def test_create_label_tensors(self):
tensorizer = LabelTensorizer(column="label")
init = tensorizer.initialize()
init.send(None) # kick
for row in self.data.train:
init.send(row)
init.close()
rows = [
{
"label": types.Label("weather/find")
},
{
"label": types.Label("alarm/set_alarm")
},
{
"label": types.Label("non/existent")
},
]
tensors = (tensorizer.numberize(row) for row in rows)
tensor = next(tensors)
self.assertEqual(6, tensor)
tensor = next(tensors)
self.assertEqual(1, tensor)
with self.assertRaises(Exception):
tensor = next(tensors)
def test_create_label_tensors_fails_with_unknown_label(self):
tensorizer = LabelTensorizer(column="label")
init = tensorizer.initialize()
init.send(None) # kick
for row in self.data.train:
init.send(row)
init.close()
batch = [
{"label": types.Label("non/existent")},
{"label": types.Label("alarm/set_alarm")},
]
with self.assertRaises(Exception):
tensorizer.create_training_tensors(batch)
def test_create_label_tensors(self):
tensorizer = LabelTensorizer(column="label")
init = tensorizer.initialize()
init.send(None) # kick
for row in self.data.train:
init.send(row)
init.close()
batch = [
{"label": types.Label("weather/find")},
{"label": types.Label("alarm/set_alarm")},
]
tensor = tensorizer.create_training_tensors(batch)
self.assertEqual((2,), tensor.size())
self.assertEqual([6, 1], tensor.tolist())
def load_label(s):
return types.Label(s)