g. $-omp 10$). + If the wild card is not present, a blank space is always added after the command + (e.g. $--mycommand => --mycommand 10$). + % + \default{--n-threads=\%NUM\_CPUS\%} + %%%%%% BATCH SIZE \item \xmlNode{batchSize}, \xmlDesc{integer, optional field}, specifies the number of parallel runs executed simultaneously (e.g., @@ -125,7 +138,8 @@ \subsection{RunInfo: Input of Calculation Flow} For example, if RAVEN is driving a code named ``FOO,'' and this code has multi-threading support, this block is used to specify how many threads each instance of FOO should use (e.g. ``\texttt{FOO --n-threads=N}'' where \texttt{N} - is the number of threads). + is the number of threads). The command to specify the number of threads can be +customized via the node \xmlNode{threadParameter}. % \default{1 (or None when the driven code does not have multi-threading support)} diff --git a/framework/CustomModes/MPILegacySimulationMode.py b/framework/CustomModes/MPILegacySimulationMode.py index 94f698bd14..c10d14a1df 100644 --- a/framework/CustomModes/MPILegacySimulationMode.py +++ b/framework/CustomModes/MPILegacySimulationMode.py @@ -201,7 +201,8 @@ def modifyInfo(self, runInfoDict): newRunInfo['precommand'] = runInfoDict["MPIExec"]+" "+nodeCommand+" -n "+str(numMPI)+" "+runInfoDict['precommand'] if(runInfoDict['NumThreads'] > 1): #add number of threads to the post command. - newRunInfo['postcommand'] = " --n-threads=%NUM_CPUS% "+runInfoDict['postcommand'] + newRunInfo['threadParameter'] = runInfoDict['threadParameter'] + newRunInfo['postcommand'] =" {} {}".format(newRunInfo['threadParameter'],runInfoDict['postcommand']) self.raiseAMessage("precommand: "+newRunInfo['precommand']+", postcommand: "+newRunInfo.get('postcommand',runInfoDict['postcommand'])) return newRunInfo diff --git a/framework/CustomModes/MPISimulationMode.py b/framework/CustomModes/MPISimulationMode.py index 2d0292ab1c..7457f5eec9 100644 --- a/framework/CustomModes/MPISimulationMode.py +++ b/framework/CustomModes/MPISimulationMode.py @@ -109,9 +109,9 @@ def modifyInfo(self, runInfoDict): # Note, with defaults the precommand is "mpiexec -f nodeFile -n numMPI" newRunInfo['precommand'] = runInfoDict["MPIExec"]+" "+nodeCommand+" -n "+str(numMPI)+" "+runInfoDict['precommand'] if runInfoDict['NumThreads'] > 1: + newRunInfo['threadParameter'] = runInfoDict['threadParameter'] #add number of threads to the post command. - newRunInfo['postcommand'] = " --n-threads=%NUM_CPUS% "+runInfoDict['postcommand'] - + newRunInfo['postcommand'] =" {} {}".format(newRunInfo['threadParameter'],runInfoDict['postcommand']) self.raiseAMessage("precommand: "+newRunInfo['precommand']+", postcommand: "+newRunInfo.get('postcommand',runInfoDict['postcommand'])) return newRunInfo diff --git a/framework/Optimizers/parentSelectors/parentSelectors.py b/framework/Optimizers/parentSelectors/parentSelectors.py index 5f13de81fe..0be3ca8396 100644 --- a/framework/Optimizers/parentSelectors/parentSelectors.py +++ b/framework/Optimizers/parentSelectors/parentSelectors.py @@ -91,29 +91,55 @@ def tournamentSelection(population,**kwargs): fitness = kwargs['fitness'] nParents= kwargs['nParents'] pop = population - popSize = population.values.shape[0] + if 'rank' in kwargs: + # the key rank is used in multi-objective optimization where rank identifies which front the point belongs to + rank = kwargs['rank'] + multiObjectiveRanking = True + matrixOperationRaw = np.zeros((popSize,3)) + matrixOperationRaw[:,0] = np.transpose(np.arange(popSize)) + matrixOperationRaw[:,1] = np.transpose(fitness.data) + matrixOperationRaw[:,2] = np.transpose(rank.data) + matrixOperation = np.zeros((popSize,3)) + else: + multiObjectiveRanking = False + matrixOperationRaw = np.zeros((popSize,2)) + matrixOperationRaw[:,0] = np.transpose(np.arange(popSize)) + matrixOperationRaw[:,1] = np.transpose(fitness.data) + matrixOperation = np.zeros((popSize,2)) + + indexes = list(np.arange(popSize)) + indexesShuffled = randomUtils.randomChoice(indexes, size = popSize, replace = False, engine = None) + + for idx, val in enumerate(indexesShuffled): + matrixOperation[idx,:] = matrixOperationRaw[val,:] + selectedParent = xr.DataArray( - np.zeros((nParents,np.shape(pop)[1])), - dims=['chromosome','Gene'], - coords={'chromosome':np.arange(nParents), - 'Gene': kwargs['variables']}) - - if nParents >= popSize/2.0: - # generate combination of 2 with replacement - selectionList = np.atleast_2d(randomUtils.randomChoice(list(range(0,popSize)), 2*nParents, replace=False)) - else: # nParents < popSize/2.0 - # generate combination of 2 without replacement - selectionList = np.atleast_2d(randomUtils.randomChoice(list(range(0,popSize)), 2*nParents)) - - selectionList = selectionList.reshape(nParents,2) - - for index,pair in enumerate(selectionList): - if fitness[pair[0]]>fitness[pair[1]]: - selectedParent[index,:] = pop.values[pair[0],:] - else: # fitness[pair[1]]>fitness[pair[0]]: - selectedParent[index,:] = pop.values[pair[1],:] + np.zeros((nParents,np.shape(pop)[1])), + dims=['chromosome','Gene'], + coords={'chromosome':np.arange(nParents), + 'Gene': kwargs['variables']}) + + if not multiObjectiveRanking: # single-objective implementation of tournamentSelection + for i in range(nParents): + if matrixOperation[2*i,1] > matrixOperation[2*i+1,1]: + index = int(matrixOperation[i,0]) + else: + index = int(matrixOperation[i+1,0]) + selectedParent[i,:] = pop.values[index,:] + else: # multi-objective implementation of tournamentSelection + for i in range(nParents-1): + if matrixOperation[2*i,2] > matrixOperation[2*i+1,2]: + index = int(matrixOperation[i,0]) + elif matrixOperation[2*i,2] < matrixOperation[2*i+1,2]: + index = int(matrixOperation[i+1,0]) + else: # same rank case + if matrixOperation[2*i,1] > matrixOperation[2*i+1,1]: + index = int(matrixOperation[i,0]) + else: + index = int(matrixOperation[i+1,0]) + selectedParent[i,:] = pop.values[index,:] return selectedParent diff --git a/framework/Simulation.py b/framework/Simulation.py index d7a059f8f3..0035653fd7 100644 --- a/framework/Simulation.py +++ b/framework/Simulation.py @@ -215,34 +215,41 @@ def __init__(self, frameworkDir, verbosity='all', interactive=Interaction.No): sys.path.append(os.getcwd()) #this dictionary contains the general info to run the simulation self.runInfoDict = {} - self.runInfoDict['DefaultInputFile' ] = 'test.xml' #Default input file to use - self.runInfoDict['SimulationFiles' ] = [] #the xml input file + self.runInfoDict['DefaultInputFile' ] = 'test.xml' #Default input file to use + self.runInfoDict['SimulationFiles' ] = [] #the xml input file self.runInfoDict['ScriptDir' ] = os.path.join(os.path.dirname(frameworkDir),"scripts") # the location of the pbs script interfaces - self.runInfoDict['FrameworkDir' ] = frameworkDir # the directory where the framework is located + self.runInfoDict['FrameworkDir' ] = frameworkDir # the directory where the framework is located self.runInfoDict['RemoteRunCommand' ] = os.path.join(frameworkDir,'raven_qsub_command.sh') - self.runInfoDict['NodeParameter' ] = '-f' # the parameter used to specify the files where the nodes are listed - self.runInfoDict['MPIExec' ] = 'mpiexec' # the command used to run mpi commands - self.runInfoDict['WorkingDir' ] = '' # the directory where the framework should be running - self.runInfoDict['TempWorkingDir' ] = '' # the temporary directory where a simulation step is run - self.runInfoDict['NumMPI' ] = 