

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


lowercase_             =     {
    'configuration_speecht5': [
        'SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP',
        'SpeechT5Config',
        'SpeechT5HifiGanConfig',
    ],
    'feature_extraction_speecht5': ['SpeechT5FeatureExtractor'],
    'processing_speecht5': ['SpeechT5Processor'],
}

try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_             =     ['SpeechT5Tokenizer']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_             =     [
      'SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST',
      'SpeechT5ForSpeechToText',
      'SpeechT5ForSpeechToSpeech',
      'SpeechT5ForTextToSpeech',
      'SpeechT5Model',
      'SpeechT5PreTrainedModel',
      'SpeechT5HifiGan',
  ]

if TYPE_CHECKING:
  from .configuration_speechta import (
      SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
      SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
      SpeechTaConfig,
      SpeechTaHifiGanConfig,
  )
  from .feature_extraction_speechta import SpeechTaFeatureExtractor
  from .processing_speechta import SpeechTaProcessor

  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_speechta import SpeechTaTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_speechta import (
        SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
        SpeechTaForSpeechToSpeech,
        SpeechTaForSpeechToText,
        SpeechTaForTextToSpeech,
        SpeechTaHifiGan,
        SpeechTaModel,
        SpeechTaPreTrainedModel,
    )

else:
  import sys

  lowercase_             =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class 				__lowerCAmelCase  (      SCREAMING_SNAKE_CASE    ,    unittest.TestCase							):
  _a		    =						OpenAIGPTTokenizer
  _a		    =						OpenAIGPTTokenizerFast
  _a		    =						True
  _a		    =						False




  def 						A__  (       self      )						->				Tuple:
        '''simple docstring'''






        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        _lowercase			 =[
            'l',
            'o',
            'w',
            'e',
            'r',
            's',
            't',
            'i',
            'd',
            'n',
            'w</w>',
            'r</w>',
            't</w>',
            'lo',
            'low',
            'er</w>',
            'low</w>',
            'lowest</w>',
            'newer</w>',
            'wider</w>',
            '<unk>',
        ]
        _lowercase			 =dict(zip(lowerCAmelCase							,     range(len(lowerCAmelCase      )      )      )      )
        _lowercase			 =['#version: 0.2', 'l o', 'lo w', 'e r</w>', '']

        _lowercase			 =os.path.join(self.tmpdirname							,     VOCAB_FILES_NAMES['vocab_file']      )
        _lowercase			 =os.path.join(self.tmpdirname							,     VOCAB_FILES_NAMES['merges_file']      )
        with open(self.vocab_file							,     'w'      ) as fp:
              fp.write(json.dumps(lowerCAmelCase      )      )
        with open(self.merges_file							,     'w'      ) as fp:
              fp.write('\n'.join(lowerCAmelCase      )      )




  def 						A__  (       self							,     lowerCAmelCase      )						->				str:
        '''simple docstring'''






        return "lower newer", "lower newer"




  def 						A__  (       self      )						->				Tuple:
        '''simple docstring'''






        _lowercase			 =OpenAIGPTTokenizer(self.vocab_file							,     self.merges_file      )

        _lowercase			 ='lower'
        _lowercase			 =['low', 'er</w>']
        _lowercase			 =tokenizer.tokenize(lowerCAmelCase      )
        self.assertListEqual(lowerCAmelCase							,     lowerCAmelCase      )

        _lowercase			 =tokens + ['<unk>']
        _lowercase			 =[14, 15, 20]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase      )							,     lowerCAmelCase      )




  def 						A__  (       self							,     lowerCAmelCase=15      )						->				Union[str, Any]:
        '''simple docstring'''






        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
                    _lowercase			 =self.rust_tokenizer_class.from_pretrained(lowerCAmelCase							,     **lowerCAmelCase      )

                    # Simple input
                    _lowercase			 ='This is a simple input'
                    _lowercase			 =['This is a simple input 1', 'This is a simple input 2']
                    _lowercase			 =('This is a simple input', 'This is a pair')
                    _lowercase			 =[
                        ('This is a simple input 1', 'This is a simple input 2'),
                        ('This is a simple pair 1', 'This is a simple pair 2'),
                    ]

                    # Simple input tests
                    self.assertRaises(lowerCAmelCase							,     tokenizer_r.encode							,     lowerCAmelCase							,     max_length=lowerCAmelCase							,     padding='max_length'      )

                    # Simple input
                    self.assertRaises(lowerCAmelCase							,     tokenizer_r.encode_plus							,     lowerCAmelCase							,     max_length=lowerCAmelCase							,     padding='max_length'      )

                    # Simple input
                    self.assertRaises(
                        lowerCAmelCase							,     tokenizer_r.batch_encode_plus							,     lowerCAmelCase							,     max_length=lowerCAmelCase							,     padding='max_length'							,     )

                    # Pair input
                    self.assertRaises(lowerCAmelCase							,     tokenizer_r.encode							,     lowerCAmelCase							,     max_length=lowerCAmelCase							,     padding='max_length'      )

                    # Pair input
                    self.assertRaises(lowerCAmelCase							,     tokenizer_r.encode_plus							,     lowerCAmelCase							,     max_length=lowerCAmelCase							,     padding='max_length'      )

                    # Pair input
                    self.assertRaises(
                        lowerCAmelCase							,     tokenizer_r.batch_encode_plus							,     lowerCAmelCase							,     max_length=lowerCAmelCase							,     padding='max_length'							,     )




  def 						A__  (       self      )						->				Dict:
        '''simple docstring'''






        pass





@require_ftfy
@require_spacy
@require_tokenizers
class 				__lowerCAmelCase  (      SCREAMING_SNAKE_CASE							):
  pass


