def test_generate_noise_utterances(self, mocked_get_noise):
# Given
language = LANGUAGE_EN
num_intents = 2
noise_factor = 1
utterances_length = 5
noise = [str(i) for i in range(utterances_length)]
mocked_get_noise.return_value = noise
augmented_utterances = [
{
"data": [
{
"text": " ".join(
"{}".format(i) for i in range(utterances_length))
}
]
}
]
num_utterances = 10
random_state = np.random.RandomState(1)
augmented_utterances = augmented_utterances * num_utterances
config = IntentClassifierDataAugmentationConfig(
noise_factor=noise_factor)
# When
noise_utterances = generate_noise_utterances(
augmented_utterances, noise, num_intents, config, language,
random_state)
# Then
joined_noise = text_to_utterance(" ".join(noise))
for u in noise_utterances:
self.assertEqual(u, joined_noise)
def test_generate_noise_utterances(self, mocked_get_noises):
# Given
language = LANGUAGE_EN
num_intents = 2
noise_factor = 1
utterances_length = 5
noise = [str(i) for i in range(utterances_length)]
mocked_get_noises.return_value = noise
augmented_utterances = [
{
"data": [
{
"text": " ".join(
"{}".format(i) for i in range(utterances_length))
}
]
}
]
num_utterances = 10
random_state = np.random.RandomState(1)
augmented_utterances = augmented_utterances * num_utterances
config = IntentClassifierDataAugmentationConfig(
noise_factor=noise_factor)
# When
noise_utterances = generate_noise_utterances(
augmented_utterances, num_intents, config, language, random_state)
# Then
joined_noise = " ".join(noise)
for u in noise_utterances:
self.assertEqual(u, joined_noise)