1 # the number of mpi process by run - self.runInfoDict['NumThreads' ] = 1 # Number of Threads by run - self.runInfoDict['numProcByRun' ] = 1 # Total number of core used by one run (number of threads by number of mpi) - self.runInfoDict['batchSize' ] = 1 # number of contemporaneous runs - self.runInfoDict['internalParallel' ] = False # activate internal parallel (parallel python). If True parallel python is used, otherwise multi-threading is used - self.runInfoDict['ParallelCommand' ] = '' # the command that should be used to submit jobs in parallel (mpi) - self.runInfoDict['ThreadingCommand' ] = '' # the command should be used to submit multi-threaded - self.runInfoDict['totalNumCoresUsed' ] = 1 # total number of cores used by driver - self.runInfoDict['queueingSoftware' ] = '' # queueing software name - self.runInfoDict['stepName' ] = '' # the name of the step currently running - self.runInfoDict['precommand' ] = '' # Add to the front of the command that is run - self.runInfoDict['postcommand' ] = '' # Added after the command that is run. - self.runInfoDict['delSucLogFiles' ] = False # If a simulation (code run) has not failed, delete the relative log file (if True) - self.runInfoDict['deleteOutExtension'] = [] # If a simulation (code run) has not failed, delete the relative output files with the listed extension (comma separated list, for example: 'e,r,txt') - self.runInfoDict['mode' ] = '' # Running mode. Curently the only mode supported is mpi but others can be added with custom modes. - self.runInfoDict['Nodes' ] = [] # List of node IDs. Filled only in case RAVEN is run in a DMP machine - self.runInfoDict['expectedTime' ] = '10:00:00' # How long the complete input is expected to run. + self.runInfoDict['NodeParameter' ] = '-f' # the parameter used to specify the files where the nodes are listed + self.runInfoDict['MPIExec' ] = 'mpiexec' # the command used to run mpi commands + self.runInfoDict['threadParameter'] = '--n-threads=%NUM_CPUS%'# the command used to run multi-threading commands. + # The "%NUM_CPUS%" is a wildcard to replace. In this way for commands + # that require the num of threads to be inputted without a + # blank space we can have something like --my-nthreads=%NUM_CPUS% + # (e.g. --my-nthreads=10), otherwise we can have something like + # -omp %NUM_CPUS% (e.g. -omp 10). If not present, a blank + # space is always added (e.g. --mycommand => --mycommand 10) + self.runInfoDict['WorkingDir' ] = '' # the directory where the framework should be running + self.runInfoDict['TempWorkingDir' ] = '' # the temporary directory where a simulation step is run + self.runInfoDict['NumMPI' ] = 1 # the number of mpi process by run + self.runInfoDict['NumThreads' ] = 1 # Number of Threads by run + self.runInfoDict['numProcByRun' ] = 1 # Total number of core used by one run (number of threads by number of mpi) + self.runInfoDict['batchSize' ] = 1 # number of contemporaneous runs + self.runInfoDict['internalParallel' ] = False # activate internal parallel (parallel python). If True parallel python is used, otherwise multi-threading is used + self.runInfoDict['ParallelCommand' ] = '' # the command that should be used to submit jobs in parallel (mpi) + self.runInfoDict['ThreadingCommand' ] = '' # the command should be used to submit multi-threaded + self.runInfoDict['totalNumCoresUsed' ] = 1 # total number of cores used by driver + self.runInfoDict['queueingSoftware' ] = '' # queueing software name + self.runInfoDict['stepName' ] = '' # the name of the step currently running + self.runInfoDict['precommand' ] = '' # Add to the front of the command that is run + self.runInfoDict['postcommand' ] = '' # Added after the command that is