


from __future__ import annotations

import sys
from collections import deque
from typing import Generic, TypeVar

lowerCAmelCase__      		= TypeVar('T')







class      lowerCAmelCase__       (				Generic[T]):




     '''simple docstring'''
     __SCREAMING_SNAKE_CASE  			= 42  # Cache store of keys
     __SCREAMING_SNAKE_CASE  			= 42  # References of the keys in cache
     __SCREAMING_SNAKE_CASE  			= 10  # Maximum capacity of cache


     def __init__(						self ,						__lowerCamelCase)			->				None:
            _A      :       List[Any]				    = deque()
            _A      :       Union[str, Any]				    = set()
            if not n:
                   _A      :       List[Any]				    = sys.maxsize
            elif n < 0:
                   raise ValueError("n should be an integer greater than 0.")
            else:
                   _A      :       str				    = n


     def  _lowerCamelCase (						self ,						__lowerCamelCase)			->				None:
            if x not in self.key_reference:
                   if len(self.dq_store) == LRUCache._MAX_CAPACITY:
                          _A      :       Optional[Any]				    = self.dq_store.pop()
                          self.key_reference.remove(__lowerCamelCase)
            else:
                   self.dq_store.remove(__lowerCamelCase)

            self.dq_store.appendleft(__lowerCamelCase)
            self.key_reference.add(__lowerCamelCase)


     def  _lowerCamelCase (						self)			->				None:
            for k in self.dq_store:
                   print(__lowerCamelCase)


     def __repr__(						self)			->				str:
            return F"LRUCache({self._MAX_CAPACITY}) => {list(self.dq_store)}"


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    lowerCAmelCase__      		= LRUCache(4)
    lru_cache.refer('A')
    lru_cache.refer(2)
    lru_cache.refer(3)
    lru_cache.refer('A')
    lru_cache.refer(4)
    lru_cache.refer(5)
    lru_cache.display()

    print(lru_cache)
    assert str(lru_cache) == "LRUCache(4) => [5, 4, 'A', 3]"




from typing import TYPE_CHECKING

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


lowerCAmelCase__      		= {
    '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:
    lowerCAmelCase__      		= ['SpeechT5Tokenizer']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__      		= [
        '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

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