


from typing import Dict, List, Optional

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


A   :					str	=      logging.get_logger(__name__)


A   :					int	=      {
    "nielsr/canine-s": 2048,
}

# Unicode defines 1,114,112 total “codepoints”
A   :					Optional[int]	=      1114112

# Below: Constants defining canonical codepoints for special, pseudo-characters.
# Copied from https://github.com/google-research/language/blob/master/language/canine/special_codepoints.py
A   :					Optional[Any]	=      0

A   :					Any	=      0XE000
A   :					List[str]	=      0XE001
A   :					Dict	=      0XE002
A   :					Optional[int]	=      0XE003
A   :					int	=      0XE004

# Maps special codepoints to human-readable names.
A   :					Dict[int, str]	=      {
    # Special symbols are represented using codepoints values that are valid,
    # but designated as "Private Use", meaning that they will never be assigned
    # characters by the Unicode Consortium, and are thus safe for use here.
    #
    # NOTE: Do *NOT* add any sort of [UNK_CHAR] here. They are explicitly
    # excluded and should fail with a hard error.
    CLS: "[CLS]",
    SEP: "[SEP]",
    BOS: "[BOS]",
    MASK: "[MASK]",
    PAD: "[PAD]",
    RESERVED: "[RESERVED]",
}

# Maps special codepoint human-readable names to their codepoint values.
A   :					Dict[str, int]	=      {name: codepoint for codepoint, name in SPECIAL_CODEPOINTS.items()}







class     _lowercase				(							lowercase__):


       """simple docstring"""




       A__      		=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES





       def __init__(     self							:    Optional[int]      ,   __lowerCamelCase							:    Tuple=chr(__lowerCamelCase )      ,   __lowerCamelCase							:    Union[str, Any]=chr(__lowerCamelCase )      ,   __lowerCamelCase							:    int=chr(__lowerCamelCase )      ,   __lowerCamelCase							:    str=chr(__lowerCamelCase )      ,   __lowerCamelCase							:    Any=chr(__lowerCamelCase )      ,   __lowerCamelCase							:    str=chr(__lowerCamelCase )      ,   __lowerCamelCase							:    Dict=False      ,   __lowerCamelCase							:    Optional[Any]=2048      ,   **__lowerCamelCase							:    int      ,   ):


             '''simple docstring'''



             lowerCamelCase__	:       int					=						AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase      ,   __lowerCamelCase ) else bos_token
             lowerCamelCase__	:       List[str]					=						AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase      ,   __lowerCamelCase ) else eos_token
             lowerCamelCase__	:       Any					=						AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase      ,   __lowerCamelCase ) else sep_token
             lowerCamelCase__	:       List[str]					=						AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase      ,   __lowerCamelCase ) else cls_token
             lowerCamelCase__	:       Tuple					=						AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase      ,   __lowerCamelCase ) else pad_token

             # Mask token behave like a normal word, i.e. include the space before it
             lowerCamelCase__	:       List[str]					=						AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase      ,   __lowerCamelCase ) else mask_token

             super().__init__(
                 bos_token=__lowerCamelCase      ,   eos_token=__lowerCamelCase      ,   sep_token=__lowerCamelCase      ,   cls_token=__lowerCamelCase      ,   pad_token=__lowerCamelCase      ,   mask_token=__lowerCamelCase      ,   add_prefix_space=__lowerCamelCase      ,   model_max_length=__lowerCamelCase      ,   **__lowerCamelCase      ,   )

             # Creates a mapping for looking up the IDs of special symbols.
             lowerCamelCase__	:       Dict[str, int]					=						{}
             for codepoint, name in SPECIAL_CODEPOINTS.items():
                   lowerCamelCase__	:       Optional[Any]					=						codepoint

             # Creates a mapping for looking up the string forms of special symbol IDs.
             lowerCamelCase__	:       Dict[int, str]					=						{
                 codepoint: name for name, codepoint in self._special_codepoints.items()
             }

             lowerCamelCase__	:       Any					=						UNICODE_VOCAB_SIZE
             lowerCamelCase__	:       str					=						len(self._special_codepoints )





       @property
       def 		lowerCAmelCase  (     self							:    Dict ):


             '''simple docstring'''



             return self._unicode_vocab_size





       def 		lowerCAmelCase  (     self							:    int      ,   __lowerCamelCase							:    str ):


             '''simple docstring'''



             return list(__lowerCamelCase )





       def 		lowerCAmelCase  (     self							:    Dict      ,   __lowerCamelCase							:    str ):


             '''simple docstring'''



             try:
                   return ord(__lowerCamelCase )
             except TypeError:
                   raise ValueError(f"invalid token: '{token}'" )





       def 		lowerCAmelCase  (     self							:    Optional[Any]      ,   __lowerCamelCase							:    int ):


             '''simple docstring'''



             try:
                   if index in SPECIAL_CODEPOINTS:
                         return SPECIAL_CODEPOINTS[index]
                   return chr(__lowerCamelCase )
             except TypeError:
                   raise ValueError(f"invalid id: {index}" )





       def 		lowerCAmelCase  (     self							:    List[str]      ,   __lowerCamelCase							:    int ):


             '''simple docstring'''



             return "".join(__lowerCamelCase )





       def 		lowerCAmelCase  (     self							:    Union[str, Any]      ,   __lowerCamelCase							:    List[int]      ,   __lowerCamelCase							:    Optional[List[int]] = None ):


             '''simple docstring'''



             lowerCamelCase__	:       Any					=						[self.sep_token_id]
             lowerCamelCase__	:       str					=						[self.cls_token_id]

             lowerCamelCase__	:       Tuple					=						cls + token_ids_a + sep
             if token_ids_a is not None:
                   result += token_ids_a + sep
             return result





       def 		lowerCAmelCase  (     self							:    Any      ,   __lowerCamelCase							:    List[int]      ,   __lowerCamelCase							:    Optional[List[int]] = None      ,   __lowerCamelCase							:    bool = False ):


             '''simple docstring'''



             if already_has_special_tokens:
                   return super().get_special_tokens_mask(
                       token_ids_a=__lowerCamelCase      ,   token_ids_a=__lowerCamelCase      ,   already_has_special_tokens=__lowerCamelCase )

             lowerCamelCase__	:       Union[str, Any]					=						[1] + ([0] * len(__lowerCamelCase )) + [1]
             if token_ids_a is not None:
                   result += ([0] * len(__lowerCamelCase )) + [1]
             return result





       def 		lowerCAmelCase  (     self							:    Tuple      ,   __lowerCamelCase							:    List[int]      ,   __lowerCamelCase							:    Optional[List[int]] = None ):


             '''simple docstring'''



             lowerCamelCase__	:       int					=						[self.sep_token_id]
             lowerCamelCase__	:       Optional[Any]					=						[self.cls_token_id]

             lowerCamelCase__	:       Union[str, Any]					=						len(cls + token_ids_a + sep ) * [0]
             if token_ids_a is not None:
                   result += len(token_ids_a + sep ) * [1]
             return result





       def 		lowerCAmelCase  (     self							:    str      ,   __lowerCamelCase							:    str      ,   __lowerCamelCase							:    Optional[str] = None ):


             '''simple docstring'''



             return ()






from typing import TYPE_CHECKING

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


A   :					Optional[int]	=      {
    "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:
    A   :					List[Any]	=      ["SpeechT5Tokenizer"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A   :					List[str]	=      [
        "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

    A   :					Any	=      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


