Files
artcraft/models/tts/NeMo/tests/nemo_text_processing/test_decimal.py
T

50 lines
2.3 KiB
Python

# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import pytest
from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer
from nemo_text_processing.text_normalization.normalize import Normalizer
from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio
from parameterized import parameterized
from utils import PYNINI_AVAILABLE, parse_test_case_file
class TestDecimal:
inverse_normalizer = InverseNormalizer() if PYNINI_AVAILABLE else None
@parameterized.expand(parse_test_case_file('data_inverse_text_normalization/test_cases_decimal.txt'))
@pytest.mark.skipif(
not PYNINI_AVAILABLE, reason="`pynini` not installed, please install via nemo_text_processing/setup.sh"
)
@pytest.mark.run_only_on('CPU')
@pytest.mark.unit
def test_denorm(self, test_input, expected):
pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False)
assert pred == expected
normalizer = Normalizer(input_case="cased") if PYNINI_AVAILABLE else None
normalizer_with_audio = NormalizerWithAudio(input_case='cased') if PYNINI_AVAILABLE else None
@parameterized.expand(parse_test_case_file('data_text_normalization/test_cases_decimal.txt'))
@pytest.mark.skipif(
not PYNINI_AVAILABLE, reason="`pynini` not installed, please install via nemo_text_processing/setup.sh"
)
@pytest.mark.run_only_on('CPU')
@pytest.mark.unit
def test_norm(self, test_input, expected):
pred = self.normalizer.normalize(test_input, verbose=False)
assert pred == expected
pred_non_deterministic = self.normalizer_with_audio.normalize(test_input, n_tagged=100)
assert expected in pred_non_deterministic