2023 the huggingface team 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 orglicenseslicense2 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 copied from transformers tests models whisper testprocessorwhisper whisperprocessortest gettokenizer with whisperclvp copied from transformers tests models whisper testprocessorwhisper whisperprocessortest getfeatureextractor with whisperclvp copied from transformers tests models whisper testprocessorwhisper whisperprocessortest testsaveloadpretraineddefault with whisperclvp copied from transformers tests models whisper testprocessorwhisper whisperprocessortest testfeatureextractor with whisperclvp processorrawspeechprocessorrawspeechrawspeech copied from transformers tests models whisper testprocessorwhisper whisperprocessortest testtokenizer with whisperclvp copied from transformers tests models whisper testprocessorwhisper whisperprocessortest testtokenizerdecode with whisperclvp 2023 the huggingface team 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 copied from transformers tests models whisper test_processor_whisper whisperprocessortest get_tokenizer with whisper clvp copied from transformers tests models whisper test_processor_whisper whisperprocessortest get_feature_extractor with whisper clvp copied from transformers tests models whisper test_processor_whisper whisperprocessortest test_save_load_pretrained_default with whisper clvp copied from transformers tests models whisper test_processor_whisper whisperprocessortest test_feature_extractor with whisper clvp processor raw_speech processor raw_speech raw_speech copied from transformers tests models whisper test_processor_whisper whisperprocessortest test_tokenizer with whisper clvp copied from transformers tests models whisper test_processor_whisper whisperprocessortest test_tokenizer_decode with whisper clvp
import gc
import shutil
import tempfile
import unittest

from transformers import ClvpFeatureExtractor, ClvpProcessor, ClvpTokenizer
from transformers.testing_utils import require_torch

from .test_feature_extraction_clvp import floats_list


@require_torch
class ClvpProcessorTest(unittest.TestCase):
    def setUp(self):
        self.checkpoint = "susnato/clvp_dev"
        self.tmpdirname = tempfile.mkdtemp()

    def tearDown(self):
        super().tearDown()
        shutil.rmtree(self.tmpdirname)
        gc.collect()

    
    def get_tokenizer(self, **kwargs):
        return ClvpTokenizer.from_pretrained(self.checkpoint, **kwargs)

    
    def get_feature_extractor(self, **kwargs):
        return ClvpFeatureExtractor.from_pretrained(self.checkpoint, **kwargs)

    
    def test_save_load_pretrained_default(self):
        tokenizer = self.get_tokenizer()
        feature_extractor = self.get_feature_extractor()

        processor = ClvpProcessor(tokenizer=tokenizer, feature_extractor=feature_extractor)

        processor.save_pretrained(self.tmpdirname)
        processor = ClvpProcessor.from_pretrained(self.tmpdirname)

        self.assertEqual(processor.tokenizer.get_vocab(), tokenizer.get_vocab())
        self.assertIsInstance(processor.tokenizer, ClvpTokenizer)

        self.assertEqual(processor.feature_extractor.to_json_string(), feature_extractor.to_json_string())
        self.assertIsInstance(processor.feature_extractor, ClvpFeatureExtractor)

    
    def test_feature_extractor(self):
        feature_extractor = self.get_feature_extractor()
        tokenizer = self.get_tokenizer()

        processor = ClvpProcessor(tokenizer=tokenizer, feature_extractor=feature_extractor)

        raw_speech = floats_list((3, 1000))

        input_feat_extract = feature_extractor(raw_speech, return_tensors="np")
        input_processor = processor(raw_speech=raw_speech, return_tensors="np")

        for key in input_feat_extract.keys():
            self.assertAlmostEqual(input_feat_extract[key].sum(), input_processor[key].sum(), delta=1e-2)

    
    def test_tokenizer(self):
        feature_extractor = self.get_feature_extractor()
        tokenizer = self.get_tokenizer()

        processor = ClvpProcessor(tokenizer=tokenizer, feature_extractor=feature_extractor)

        input_str = "This is a test string"

        encoded_processor = processor(text=input_str)

        encoded_tok = tokenizer(input_str)

        for key in encoded_tok.keys():
            self.assertListEqual(encoded_tok[key], encoded_processor[key])

    
    def test_tokenizer_decode(self):
        feature_extractor = self.get_feature_extractor()
        tokenizer = self.get_tokenizer()

        processor = ClvpProcessor(tokenizer=tokenizer, feature_extractor=feature_extractor)

        predicted_ids = [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        decoded_processor = processor.batch_decode(predicted_ids)
        decoded_tok = tokenizer.batch_decode(predicted_ids)

        self.assertListEqual(decoded_tok, decoded_processor)

    def test_save_load_pretrained_additional_features(self):
        processor = ClvpProcessor(tokenizer=self.get_tokenizer(), feature_extractor=self.get_feature_extractor())
        processor.save_pretrained(self.tmpdirname)

        tokenizer_add_kwargs = self.get_tokenizer(pad_token="(PAD)")
        feature_extractor_add_kwargs = self.get_feature_extractor(sampling_rate=16000)

        processor = ClvpProcessor.from_pretrained(
            self.tmpdirname,
            pad_token="(PAD)",
            sampling_rate=16000,
        )

        self.assertEqual(processor.tokenizer.get_vocab(), tokenizer_add_kwargs.get_vocab())
        self.assertIsInstance(processor.tokenizer, ClvpTokenizer)

        self.assertEqual(processor.feature_extractor.to_json_string(), feature_extractor_add_kwargs.to_json_string())
        self.assertIsInstance(processor.feature_extractor, ClvpFeatureExtractor)

    def test_model_input_names(self):
        feature_extractor = self.get_feature_extractor()
        tokenizer = self.get_tokenizer()

        processor = ClvpProcessor(tokenizer=tokenizer, feature_extractor=feature_extractor)

        self.assertListEqual(
            sorted(processor.model_input_names),
            sorted(set(feature_extractor.model_input_names + tokenizer.model_input_names)),
            msg="`processor` and `feature_extractor` model input names do not match",
        )