



'''simple docstring'''


from typing import TYPE_CHECKING

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


_lowerCamelCase	:       int      	=	{
    "configuration_speech_to_text": ["SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "Speech2TextConfig"],
    "processing_speech_to_text": ["Speech2TextProcessor"],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowerCamelCase	:       Optional[int]      	=	["Speech2TextTokenizer"]

try:
   if not is_speech_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowerCamelCase	:       Tuple      	=	["Speech2TextFeatureExtractor"]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowerCamelCase	:       Tuple      	=	[
       "TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
       "TFSpeech2TextForConditionalGeneration",
       "TFSpeech2TextModel",
       "TFSpeech2TextPreTrainedModel",
   ]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowerCamelCase	:       int      	=	[
       "SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
       "Speech2TextForConditionalGeneration",
       "Speech2TextModel",
       "Speech2TextPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_speech_to_text import SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextConfig
   from .processing_speech_to_text import SpeechaTextProcessor

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_speech_to_text import SpeechaTextTokenizer

   try:
      if not is_speech_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_speech_to_text import SpeechaTextFeatureExtractor

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_speech_to_text import (
          TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFSpeechaTextForConditionalGeneration,
          TFSpeechaTextModel,
          TFSpeechaTextPreTrainedModel,
      )

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_speech_to_text import (
          SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
          SpeechaTextForConditionalGeneration,
          SpeechaTextModel,
          SpeechaTextPreTrainedModel,
      )

else:
   import sys

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






'''simple docstring'''


import warnings

from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor


_lowerCamelCase	:       str      	=	logging.get_logger(__name__)

class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""





    def __init__(  self      :					Dict  ,						*UpperCamelCase__      :					List[Any]  ,						**UpperCamelCase__      :					List[Any] ):


       """simple docstring"""







       warnings.warn(
           'The class ChineseCLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
           ' Please use ChineseCLIPImageProcessor instead.'  ,						UpperCamelCase__  ,						)
       super().__init__(*UpperCamelCase__  ,						**UpperCamelCase__ )