run. + self.runInfoDict['delSucLogFiles' ] = False # If a simulation (code run) has not failed, delete the relative log file (if True) + self.runInfoDict['deleteOutExtension'] = [] # If a simulation (code run) has not failed, delete the relative output files with the listed extension (comma separated list, for example: 'e,r,txt') + self.runInfoDict['mode' ] = '' # Running mode. Curently the only mode supported is mpi but others can be added with custom modes. + self.runInfoDict['Nodes' ] = [] # List of node IDs. Filled only in case RAVEN is run in a DMP machine + self.runInfoDict['expectedTime' ] = '10:00:00' # How long the complete input is expected to run. self.runInfoDict['logfileBuffer' ] = int(io.DEFAULT_BUFFER_SIZE)*50 # logfile buffer size in bytes - self.runInfoDict['clusterParameters' ] = [] # Extra parameters to use with the qsub command. + self.runInfoDict['clusterParameters' ] = [] # Extra parameters to use with the qsub command. self.runInfoDict['maxQueueSize' ] = None #Following a set of dictionaries that, in a manner consistent with their names, collect the instance of all objects needed in the simulation @@ -586,6 +593,8 @@ def __readRunInfo(self,xmlNode,runInfoSkip,xmlFilename): self.runInfoDict['NodeParameter'] = element.text.strip() elif element.tag == 'MPIExec': self.runInfoDict['MPIExec'] = element.text.strip() + elif element.tag == 'threadParameter': + self.runInfoDict['threadParameter'] = element.text.strip() elif element.tag == 'JobName': self.runInfoDict['JobName' ] = element.text.strip() elif element.tag == 'ParallelCommand': diff --git a/framework/SupervisedLearning/KerasBase.py b/framework/SupervisedLearning/KerasBase.py index 48b63277b2..0cbee14c90 100644 --- a/framework/SupervisedLearning/KerasBase.py +++ b/framework/SupervisedLearning/KerasBase.py @@ -227,13 +227,7 @@ def readInitDict(self, initDict): self._ROM = None # the training/testing history of ROM self._romHistory = None - self._sessionConf = None randomSeed = self.initOptionDict.pop('random_seed',None) - # Force TensorFlow to use single thread when reproducible results are requested - # Multiple threads are a potential source of non-reproducible results. - # For further details, see: https://stackoverflow.com/questions/42022950/ - self._sessionConf = tf.ConfigProto(intra_op_parallelism_threads=self.numThreads, - inter_op_parallelism_threads=self.numThreads) # Set the seed for random number generation to obtain reproducible results # https://keras.io/getting-started/faq/#how-can-i-obtain-reproducible-results-using-keras-during-development if randomSeed is not None: @@ -243,18 +237,11 @@ def readInitDict(self, initDict): # The below is necessary for starting core Python generated random numbers # in a well-defined state. rn.seed(randomSeed) - # The below tf.set_random_seed() will make random number generation + # The below tf.random.set_seed() will make random number generation # in the TensorFlow backend have a well-defined initial state. # For further details, see: - # https://www.tensorflow.org/api_docs/python/tf/set_random_seed - tf.set_random_seed(randomSeed) - self._session = tf.Session(graph=tf.get_default_graph(), config=self._sessionConf) - # Base on issue https://github.com/tensorflow/tensorflow/issues/28287 - # The problem is that tensorflow graphs and sessions are not thread safe. So by default - # a new session (which) does not contain any previously loaded weights, models, and so on) - # is created for each thread, i.e. for each request. By saving the session that contains all - # the models and setting it to be used by keras in each thread. - tf.keras.backend.set_session(self._session) + # https://www.tensorflow.org/api_docs/python/tf/random/set_seed + tf.random.set_seed(randomSeed) modelName = self.initOptionDict.pop('name','') # number of classes for classifier @@ -300,9 +287,7 @@ def _initGraph(self): @ In, None @ Out, None """ - # This is needed to solve the thread issue in self._ROM.predict() - # https://github.com/fchollet/keras/issues/2397#issuecomment-306687500 - self.graph = tf.get_default_graph() + pass def __getstate__(self): """ @@ -311,7 +296,7 @@ def __getstate__(self): @ Out, state, dict, it contains all the information needed by the ROM to be initialized """ state = supervisedLearning.