def test_classifier_server_get():
x_hotel = ['book a hotel', 'need a nice place to stay', 'any motels near by']
x_weather = ['what is the weather like', 'is it hot outside']
x_place = ['which place is this', 'where are we', 'where are you going', 'which place is it']
x_name = ['What is your name', 'Who are you', 'What do i call you', 'what are you called']
clf = Classifier()
clf.fit(x_hotel, 'hotel')
clf.fit(x_weather, 'weather')
clf.fit(x_place, 'place')
clf.fit(x_name, 'name')
clf_serialized = clf.serialize()
server = NLUServer(clf).serve(test=True)
r = server.requests.get("/models/classifier/predict?input=will it rain today")
assert r.text == 'weather'
r = server.requests.get("/models/classifier/config")
assert r.json() == clf_serialized
def test_classifier_serialization(self):
x_hotel = ['book a hotel', 'need a nice place to stay', 'any motels near by']
x_weather = ['what is the weather like', 'is it hot outside']
clf1 = Classifier()
clf1.fit(x_hotel, 'hotel')
clf1.fit(x_weather, 'weather')
config = clf1.serialize()
clf2 = Classifier.deserialize(config)
assert clf1.classes == clf2.classes
test_inputs = ['will it rain today', 'find a place to stay']
for test_input in test_inputs:
clf1_out = clf1.predict(test_input, return_probs=True)
clf2_out = clf2.predict(test_input, return_probs=True)
assert clf1_out == clf2_out
def test_classifier_serialization():
x_hotel = ['book a hotel', 'need a nice place to stay', 'any motels near by']
x_weather = ['what is the weather like', 'is it hot outside']
clf1 = Classifier()
clf1.fit(x_hotel, 'hotel')
clf1.fit(x_weather, 'weather')
config = clf1.serialize()
clf2 = Classifier.deserialize(config)
assert clf1.classes == clf2.classes
test_inputs = ['will it rain today', 'find a place to stay']
for test_input in test_inputs:
clf1_out = clf1.predict(test_input, return_probs=True)
clf2_out = clf2.predict(test_input, return_probs=True)
assert clf1_out == clf2_out