Error while building MulticlassSVM cookbook.

error.txt

[  0%] Built target class_list
[  0%] Built target HeadersProtobuf
[  0%] Built target ChunksProtobuf
[  1%] Built target ShogunVersionProtobuf
[  3%] Generating version header
[  3%] Built target version
[ 96%] Built target libshogun
[ 96%] Built target shogun
[ 96%] Built target ctags
[ 96%] Generating examples from meta-language
Translating gaussian_processes/gaussian_process_classifier.sg
Translating gaussian_processes/gaussian_process_regression.sg
Translating multiclass_classifier/svm.sg
Traceback (most recent call last):
  File "/home/sanuj/Projects/shogun_cb/examples/meta/generator/generate.py", line 135, in <module>
    includedTargets=args.targets, storeVars=storeVars)
  File "/home/sanuj/Projects/shogun_cb/examples/meta/generator/generate.py", line 59, in translateExamples
    ast = parse(file.read(), os.path.join(dirRelative, filename))
  File "/home/sanuj/Projects/shogun_cb/examples/meta/generator/parse.py", line 285, in parse
    return parser.parse(programString, filePath)
  File "/home/sanuj/Projects/shogun_cb/examples/meta/generator/parse.py", line 28, in parse
    program = self.parser.parse(programString)
  File "/usr/local/lib/python2.7/dist-packages/ply-3.8-py2.7.egg/ply/yacc.py", line 331, in parse
    return self.parseopt_notrack(input, lexer, debug, tracking, tokenfunc)
  File "/usr/local/lib/python2.7/dist-packages/ply-3.8-py2.7.egg/ply/yacc.py", line 1049, in parseopt_notrack
    lookahead = get_token()     # Get the next token
  File "/usr/local/lib/python2.7/dist-packages/ply-3.8-py2.7.egg/ply/lex.py", line 386, in token
    newtok = self.lexerrorf(tok)
  File "/home/sanuj/Projects/shogun_cb/examples/meta/generator/parse.py", line 121, in t_error
    raise TypeError("Failed to tokenize input. Unknown text on line %d '%s'" % (t.lineno, t.value,))
TypeError: Failed to tokenize input. Unknown text on line 15 ';
MulticlassSVM svm(C, gauss_kernel, labels_train)
svm.set_epsilon(epsilon)
#![create_instance]

#![train_and_apply]
svm.train()
MulticlassLabels labels_predict = svm.apply_multiclass(features_test)
#![train_and_apply]

#![evaluate_accuracy]
MulticlassAccuracy eval()
real accuracy = eval.evaluate(labels_predict, labels_test)
#![evaluate_accuracy]

# additional integration testing variables
RealVector output = labels_predict.get_labels()
'
make[3]: *** [examples/meta/CMakeFiles/meta_examples] Error 1
make[2]: *** [examples/meta/CMakeFiles/meta_examples.dir/all] Error 2
make[1]: *** [examples/meta/cpp/CMakeFiles/build_cpp_meta_examples.dir/rule] Error 2

svm.sg

CSVFile f_feats_train("../../data/classifier_4class_2d_linear_features_train.dat")
CSVFile f_feats_test("../../data/classifier_4class_2d_linear_features_test.dat")
CSVFile f_labels_train("../../data/classifier_4class_2d_linear_labels_train.dat")
CSVFile f_labels_test("../../data/classifier_4class_2d_linear_labels_test.dat")

#![create_features]
RealFeatures features_train(f_feats_train)
RealFeatures features_test(f_feats_test)
MulticlassLabels labels_train(f_labels_train)
MulticlassLabels labels_test(f_labels_test)
#![create_features]

#![set_parameters]
real C = 1
real epsilon = 0.0001
GaussianKernel gauss_kernel(features_train, features_train, 15)
#![set_parameters]

#![create_instance]
MulticlassOneVsOneStrategy ovo_strategy();
MulticlassSVM svm(ovo_strategy, C, gauss_kernel, labels_train)
svm.set_epsilon(epsilon)
#![create_instance]

#![train_and_apply]
svm.train()
MulticlassLabels labels_predict = svm.apply_multiclass(features_test)
#![train_and_apply]

#![evaluate_accuracy]
MulticlassAccuracy eval()
real accuracy = eval.evaluate(labels_predict, labels_test)
#![evaluate_accuracy]

# additional integration testing variables
RealVector output = labels_predict.get_labels()