__getstate__(self) - tf.keras.models.save_model(self._ROM, KerasBase.tempModelFile) + tf.keras.models.save_model(self._ROM, KerasBase.tempModelFile, save_format='h5') # another method to save the TensorFlow model # self._ROM.save(KerasBase.tempModelFile) with open(KerasBase.tempModelFile, "rb") as f: @@ -331,7 +316,6 @@ def __setstate__(self, d): with open(KerasBase.tempModelFile, "wb") as f: f.write(d[KerasBase.modelAttr]) del d[KerasBase.modelAttr] - tf.keras.backend.set_session(self._session) self._ROM = tf.keras.models.load_model(KerasBase.tempModelFile) os.remove(KerasBase.tempModelFile) self.__dict__.update(d) @@ -348,8 +332,8 @@ def writeXML(self, writeTo, targets=None, skip=None): if not self.amITrained: self.raiseAnError(RuntimeError, 'ROM is not yet trained! Cannot write to DataObject.') root = writeTo.getRoot() - writeTo.addScalar('Accuracy',"Training",' '.join([str(elm) for elm in self._romHistory.history['acc']])) - writeTo.addScalar('Accuracy',"Testing",' '.join([str(elm) for elm in self._romHistory.history['val_acc']])) + writeTo.addScalar('Accuracy',"Training",' '.join([str(elm) for elm in self._romHistory.history['accuracy']])) + writeTo.addScalar('Accuracy',"Testing",' '.join([str(elm) for elm in self._romHistory.history['val_accuracy']])) writeTo.addScalar('Loss',"Training",' '.join([str(elm) for elm in self._romHistory.history['loss']])) writeTo.addScalar('Loss',"Testing",' '.join([str(elm) for elm in self._romHistory.history['val_loss']])) @@ -465,7 +449,6 @@ def __trainLocal__(self,featureVals,targetVals): #output layer self._addOutputLayers() self._ROM.compile(loss=self.lossFunction, optimizer=self.optimizer, metrics=self.metrics) - self._ROM._make_predict_function() # have to initialize before threading self._romHistory = self._ROM.fit(featureVals, targetVals, epochs=self.epochs, batch_size=self.batchSize, validation_split=self.validationSplit) # The following requires pydot-ng and graphviz to be installed (See the manual) # https://github.com/keras-team/keras/issues/3210 @@ -490,9 +473,7 @@ def __evaluateLocal__(self,featureVals): """ featureVals = self._preprocessInputs(featureVals) prediction = {} - with self.graph.as_default(): - tf.keras.backend.set_session(self._session) - outcome = self._ROM.predict(featureVals) + outcome = self._ROM.predict(featureVals) if self.numClasses > 1 and self.lossFunction in ['categorical_crossentropy']: outcome = np.argmax(outcome,axis=1) # Transform labels back to original encoding diff --git a/framework/SupervisedLearning/KerasClassifier.py b/framework/SupervisedLearning/KerasClassifier.py index 1b344710be..f17992c5bc 100644 --- a/framework/SupervisedLearning/KerasClassifier.py +++ b/framework/SupervisedLearning/KerasClassifier.py @@ -139,9 +139,7 @@ def __evaluateLocal__(self,featureVals): """ featureVals = self._preprocessInputs(featureVals) prediction = {} - with self.graph.as_default(): - tf.keras.backend.set_session(self._session) - outcome = self._ROM.predict(featureVals) + outcome = self._ROM.predict(featureVals) if self.numClasses > 1 and self.lossFunction in ['categorical_crossentropy']: outcome = np.argmax(outcome,axis=1) # Transform labels back to