def test_execution(name, python_command): '''Execute the test case''' tt.run_checked(['output/aql/bin/standalone', 'loop=100']) tt.run_checked(['output/uima/bin/standalone', 'loop=100']) tt.run_checked(['output/ruta/bin/standalone', 'loop=100']) tt.run_checked( ['output/uima/bin/standalone', 'loop=100', 'pear=EmptyUima.pear']) tt.run_checked( ['output/ruta/bin/standalone', 'loop=100', 'pear=EmptyRuta.pear'])
def test_execution(name, python_command): '''Execute the test case''' tt.run_checked(['output/ModelBuilder/bin/standalone']) tt.run_checked(['diff', 'data/out_tfidf_corpus.txt', 'data/tfidf_corpus.txt.expected']) print '****** corpus trainer finished' tt.run_checked(['output/bin/standalone']) tt.run_checked(['diff', 'data/out.txt', 'data/expected.txt'])
def test_execution(name, python_command): '''Execute the test case''' #tt.assert_pass(err != 0, stdout, stderr) print "Execute scenario ContentRankingSample" tt.run_checked([ 'output/ModelBuilder/bin/standalone', 'pythonCommand=' + python_command ]) # the test script runs in python2 # check the python version in the environment since the Streams job might use a different python version ver = tt.get_major_version(python_command) shutil.copy('data/model_KB/d_lemms.json.provided' + str(ver), 'data/model_KB/d_lemms.json') shutil.copy('data/model_KB/kb_lstm_model.pklz.provided' + str(ver), 'data/model_KB/kb_lstm_model.pklz') print 'XXXXXXXXXXXXXXXXXXXXXXXXXXX' tt.run_checked( ['output/bin/standalone', 'pythonCommand=' + python_command]) print 'XXXXXXXXXXXXXXXXXXXXXXXXXXX' tt.run_checked( ['diff', 'data/out.txt', 'data/expected' + str(ver) + '.txt'])
def test_execution(name, python_command): '''Execute the test case''' tt.run_checked(['output/bin/standalone']) tt.run_checked(['diff', 'data/out.txt', 'data/expected.txt'])
def test_execution(name, python_command): '''Execute the test case''' tt.run_checked(['./runTest.sh']) tt.run_checked(['diff', 'mem0', 'mem1'])
def test_execution(name, python_command): '''Execute the test case''' #tt.assert_pass(err != 0, stdout, stderr) print "Execute scenario LinearClassificationSample" tt.run_checked([ 'output/ModelBuilder/bin/standalone', 'pythonCommand=' + python_command ]) tt.run_checked( ['output/bin/standalone', 'pythonCommand=' + python_command]) tt.run_checked(['diff', 'data/out2.txt', 'data/expected.txt']) tt.run_checked([ 'output/ModelBuilder/bin/standalone', 'pythonCommand=' + python_command, 'trainingFile=training2Classes.csv' ]) tt.run_checked( ['output/bin/standalone', 'pythonCommand=' + python_command]) tt.run_checked(['diff', 'data/out2.txt', 'data/expected2Classes.txt'])
def test_execution(name, python_command): '''Execute the test case''' tt.run_checked(['output/bin/standalone'])