

'''simple docstring'''






from typing import TYPE_CHECKING

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


lowerCAmelCase__      		=			{
    """configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MobileViTConfig""", """MobileViTOnnxConfig"""],
}

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

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

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase__      		=			[
     """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

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




'''simple docstring'''






import random
from typing import Any


def 	_A  (					A__   ):






 """simple docstring"""



 for _ in range(len(A__   )   ):
  __lowercase													=				random.randint(0  ,       len(A__   ) - 1   )
  __lowercase													=				random.randint(0  ,       len(A__   ) - 1   )
  __lowercase						,			__lowercase													=				data[b], data[a]
 return data


if __name__ == "__main__":
 lowerCAmelCase__      		=			[0, 1, 2, 3, 4, 5, 6, 7]
 lowerCAmelCase__      		=			['''python''', '''says''', '''hello''', '''!''']
 print('''Fisher-Yates Shuffle:''')
 print('''List''', integers, strings)
 print('''FY Shuffle''', fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))

