
import os
import unittest

from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class __snake_case		(      lowerCAmelCase					,	unittest.TestCase     ):
    _a		:						str=				LxmertTokenizer
    _a		:						Optional[Any]=				LxmertTokenizerFast
    _a		:						List[Any]=				True
    _a		:						int=				True
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           super().setUp()

           lowercase							:     List[str]       	=      [
               """[UNK]""",
               """[CLS]""",
               """[SEP]""",
               """want""",
               """##want""",
               """##ed""",
               """wa""",
               """un""",
               """runn""",
               """##ing""",
               """,""",
               """low""",
               """lowest""",
           ]
           lowercase							:     Optional[int]       	=      os.path.join(self.tmpdirname		,VOCAB_FILES_NAMES["""vocab_file"""]      )
           with open(self.vocab_file		,"""w"""		,encoding="""utf-8"""      ) as vocab_writer:
                  vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]      )      )
    def       _SCREAMING_SNAKE_CASE       (  self		,snake_case      ):



           '''simple docstring'''







           lowercase							:     str       	=      """UNwant\u00E9d,running"""
           lowercase							:     List[Any]       	=      """unwanted, running"""
           return input_text, output_text
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     List[Any]       	=      self.tokenizer_class(self.vocab_file      )

           lowercase							:     Any       	=      tokenizer.tokenize("""UNwant\u00E9d,running"""      )
           self.assertListEqual(snake_case		,["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]      )
           self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case      )		,[7, 4, 5, 10, 8, 9]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           if not self.test_rust_tokenizer:
                  return

           lowercase							:     Union[str, Any]       	=      self.get_tokenizer()
           lowercase							:     Optional[int]       	=      self.get_rust_tokenizer()

           lowercase							:     str       	=      """I was born in 92000, and this is falsé."""

           lowercase							:     Optional[Any]       	=      tokenizer.tokenize(snake_case      )
           lowercase							:     Tuple       	=      rust_tokenizer.tokenize(snake_case      )
           self.assertListEqual(snake_case		,snake_case      )

           lowercase							:     Tuple       	=      tokenizer.encode(snake_case		,add_special_tokens=snake_case      )
           lowercase							:     int       	=      rust_tokenizer.encode(snake_case		,add_special_tokens=snake_case      )
           self.assertListEqual(snake_case		,snake_case      )

           lowercase							:     Optional[Any]       	=      self.get_rust_tokenizer()
           lowercase							:     Any       	=      tokenizer.encode(snake_case      )
           lowercase							:     Union[str, Any]       	=      rust_tokenizer.encode(snake_case      )
           self.assertListEqual(snake_case		,snake_case      )





'''simple docstring'''






import shutil
import tempfile
import unittest

from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio

from .test_feature_extraction_clap import floats_list



@require_torchaudio
@require_sentencepiece
class 							lowercase       (  unittest.TestCase				):


 """simple docstring"""


 def _snake_case (							self							)		->   Optional[Any]:
        _UpperCAmelCase  :						str			     = """laion/clap-htsat-unfused"""
        _UpperCAmelCase  :						int			     = tempfile.mkdtemp()







 def _snake_case (							self  ,**a_							)		->   str:
        return RobertaTokenizer.from_pretrained(self.checkpoint  ,**a_							)







 def _snake_case (							self  ,**a_							)		->   Tuple:
        return ClapFeatureExtractor.from_pretrained(self.checkpoint  ,**a_							)







 def _snake_case (							self							)		->   int:
        shutil.rmtree(self.tmpdirname							)







 def _snake_case (							self							)		->   Optional[int]:
        _UpperCAmelCase  :						str			     = self.get_tokenizer()
        _UpperCAmelCase  :						Any			     = self.get_feature_extractor()

        _UpperCAmelCase  :						int			     = ClapProcessor(tokenizer=a_  ,feature_extractor=a_							)

        processor.save_pretrained(self.tmpdirname							)
        _UpperCAmelCase  :						List[Any]			     = ClapProcessor.from_pretrained(self.tmpdirname							)

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

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







 def _snake_case (							self							)		->   List[Any]:
        _UpperCAmelCase  :						int			     = ClapProcessor(tokenizer=self.get_tokenizer()  ,feature_extractor=self.get_feature_extractor()							)
        processor.save_pretrained(self.tmpdirname							)

        _UpperCAmelCase  :						List[str]			     = self.get_tokenizer(bos_token="""(BOS)"""  ,eos_token="""(EOS)"""							)
        _UpperCAmelCase  :						List[Any]			     = self.get_feature_extractor(do_normalize=a_  ,padding_value=1.0							)

        _UpperCAmelCase  :						Optional[Any]			     = ClapProcessor.from_pretrained(
            self.tmpdirname  ,bos_token="""(BOS)"""  ,eos_token="""(EOS)"""  ,do_normalize=a_  ,padding_value=1.0							)

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

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







 def _snake_case (							self							)		->   str:
        _UpperCAmelCase  :						Tuple			     = self.get_feature_extractor()
        _UpperCAmelCase  :						Dict			     = self.get_tokenizer()

        _UpperCAmelCase  :						str			     = ClapProcessor(tokenizer=a_  ,feature_extractor=a_							)

        _UpperCAmelCase  :						Tuple			     = floats_list((3, 1_000)							)

        _UpperCAmelCase  :						int			     = feature_extractor(a_  ,return_tensors="""np"""							)
        _UpperCAmelCase  :						Union[str, Any]			     = processor(audios=a_  ,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 _snake_case (							self							)		->   Tuple:
        _UpperCAmelCase  :						List[Any]			     = self.get_feature_extractor()
        _UpperCAmelCase  :						Any			     = self.get_tokenizer()

        _UpperCAmelCase  :						Optional[int]			     = ClapProcessor(tokenizer=a_  ,feature_extractor=a_							)

        _UpperCAmelCase  :						Union[str, Any]			     = """This is a test string"""

        _UpperCAmelCase  :						Optional[Any]			     = processor(text=a_							)

        _UpperCAmelCase  :						Any			     = tokenizer(a_							)

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







 def _snake_case (							self							)		->   List[Any]:
        _UpperCAmelCase  :						str			     = self.get_feature_extractor()
        _UpperCAmelCase  :						List[str]			     = self.get_tokenizer()

        _UpperCAmelCase  :						Any			     = ClapProcessor(tokenizer=a_  ,feature_extractor=a_							)

        _UpperCAmelCase  :						List[str]			     = [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        _UpperCAmelCase  :						Dict			     = processor.batch_decode(a_							)
        _UpperCAmelCase  :						Any			     = tokenizer.batch_decode(a_							)

        self.assertListEqual(a_  ,a_							)







 def _snake_case (							self							)		->   Dict:
        _UpperCAmelCase  :						List[str]			     = self.get_feature_extractor()
        _UpperCAmelCase  :						int			     = self.get_tokenizer()

        _UpperCAmelCase  :						Dict			     = ClapProcessor(tokenizer=a_  ,feature_extractor=a_							)

        self.assertListEqual(
            processor.model_input_names[2:]  ,feature_extractor.model_input_names  ,msg="""`processor` and `feature_extractor` model input names do not match"""  ,)



