def test_rte_classification_without_megam(self):
# Use a sample size for unit testing, since we
# don't need to fully train these classifiers
clf = rte_classifier("IIS", sample_N=100)
clf = rte_classifier("GIS", sample_N=100)
def test_rte_classification_with_megam(self):
nltk.config_megam("/usr/local/bin/megam")
clf = rte_classifier("megam", sample_N=100)
clf = rte_classifier("BFGS", sample_N=100)
def test_rte_classification_with_megam(self):
nltk.config_megam('/usr/local/bin/megam')
clf = rte_classifier('megam', sample_N=100)
clf = rte_classifier('BFGS', sample_N=100)
def test_rte_classification_without_megam(self):
clf = rte_classifier('IIS')
clf = rte_classifier('GIS')
def test_rte_classification_with_megam(self):
nltk.config_megam('/usr/local/bin/megam')
clf = rte_classifier('megam')
clf = rte_classifier('BFGS')
def test_rte_classification_without_megam(self):
clf = rte_classifier('IIS')
clf = rte_classifier('GIS')
def test_rte_classification_with_megam(self):
try:
config_megam()
except (LookupError, AttributeError) as e:
pytest.skip("Skipping tests with dependencies on MEGAM")
clf = rte_classifier("megam", sample_N=100)