




from typing import TYPE_CHECKING

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


_UpperCAmelCase	:						Tuple			=     {
    "configuration_clip": [
        "CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "CLIPConfig",
        "CLIPOnnxConfig",
        "CLIPTextConfig",
        "CLIPVisionConfig",
    ],
    "processing_clip": ["CLIPProcessor"],
    "tokenization_clip": ["CLIPTokenizer"],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase	:						List[str]			=     ["CLIPTokenizerFast"]

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase	:						List[Any]			=     ["CLIPFeatureExtractor"]
     _UpperCAmelCase	:						str			=     ["CLIPImageProcessor"]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase	:						Dict			=     [
         "CLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
         "CLIPModel",
         "CLIPPreTrainedModel",
         "CLIPTextModel",
         "CLIPTextModelWithProjection",
         "CLIPVisionModel",
         "CLIPVisionModelWithProjection",
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase	:						List[str]			=     [
         "TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TFCLIPModel",
         "TFCLIPPreTrainedModel",
         "TFCLIPTextModel",
         "TFCLIPVisionModel",
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase	:						Optional[int]			=     [
         "FlaxCLIPModel",
         "FlaxCLIPPreTrainedModel",
         "FlaxCLIPTextModel",
         "FlaxCLIPTextPreTrainedModel",
         "FlaxCLIPVisionModel",
         "FlaxCLIPVisionPreTrainedModel",
     ]


if TYPE_CHECKING:
     from .configuration_clip import (
         CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
         CLIPConfig,
         CLIPOnnxConfig,
         CLIPTextConfig,
         CLIPVisionConfig,
     )
     from .processing_clip import CLIPProcessor
     from .tokenization_clip import CLIPTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_clip_fast import CLIPTokenizerFast

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_clip import CLIPFeatureExtractor
          from .image_processing_clip import CLIPImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_clip import (
              CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
              CLIPModel,
              CLIPPreTrainedModel,
              CLIPTextModel,
              CLIPTextModelWithProjection,
              CLIPVisionModel,
              CLIPVisionModelWithProjection,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_clip import (
              TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFCLIPModel,
              TFCLIPPreTrainedModel,
              TFCLIPTextModel,
              TFCLIPVisionModel,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_clip import (
              FlaxCLIPModel,
              FlaxCLIPPreTrainedModel,
              FlaxCLIPTextModel,
              FlaxCLIPTextPreTrainedModel,
              FlaxCLIPVisionModel,
              FlaxCLIPVisionPreTrainedModel,
          )


else:
     import sys

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









import string



def       UpperCAmelCase__  (     lowerCamelCase   ):
  lowercase    :Optional[int]      	=						""
  for i in sequence:
    lowercase    :Optional[Any]      	=						ord(lowerCamelCase   )
    if 65 <= extract <= 90:
      output += chr(155 - extract   )
    elif 97 <= extract <= 122:
      output += chr(219 - extract   )
    else:
      output += i
  return output



def       UpperCAmelCase__  (     lowerCamelCase   ):
  lowercase    :Union[str, Any]      	=						string.ascii_letters
  lowercase    :Dict      	=						string.ascii_lowercase[::-1] + string.ascii_uppercase[::-1]
  return "".join(
      letters_reversed[letters.index(lowerCamelCase   )] if c in letters else c for c in sequence   )



def       UpperCAmelCase__  (     ):
  from timeit import timeit

  print("Running performance benchmarks..."   )
  lowercase    :Dict      	=						"from string import printable ; from __main__ import atbash, atbash_slow"
  print(F"> atbash_slow(): {timeit('atbash_slow(printable)',			setup=lowerCamelCase   )} seconds"   )
  print(F">      atbash(): {timeit('atbash(printable)',			setup=lowerCamelCase   )} seconds"   )


if __name__ == "__main__":
     for example in ("ABCDEFGH", "123GGjj", "testStringtest", "with space"):
          print(f'''{example} encrypted in atbash: {atbash(example)}''')
     benchmark()