original encoding diff --git a/framework/SupervisedLearning/KerasRegression.py b/framework/SupervisedLearning/KerasRegression.py index 8f7d4dba28..ddc062b938 100644 --- a/framework/SupervisedLearning/KerasRegression.py +++ b/framework/SupervisedLearning/KerasRegression.py @@ -168,9 +168,7 @@ def __evaluateLocal__(self,featureVals): """ featureVals = self._preprocessInputs(featureVals) prediction = {} - with self.graph.as_default(): - tf.keras.backend.set_session(self._session) - outcome = self._ROM.predict(featureVals) + outcome = self._ROM.predict(featureVals) for i, target in enumerate(self.target): prediction[target] = self._invertScaleToNormal(outcome[0, :, i], target) return prediction diff --git a/scripts/establish_conda_env.sh b/scripts/establish_conda_env.sh index 49bdec2bb8..44eefa0188 100755 --- a/scripts/establish_conda_env.sh +++ b/scripts/establish_conda_env.sh @@ -74,6 +74,25 @@ function find_conda_defs () CONDA_DEFS="${CONDA_DEFS//\\//}" } +function guess_conda_defs () +{ + if [ -z ${CONDA_DEFS} ]; + then + CONDA_DEFS=$(which conda | tail -1) + if [[ "$CONDA_DEFS" != "" ]]; then + # we found it + LOCATION_CONDASH="etc/profile.d/conda.sh" + if [[ "$CONDA_PATH" == *"condabin"* ]]; then + CONDA_DEFS=`echo "${CONDA_DEFS/condabin\/conda/$LOCATION_CONDASH}"` + else + CONDA_DEFS=`echo "${CONDA_DEFS/bin\/conda/$LOCATION_CONDASH}"` + fi + # fix Windows backslashes to be forward, compatible with all *nix including mingw + CONDA_DEFS="${CONDA_DEFS//\\//}" + fi + fi +} + function install_libraries() { if [[ $ECE_VERBOSE == 0 ]]; then echo Installing libraries ...; fi @@ -368,9 +387,17 @@ if [[ "$INSTALL_MANAGER" == "CONDA" ]]; # conda info || echo conda info failed #fi else - echo ... Conda definitions not found at \"${CONDA_DEFS}\"! - echo ... \>\> Specify the location of miniconda3/etc/profile.d/conda.sh through the --conda-defs option. - exit 1 + # try to guess + guess_conda_defs + if test -e ${CONDA_DEFS}; + then + if [[ $ECE_VERBOSE == 0 ]]; then echo ... Found conda definitions at ${CONDA_DEFS}; fi + source ${CONDA_DEFS} + else + echo ... Conda definitions not found at \"${CONDA_DEFS}\"! + echo ... \>\> Specify the location of miniconda3/etc/profile.d/conda.sh through the --conda-defs option. + exit 1 + fi fi else # check if pip exists diff --git a/tests/cluster_tests/test_mpiqsub_nosplit.xml b/tests/cluster_tests/test_mpiqsub_nosplit.xml index 83255e8294..8cf8bf04ac 100644 --- a/tests/cluster_tests/test_mpiqsub_nosplit.xml +++ b/tests/cluster_tests/test_mpiqsub_nosplit.xml @@ -16,6 +16,7 @@ 3 -W block=true 1 + --n-threads=%NUM_CPUS% mpilegacy diff --git a/tests/framework/Optimizers/GeneticAlgorithms/GA_knapsackBaseTournament.xml b/tests/framework/Optimizers/GeneticAlgorithms/GA_knapsackBaseTournament.xml new file mode 100644 index 0000000000..92886da352 --- /dev/null +++ b/tests/framework/Optimizers/GeneticAlgorithms/GA_knapsackBaseTournament.xml @@ -0,0 +1,155 @@ + + + + framework/Optimizers/GeneticAlgorithms/GA_knapsackBaseTournament + mandd + 2021-06-22 + GeneticAlgorithm + + This test is designed to find the optimal solution of a basic knapsack problem using tournament select + + + + + simpleKnapsack + opt, print, printExport + 1 + False + + + + + placeholder + Kbase + GAoptimizer + opt_export + optOut + + + optOut + PrintOptOut_1 + + + opt_export + PrintOptOut_export_1 + + + + + + 0 + 1 + withReplacement + + + + + + + 5 + 42 + final + + + + 14 + + + 0.9 + + + 0.1 + + + + 0.2 + 13.0 + + tournamentSelection + fitnessBased + + + + -1 + + + + unif_dist_wRepl + 0,0,0,0,1,0,0,0,0,1,0,0,0,0 + + + unif_dist_wRepl + 0,0,0,1,0,0,0,0,1,0,0,0,0,1 + + + unif_dist_wRepl + 0,0,1,0,0,0,0,1,0,0,0,0,1,0 + + + unif_dist_wRepl + 0,1,0,0,0,0,1,0,0,0,0,1,0,0 + + + unif_dist_wRepl + 1,0,0,0,0,1,0,0,0,0,1,0,0,0 + + + unif_dist_wRepl + 0,0,0,0,1,0,0,0,0,1,0,0,0,0 + + + unif_dist_wRepl + 0,0,0,1,0,0,0,0,1,0,0,0,0,1 + + + unif_dist_wRepl + 0,0,1,0,0,0,0,1,0,0,0,0,1,0 + + + unif_dist_wRepl + 0,1,0,0,0,0,1,0,0,0,0,1,0,0 + + + unif_dist_wRepl + 1,0,0,0,0,1,0,0,0,0,1,0,0,0 + + + planValue + optOut + + + + + + proj1,proj2,proj3,proj4,proj5,proj6,proj7,proj8,proj9,proj10,planValue,validPlan + + + + + + + proj1,proj2,proj3,proj4,proj5,proj6,proj7,proj8,proj9,proj10 + planValue,validPlan + + + proj1,proj2,proj3,proj4,proj5,proj6,proj7,proj8,proj9,proj10 + planValue,validPlan + + + trajID + proj1,proj2,proj3,proj4,proj5,proj6,proj7,proj8,proj9,proj10,planValue + + + + + + csv + optOut + + + csv + opt_export + + + + diff --git a/tests/framework/Optimizers/GeneticAlgorithms/gold/simpleKnapsack/PrintOptOut_1.csv b/tests/framework/Optimizers/GeneticAlgorithms/gold/simpleKnapsack/PrintOptOut_1.csv new file mode 100644 index 0000000000..8f133488cb --- /dev/null +++ b/tests/framework/Optimizers/GeneticAlgorithms/gold/simpleKnapsack/PrintOptOut_1.csv @@ -0,0 +1,135 @@ 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+0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,4,0.0,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.0009765625,5,0.5,5 +0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,6,0.0,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.0009765625,5,0.5,5 +0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,6,0.0,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.0009765625,5,0.5,5 diff --git a/tests/framework/Optimizers/GeneticAlgorithms/gold/simpleKnapsack/PrintOptOut_export_1.csv b/tests/framework/Optimizers/GeneticAlgorithms/gold/simpleKnapsack/PrintOptOut_export_1.csv new file mode 100644 index 0000000000..46dbd37daf --- /dev/null +++ b/tests/framework/Optimizers/GeneticAlgorithms/gold/simpleKnapsack/PrintOptOut_export_1.csv @@ -0,0 +1,2 @@ +trajID,proj1,proj2,proj3,proj4,proj5,proj6,proj7,proj8,proj9,proj10,planValue +0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,7 diff --git a/tests/framework/Optimizers/GeneticAlgorithms/tests b/tests/framework/Optimizers/GeneticAlgorithms/tests index 4130c18bc6..1aecf33901 100644 --- a/tests/framework/Optimizers/GeneticAlgorithms/tests +++ b/tests/framework/Optimizers/GeneticAlgorithms/tests @@ -132,6 +132,16 @@ rel_err = 0.001 [../] [../] + + [./GA_knapsackBaseTournament] + type = 'RavenFramework' + input = 'GA_knapsackBaseTournament.xml' + [./csv] + type = OrderedCSV + output = 'simpleKnapsack/PrintOptOut_export_1.csv simpleKnapsack/PrintOptOut_1.csv' + rel_err = 0.001 + [../] + [../] [./GA_knapsackBaseUnifXover] type = 'RavenFramework' diff --git a/tests/framework/ROM/tensorflow_keras/gold/LSTMRegression/out_resampled_0.csv b/tests/framework/ROM/tensorflow_keras/gold/LSTMRegression/out_resampled_0.csv index 98a0e61a3a..e36af7c657 100644 --- a/tests/framework/ROM/tensorflow_keras/gold/LSTMRegression/out_resampled_0.csv +++ b/tests/framework/ROM/tensorflow_keras/gold/LSTMRegression/out_resampled_0.csv @@ -1,102 +1,102 @@ index,sum,square,prev_sum,prev_square,prev_square_sum -0,0.278171479702,23.6013278961,0.0,0.0,0.0 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+95,-0.833904743195,25.6101722717,-6.82570998246,46.5903167647,23.5437819089 +96,-0.823221564293,25.3861408234,-6.45572574909,41.6763949475,20.8654288251 +97,-0.788672804832,25.0822181702,-6.03639334556,36.4380446223,18.2597123309 +98,-0.728544354439,24.7063045502,-5.57443824234,31.0743617177,15.8933575617 +99,-0.643340945244,24.2753868103,-5.07718126238,25.7777695711,13.9191909899 +100,-0.536521077156,23.8140258789,-4.55243301702,20.7246463745,12.4673523124 diff --git