def RunReRank(config, FileData):
print("4 Create Query DataList")
genqueries = GenerateQueryClass.GenerateQueries()
#print(FileData)
reRankQueries = genqueries.generateQueriesExcelData(
FileData, config["collection"], config["requestHandler"],
config["solrFeatureStoreName"], config["efiParams"],
config["QueryColums"])
print("5 Running Solr queries to extract features")
solrcmd = ExcuteSolrCommand.ExcuteSolr()
fvGenerator = solrcmd.generateTrainingData(reRankQueries, config["host"],
config["port"], config)
formatter = libsvm_formatter.LibSvmFormatter()
formatter.processQueryDocFeatureVector(fvGenerator, config["trainingFile"])
print("6 Training model using '" + config["trainingLibraryLocation"] +
" " + config["trainingLibraryOptions"] + "'")
libsvm_formatter.trainLibSvm(config["trainingLibraryLocation"],
config["trainingLibraryOptions"],
config["trainingFile"],
config["trainedModelFile"])
print("7 Converting trained model (" + config["trainedModelFile"] +
") to solr model (" + config["solrModelFile"] + ")")
formatter.convertLibSvmModelToLtrModel(config["trainedModelFile"],
config["solrModelFile"],
config["solrModelName"],
config["solrFeatureStoreName"])
print("8 Uploading model (" + config["solrModelFile"] + ") to Solr")
solrcmd.uploadModel(config["collection"], config["host"], config["port"],
config["solrModelFile"], config["solrModelName"])
print("------------------------END----------------------------")
def main(argv=None):
if argv is None:
argv = sys.argv
parser = OptionParser(usage="usage: %prog [options] ", version="%prog 1.0")
parser.add_option('-c',
'--config',
dest='configFile',
help='File of configuration for the test')
(options, args) = parser.parse_args()
if options.configFile == None:
parser.print_help()
return 1
with open(options.configFile) as configFile:
config = json.load(configFile)
print "Uploading features (" + config["solrFeaturesFile"] + ") to Solr"
setupSolr(config["collection"], config["host"], config["port"],
config["solrFeaturesFile"], config["solrFeatureStoreName"])
print "Converting user queries (" + config[
"userQueriesFile"] + ") into Solr queries for feature extraction"
reRankQueries = generateQueries(config["userQueriesFile"],
config["collection"],
config["requestHandler"],
config["solrFeatureStoreName"],
config["efiParams"])
print "Running Solr queries to extract features"
fvGenerator = generateTrainingData(reRankQueries, config["host"],
config["port"])
formatter = libsvm_formatter.LibSvmFormatter()
formatter.processQueryDocFeatureVector(fvGenerator,
config["trainingFile"])
print "Training model using '" + config[
"trainingLibraryLocation"] + " " + config[
"trainingLibraryOptions"] + "'"
libsvm_formatter.trainLibSvm(config["trainingLibraryLocation"],
config["trainingLibraryOptions"],
config["trainingFile"],
config["trainedModelFile"])
print "Converting trained model (" + config[
"trainedModelFile"] + ") to solr model (" + config[
"solrModelFile"] + ")"
formatter.convertLibSvmModelToLtrModel(config["trainedModelFile"],
config["solrModelFile"],
config["solrModelName"],
config["solrFeatureStoreName"])
print "Uploading model (" + config["solrModelFile"] + ") to Solr"
uploadModel(config["collection"], config["host"], config["port"],
config["solrModelFile"], config["solrModelName"])
def main(argv=None):
if argv is None:
argv = sys.argv
parser = OptionParser(usage="usage: %prog [options] ", version="%prog 1.0")
parser.add_option('-c',
'--config',
dest='configFile',
help='File of configuration for the test')
(options, args) = parser.parse_args()
if options.configFile == None:
parser.print_help()
return 1
with open(options.configFile) as configFile:
config = json.load(configFile)
print "Uploading feature space to Solr"
setupSolr(config)
print "Generating feature extraction Solr queries"
reRankQueries = generateQueries(config)
print "Extracting features"
fvGenerator = generateTrainingData(reRankQueries, config)
formatter = libsvm_formatter.LibSvmFormatter()
formatter.processQueryDocFeatureVector(fvGenerator,
config["trainingFile"])
print "Training ranksvm model"
libsvm_formatter.trainLibSvm(config["trainingLibraryLocation"],
config["trainingFile"])
print "Converting ranksvm model to solr model"
formatter.convertLibSvmModelToLtrModel(
config["trainingFile"] + ".model", config["solrModelFile"],
config["solrModelName"])
print "Uploading model to solr"
uploadModel(config["collection"], config["host"], config["port"],
config["solrModelFile"])
def main(argv=None):
if argv is None:
argv = sys.argv
parser = OptionParser(usage="usage: %prog [options] ", version="%prog 1.0")
parser.add_option('-c', '--config',
dest='configFile',
help='File of configuration for the test')
(options, args) = parser.parse_args()
if options.configFile == None:
parser.print_help()
return 1
with open(options.configFile) as configFile:
config = json.load(configFile)
print "Uploading features ("+config["solrFeaturesFile"]+") to Solr"
setupSolr(config["collection"], config["host"], config["port"], config["solrFeaturesFile"], config["solrFeatureStoreName"])
print "Converting user queries ("+config["userQueriesFile"]+") into Solr queries for feature extraction"
reRankQueries = generateQueries(config["userQueriesFile"], config["collection"], config["requestHandler"], config["solrFeatureStoreName"], config["efiParams"])
print "Running Solr queries to extract features"
fvGenerator = generateTrainingData(reRankQueries, config["host"], config["port"])
formatter = libsvm_formatter.LibSvmFormatter();
formatter.processQueryDocFeatureVector(fvGenerator,config["trainingFile"]);
print "Training model using '"+config["trainingLibraryLocation"]+" "+config["trainingLibraryOptions"]+"'"
libsvm_formatter.trainLibSvm(config["trainingLibraryLocation"],config["trainingLibraryOptions"],config["trainingFile"],config["trainedModelFile"])
print "Converting trained model ("+config["trainedModelFile"]+") to solr model ("+config["solrModelFile"]+")"
formatter.convertLibSvmModelToLtrModel(config["trainedModelFile"], config["solrModelFile"], config["solrModelName"], config["solrFeatureStoreName"])
print "Uploading model ("+config["solrModelFile"]+") to Solr"
uploadModel(config["collection"], config["host"], config["port"], config["solrModelFile"], config["solrModelName"])
def main(argv=None):
if argv is None:
argv = sys.argv
parser = OptionParser(usage="usage: %prog [options] ", version="%prog 1.0")
parser.add_option('-c', '--config',
dest='configFile',
help='File of configuration for the test')
(options, args) = parser.parse_args()
if options.configFile == None:
parser.print_help()
return 1
with open(options.configFile) as configFile:
config = json.load(configFile)
print "Uploading feature space to Solr"
setupSolr(config)
print "Generating feature extraction Solr queries"
reRankQueries = generateQueries(config)
print "Extracting features"
fvGenerator = generateTrainingData(reRankQueries, config);
formatter = libsvm_formatter.LibSvmFormatter();
formatter.processQueryDocFeatureVector(fvGenerator,config["trainingFile"]);
print "Training ranksvm model"
libsvm_formatter.trainLibSvm(config["trainingLibraryLocation"],config["trainingFile"])
print "Converting ranksvm model to solr model"
formatter.convertLibSvmModelToLtrModel(config["trainingFile"] + ".model", config["solrModelFile"], config["solrModelName"])
print "Uploading model to solr"
uploadModel(config["collection"], config["host"], config["port"], config["solrModelFile"])
