


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


__snake_case   							=						{
    '''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConfig''', '''MobileViTOnnxConfig'''],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case   							=						['''MobileViTFeatureExtractor''']
    __snake_case   							=						['''MobileViTImageProcessor''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case   							=						[
        '''MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''MobileViTForImageClassification''',
        '''MobileViTForSemanticSegmentation''',
        '''MobileViTModel''',
        '''MobileViTPreTrainedModel''',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case   							=						[
        '''TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''TFMobileViTForImageClassification''',
        '''TFMobileViTForSemanticSegmentation''',
        '''TFMobileViTModel''',
        '''TFMobileViTPreTrainedModel''',
    ]

if TYPE_CHECKING:
    from .configuration_mobilevit import MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileViTConfig, MobileViTOnnxConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_mobilevit import MobileViTFeatureExtractor
        from .image_processing_mobilevit import MobileViTImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mobilevit import (
            MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
            MobileViTForImageClassification,
            MobileViTForSemanticSegmentation,
            MobileViTModel,
            MobileViTPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_mobilevit import (
            TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFMobileViTForImageClassification,
            TFMobileViTForSemanticSegmentation,
            TFMobileViTModel,
            TFMobileViTPreTrainedModel,
        )


else:
    import sys

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






__snake_case   							=						{
    '''a''': '''AAAAA''',
    '''b''': '''AAAAB''',
    '''c''': '''AAABA''',
    '''d''': '''AAABB''',
    '''e''': '''AABAA''',
    '''f''': '''AABAB''',
    '''g''': '''AABBA''',
    '''h''': '''AABBB''',
    '''i''': '''ABAAA''',
    '''j''': '''BBBAA''',
    '''k''': '''ABAAB''',
    '''l''': '''ABABA''',
    '''m''': '''ABABB''',
    '''n''': '''ABBAA''',
    '''o''': '''ABBAB''',
    '''p''': '''ABBBA''',
    '''q''': '''ABBBB''',
    '''r''': '''BAAAA''',
    '''s''': '''BAAAB''',
    '''t''': '''BAABA''',
    '''u''': '''BAABB''',
    '''v''': '''BBBAB''',
    '''w''': '''BABAA''',
    '''x''': '''BABAB''',
    '''y''': '''BABBA''',
    '''z''': '''BABBB''',
    ''' ''': ''' ''',
}


__snake_case   							=						{value: key for key, value in encode_dict.items()}






def 		_A		(		_lowercase )					-> str:


     """simple docstring"""


     __UpperCamelCase =			''
     for letter in word.lower():
          if letter.isalpha() or letter == " ":
               encoded += encode_dict[letter]
          else:
               raise Exception('encode() accepts only letters of the alphabet and spaces' )
     return encoded






def 		_A		(		_lowercase )					-> str:


     """simple docstring"""


     if set(_lowercase ) - {"A", "B", " "} != set():
          raise Exception('decode() accepts only \'A\', \'B\' and spaces' )
     __UpperCamelCase =			''
     for word in coded.split():
          while len(_lowercase ) != 0:
               decoded += decode_dict[word[:5]]
               __UpperCamelCase =			word[5:]
          decoded += " "
     return decoded.strip()


if __name__ == "__main__":
    from doctest import testmod

    testmod()