a/tests/framework/ROM/tensorflow_keras/gold/data/outCon1DClassifier.csv b/tests/framework/ROM/tensorflow_keras/gold/data/outCon1DClassifier.csv index dfd3250b25..9e698c3c24 100644 --- a/tests/framework/ROM/tensorflow_keras/gold/data/outCon1DClassifier.csv +++ b/tests/framework/ROM/tensorflow_keras/gold/data/outCon1DClassifier.csv @@ -7,30 +7,30 @@ time,x,y 0.5625,16.0,17.0 0.675,17.0,17.0 0.7875,18.0,17.0 -0.0,2.0,9.0 -0.1125,3.0,9.0 -0.225,4.0,9.0 -0.3375,5.0,9.0 -0.45,6.0,9.0 -0.5625,7.0,9.0 -0.675,8.0,9.0 -0.7875,9.0,9.0 -0.0,3.0,9.0 -0.1125,4.0,9.0 -0.225,5.0,9.0 -0.3375,6.0,9.0 -0.45,7.0,9.0 -0.5625,8.0,9.0 -0.675,9.0,9.0 -0.7875,10.0,9.0 -0.0,5.0,13.0 -0.1125,6.0,13.0 -0.225,7.0,13.0 -0.3375,8.0,13.0 -0.45,9.0,13.0 -0.5625,10.0,13.0 -0.675,11.0,13.0 -0.7875,12.0,13.0 +0.0,2.0,11.0 +0.1125,3.0,11.0 +0.225,4.0,11.0 +0.3375,5.0,11.0 +0.45,6.0,11.0 +0.5625,7.0,11.0 +0.675,8.0,11.0 +0.7875,9.0,11.0 +0.0,3.0,11.0 +0.1125,4.0,11.0 +0.225,5.0,11.0 +0.3375,6.0,11.0 +0.45,7.0,11.0 +0.5625,8.0,11.0 +0.675,9.0,11.0 +0.7875,10.0,11.0 +0.0,5.0,14.0 +0.1125,6.0,14.0 +0.225,7.0,14.0 +0.3375,8.0,14.0 +0.45,9.0,14.0 +0.5625,10.0,14.0 +0.675,11.0,14.0 +0.7875,12.0,14.0 0.0,7.0,15.0 0.1125,8.0,15.0 0.225,9.0,15.0 @@ -55,22 +55,22 @@ time,x,y 0.5625,18.0,17.0 0.675,19.0,17.0 0.7875,20.0,17.0 -0.0,5.0,13.0 -0.1125,6.0,13.0 -0.225,7.0,13.0 -0.3375,8.0,13.0 -0.45,9.0,13.0 -0.5625,10.0,13.0 -0.675,11.0,13.0 -0.7875,12.0,13.0 -0.0,5.0,13.0 -0.1125,6.0,13.0 -0.225,7.0,13.0 -0.3375,8.0,13.0 -0.45,9.0,13.0 -0.5625,10.0,13.0 -0.675,11.0,13.0 -0.7875,12.0,13.0 +0.0,5.0,14.0 +0.1125,6.0,14.0 +0.225,7.0,14.0 +0.3375,8.0,14.0 +0.45,9.0,14.0 +0.5625,10.0,14.0 +0.675,11.0,14.0 +0.7875,12.0,14.0 +0.0,5.0,14.0 +0.1125,6.0,14.0 +0.225,7.0,14.0 +0.3375,8.0,14.0 +0.45,9.0,14.0 +0.5625,10.0,14.0 +0.675,11.0,14.0 +0.7875,12.0,14.0 0.0,6.0,14.0 0.1125,7.0,14.0 0.225,8.0,14.0 diff --git a/tests/framework/ROM/tensorflow_keras/gold/data/outLSTMClassifier.csv b/tests/framework/ROM/tensorflow_keras/gold/data/outLSTMClassifier.csv index b6a54c5478..0acc39c774 100644 --- a/tests/framework/ROM/tensorflow_keras/gold/data/outLSTMClassifier.csv +++ b/tests/framework/ROM/tensorflow_keras/gold/data/outLSTMClassifier.csv @@ -1,7 +1,7 @@ time,x,y -0.0,14.0,23.0 -0.3,15.0,23.0 -0.6,16.0,23.0 +0.0,14.0,24.0 +0.3,15.0,24.0 +0.6,16.0,24.0 0.0,2.0,3.0 0.3,3.0,3.0 0.6,4.0,3.0 @@ -14,12 +14,12 @@ time,x,y 0.0,9.0,3.0 0.3,10.0,3.0 0.6,11.0,3.0 -0.0,20.0,23.0 -0.3,21.0,23.0 -0.6,22.0,23.0 -0.0,18.0,23.0 -0.3,19.0,23.0 -0.6,20.0,23.0 +0.0,20.0,24.0 +0.3,21.0,24.0 +0.6,22.0,24.0 +0.0,18.0,24.0 +0.3,19.0,24.0 +0.6,20.0,24.0 0.0,6.0,3.0 0.3,7.0,3.0 0.6,8.0,3.0 diff --git a/tests/framework/ROM/tensorflow_keras/gold/diabetes/outMLPClassifier.csv b/tests/framework/ROM/tensorflow_keras/gold/diabetes/outMLPClassifier.csv index 5d44c222de..4e6ceeb1cd 100644 --- a/tests/framework/ROM/tensorflow_keras/gold/diabetes/outMLPClassifier.csv +++ b/tests/framework/ROM/tensorflow_keras/gold/diabetes/outMLPClassifier.csv @@ -27,7 +27,7 @@ x1,x2,x3,x4,x5,x6,x7,x8,y 0.0,181.0,88.0,44.0,510.0,43.3,0.222,26.0,1.0 8.0,154.0,78.0,32.0,0.0,32.4,0.443,45.0,1.0 1.0,128.0,88.0,39.0,110.0,36.5,1.057,37.0,1.0 -7.0,137.0,90.0,41.0,0.0,32.0,0.391,39.0,0.0 +7.0,137.0,90.0,41.0,0.0,32.0,0.391,39.0,1.0 0.0,123.0,72.0,0.0,0.0,36.3,0.258,52.0,0.0 1.0,106.0,76.0,0.0,0.0,37.5,0.197,26.0,0.0 6.0,190.0,92.0,0.0,0.0,35.5,0.278,66.0,1.0 diff --git a/tests/framework/user_guide/ravenTutorial/RomLoad.xml b/tests/framework/user_guide/ravenTutorial/RomLoad.xml index 9fa826620e..675963c665 100644 --- a/tests/framework/user_guide/ravenTutorial/RomLoad.xml +++ b/tests/framework/user_guide/ravenTutorial/RomLoad.xml @@ -23,11 +23,7 @@ - - sigma-A,decay-A - A, time -

3

- +