





'''simple docstring'''






import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer


snake_case_     =	logging.get_logger(__name__)

snake_case_     =	{"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

snake_case_     =	{
    """vocab_file""": {
        """distilbert-base-uncased""": """https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt""",
        """distilbert-base-uncased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/vocab.txt"""
        ),
        """distilbert-base-cased""": """https://huggingface.co/distilbert-base-cased/resolve/main/vocab.txt""",
        """distilbert-base-cased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/vocab.txt"""
        ),
        """distilbert-base-german-cased""": """https://huggingface.co/distilbert-base-german-cased/resolve/main/vocab.txt""",
        """distilbert-base-multilingual-cased""": (
            """https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/vocab.txt"""
        ),
    },
    """tokenizer_file""": {
        """distilbert-base-uncased""": """https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json""",
        """distilbert-base-uncased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/tokenizer.json"""
        ),
        """distilbert-base-cased""": """https://huggingface.co/distilbert-base-cased/resolve/main/tokenizer.json""",
        """distilbert-base-cased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/tokenizer.json"""
        ),
        """distilbert-base-german-cased""": (
            """https://huggingface.co/distilbert-base-german-cased/resolve/main/tokenizer.json"""
        ),
        """distilbert-base-multilingual-cased""": (
            """https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/tokenizer.json"""
        ),
    },
}

snake_case_     =	{
    """distilbert-base-uncased""": 5_12,
    """distilbert-base-uncased-distilled-squad""": 5_12,
    """distilbert-base-cased""": 5_12,
    """distilbert-base-cased-distilled-squad""": 5_12,
    """distilbert-base-german-cased""": 5_12,
    """distilbert-base-multilingual-cased""": 5_12,
}


snake_case_     =	{
    """distilbert-base-uncased""": {"""do_lower_case""": True},
    """distilbert-base-uncased-distilled-squad""": {"""do_lower_case""": True},
    """distilbert-base-cased""": {"""do_lower_case""": False},
    """distilbert-base-cased-distilled-squad""": {"""do_lower_case""": False},
    """distilbert-base-german-cased""": {"""do_lower_case""": False},
    """distilbert-base-multilingual-cased""": {"""do_lower_case""": False},
}


class   _lowercase						(							a				):
   _UpperCamelCase       		=   VOCAB_FILES_NAMES
   _UpperCamelCase       		=   PRETRAINED_VOCAB_FILES_MAP
   _UpperCamelCase       		=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _UpperCamelCase       		=   PRETRAINED_INIT_CONFIGURATION
   _UpperCamelCase       		=   ["""input_ids""", """attention_mask"""]
   _UpperCamelCase       		=   DistilBertTokenizer


   def __init__( self    ,   _UpperCAmelCase=None    ,   _UpperCAmelCase=None    ,   _UpperCAmelCase=True    ,   _UpperCAmelCase="[UNK]"    ,   _UpperCAmelCase="[SEP]"    ,   _UpperCAmelCase="[PAD]"    ,   _UpperCAmelCase="[CLS]"    ,   _UpperCAmelCase="[MASK]"    ,   _UpperCAmelCase=True    ,   _UpperCAmelCase=None    ,   **_UpperCAmelCase    ,   ):
       super().__init__(
           _UpperCAmelCase    ,   tokenizer_file=_UpperCAmelCase    ,   do_lower_case=_UpperCAmelCase    ,   unk_token=_UpperCAmelCase    ,   sep_token=_UpperCAmelCase    ,   pad_token=_UpperCAmelCase    ,   cls_token=_UpperCAmelCase    ,   mask_token=_UpperCAmelCase    ,   tokenize_chinese_chars=_UpperCAmelCase    ,   strip_accents=_UpperCAmelCase    ,   **_UpperCAmelCase    ,   )

       A       :       List[Any]							=						json.loads(self.backend_tokenizer.normalizer.__getstate__()					)
       if (
           normalizer_state.get('''lowercase'''    ,   _UpperCAmelCase					) != do_lower_case
           or normalizer_state.get('''strip_accents'''    ,   _UpperCAmelCase					) != strip_accents
           or normalizer_state.get('''handle_chinese_chars'''    ,   _UpperCAmelCase					) != tokenize_chinese_chars
       ):
           A       :       Tuple							=						getattr(_UpperCAmelCase    ,   normalizer_state.pop('''type'''					)					)
           A       :       str							=						do_lower_case
           A       :       str							=						strip_accents
           A       :       Tuple							=						tokenize_chinese_chars
           A       :       List[Any]							=						normalizer_class(**_UpperCAmelCase					)

       A       :       int							=						do_lower_case


   def 					snake_case				( self    ,   _UpperCAmelCase    ,   _UpperCAmelCase=None					):
       A       :       Optional[Any]							=						[self.cls_token_id] + token_ids_a + [self.sep_token_id]

       if token_ids_a:
           output += token_ids_a + [self.sep_token_id]

       return output


   def 					snake_case				( self    ,   _UpperCAmelCase    ,   _UpperCAmelCase = None					):
       A       :       List[str]							=						[self.sep_token_id]
       A       :       str							=						[self.cls_token_id]
       if token_ids_a is None:
           return len(cls + token_ids_a + sep					) * [0]
       return len(cls + token_ids_a + sep					) * [0] + len(token_ids_a + sep					) * [1]


   def 					snake_case				( self    ,   _UpperCAmelCase    ,   _UpperCAmelCase = None					):
       A       :       int							=						self._tokenizer.model.save(_UpperCAmelCase    ,   name=_UpperCAmelCase					)
       return tuple(_UpperCAmelCase					)







'''simple docstring'''






from typing import TYPE_CHECKING

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


snake_case_     =	{
    """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:
     snake_case_     =	["""SpeechT5Tokenizer"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case_     =	[
         """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

     snake_case_     =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
