




'''simple docstring'''





import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding

class      _a       (		__lowerCAmelCase							):
     SCREAMING_SNAKE_CASE_							:					List[Any]					       =		["""image_processor""", """tokenizer"""]
     SCREAMING_SNAKE_CASE_							:					Optional[int]					       =		"""AutoImageProcessor"""
     SCREAMING_SNAKE_CASE_							:					Dict					       =		"""AutoTokenizer"""






     def __init__(				self      ,_SCREAMING_SNAKE_CASE=None      ,_SCREAMING_SNAKE_CASE=None      ,**_SCREAMING_SNAKE_CASE					)							->    Optional[int]:
          _snake_case							=   None
          if "feature_extractor" in kwargs:
               warnings.warn(
                   "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
                   " instead."      ,_SCREAMING_SNAKE_CASE      ,)
               _snake_case							=   kwargs.pop("feature_extractor"					)

          _snake_case							=   image_processor if image_processor is not None else feature_extractor
          if image_processor is None:
               raise ValueError("You have to specify an image_processor."					)
          if tokenizer is None:
               raise ValueError("You have to specify a tokenizer."					)

          super().__init__(_SCREAMING_SNAKE_CASE      ,_SCREAMING_SNAKE_CASE					)
          _snake_case							=   self.image_processor






     def __call__(				self      ,_SCREAMING_SNAKE_CASE=None      ,_SCREAMING_SNAKE_CASE=None      ,_SCREAMING_SNAKE_CASE=None      ,**_SCREAMING_SNAKE_CASE					)							->    Any:

          if text is None and images is None:
               raise ValueError("You have to specify either text or images. Both cannot be none."					)

          if text is not None:
               _snake_case							=   self.tokenizer(_SCREAMING_SNAKE_CASE      ,return_tensors=_SCREAMING_SNAKE_CASE      ,**_SCREAMING_SNAKE_CASE					)

          if images is not None:
               _snake_case							=   self.image_processor(_SCREAMING_SNAKE_CASE      ,return_tensors=_SCREAMING_SNAKE_CASE      ,**_SCREAMING_SNAKE_CASE					)

          if text is not None and images is not None:
               _snake_case							=   image_features.pixel_values
               return encoding
          elif text is not None:
               return encoding
          else:
               return BatchEncoding(data=dict(**_SCREAMING_SNAKE_CASE					)      ,tensor_type=_SCREAMING_SNAKE_CASE					)






     def        _lowercase			(				self      ,*_SCREAMING_SNAKE_CASE      ,**_SCREAMING_SNAKE_CASE					)							->    str:
          return self.tokenizer.batch_decode(*_SCREAMING_SNAKE_CASE      ,**_SCREAMING_SNAKE_CASE					)






     def        _lowercase			(				self      ,*_SCREAMING_SNAKE_CASE      ,**_SCREAMING_SNAKE_CASE					)							->    Any:
          return self.tokenizer.decode(*_SCREAMING_SNAKE_CASE      ,**_SCREAMING_SNAKE_CASE					)






     @property
     def        _lowercase			(				self					)							->    Optional[int]:
          _snake_case							=   self.tokenizer.model_input_names
          _snake_case							=   self.image_processor.model_input_names
          return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names					)					)






     @property
     def        _lowercase			(				self					)							->    str:
          warnings.warn(
              "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."      ,_SCREAMING_SNAKE_CASE      ,)
          return self.image_processor_class






     @property
     def        _lowercase			(				self					)							->    str:
          warnings.warn(
              "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."      ,_SCREAMING_SNAKE_CASE      ,)
          return self.image_processor








'''simple docstring'''





import argparse
import os


UpperCamelCase_		:    Union[str, Any]									=		{
    '''pytorch''': {
        '''1.13''': {
            '''torch''': '''1.13.1''',
            '''torchvision''': '''0.14.1''',
            '''torchaudio''': '''0.13.1''',
            '''python''': 3.9,
            '''cuda''': '''cu116''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu116'''
            ),
            '''base_image''': '''nvidia/cuda:11.6.2-cudnn8-devel-ubuntu20.04''',
        },
        '''1.12''': {
            '''torch''': '''1.12.1''',
            '''torchvision''': '''0.13.1''',
            '''torchaudio''': '''0.12.1''',
            '''python''': 3.9,
            '''cuda''': '''cu113''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu113'''
            ),
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''1.11''': {
            '''torch''': '''1.11.0''',
            '''torchvision''': '''0.12.0''',
            '''torchaudio''': '''0.11.0''',
            '''python''': 3.9,
            '''cuda''': '''cu113''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu113'''
            ),
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''1.10''': {
            '''torch''': '''1.10.2''',
            '''torchvision''': '''0.11.3''',
            '''torchaudio''': '''0.10.2''',
            '''python''': 3.9,
            '''cuda''': '''cu113''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.10.2 torchvision==0.11.3 torchaudio==0.10.2'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu113'''
            ),
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        # torchaudio < 0.10 has no CUDA-enabled binary distributions
        '''1.9''': {
            '''torch''': '''1.9.1''',
            '''torchvision''': '''0.10.1''',
            '''torchaudio''': '''0.9.1''',
            '''python''': 3.9,
            '''cuda''': '''cu111''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.9.1 torchvision==0.10.1 torchaudio==0.9.1'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu111'''
            ),
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
    },
    '''tensorflow''': {
        '''2.11''': {
            '''tensorflow''': '''2.11.1''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.11.1''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.10''': {
            '''tensorflow''': '''2.10.1''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.10.1''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.9''': {
            '''tensorflow''': '''2.9.3''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.9.3''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.8''': {
            '''tensorflow''': '''2.8.2''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.8.2''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.7''': {
            '''tensorflow''': '''2.7.3''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.7.3''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.6''': {
            '''tensorflow''': '''2.6.5''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.6.5''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.5''': {
            '''tensorflow''': '''2.5.3''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.5.3''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
    },
}


if __name__ == "__main__":
   UpperCamelCase_		:    Optional[Any]									=		argparse.ArgumentParser('''Choose the framework and version to install''')
   parser.add_argument(
       '''--framework''', help='''The framework to install. Should be `torch` or `tensorflow`''', type=str, required=True
   )
   parser.add_argument('''--version''', help='''The version of the framework to install.''', type=str, required=True)
   UpperCamelCase_		:    Tuple									=		parser.parse_args()

   UpperCamelCase_		:    Optional[int]									=		past_versions_testing[args.framework][args.version]

   os.system(F'echo "export INSTALL_CMD=\'{info["install"]}\'" >> ~/.profile')
   print(F'echo "export INSTALL_CMD=\'{info["install"]}\'" >> ~/.profile')

   UpperCamelCase_		:    List[Any]									=		''''''
   if args.framework == "pytorch":
      UpperCamelCase_		:    str									=		info['''cuda''']
   os.system(F'echo \"export CUDA=\'{cuda}\'\" >> ~/.profile')
   print(F'echo \"export CUDA=\'{cuda}\'\" >> ~/.profile')


