


def 	_A				(lowerCAmelCase__  :List[Any]		)   ->  Optional[Any]:




     '''simple docstring'''



     if collection == []:
          return []

     # get some information about the collection
     _a			      =							len(__a		)
     _a			      =							max(__a		)
     _a			      =							min(__a		)

     # create the counting array
     _a			      =							coll_max + 1 - coll_min
     _a			      =							[0] * counting_arr_length

     # count how much a number appears in the collection
     for number in collection:
          counting_arr[number - coll_min] += 1

     # sum each position with it's predecessors. now, counting_arr[i] tells
     # us how many elements <= i has in the collection
     for i in range(1				,						__a		):
          _a			      =							counting_arr[i] + counting_arr[i - 1]

     # create the output collection
     _a			      =							[0] * coll_len

     # place the elements in the output, respecting the original order (stable
     # sort) from end to begin, updating counting_arr
     for i in reversed(range(0				,						__a		)		):
          _a			      =							collection[i]
          counting_arr[collection[i] - coll_min] -= 1

     return ordered






def 	_A				(lowerCAmelCase__  :Dict		)   ->  Optional[int]:




     '''simple docstring'''



     return "".join([chr(__a		) for i in counting_sort([ord(__a		) for c in string]		)]		)


if __name__ == "__main__":
 # Test string sort
 assert counting_sort_string("thisisthestring") == "eghhiiinrsssttt"

 a_					:    str          =    input("Enter numbers separated by a comma:\n").strip()
 a_					:    Optional[Any]          =    [int(item) for item in user_input.split(",")]
 print(counting_sort(unsorted))





'''simple docstring'''






from typing import TYPE_CHECKING

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


a_					:    int          =    {"configuration_vit": ["VIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTConfig", "ViTOnnxConfig"]}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_					:    List[Any]          =    ["ViTFeatureExtractor"]
 a_					:    Optional[int]          =    ["ViTImageProcessor"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_					:    Optional[int]          =    [
     "VIT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "ViTForImageClassification",
     "ViTForMaskedImageModeling",
     "ViTModel",
     "ViTPreTrainedModel",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_					:    Any          =    [
     "TFViTForImageClassification",
     "TFViTModel",
     "TFViTPreTrainedModel",
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_					:    Dict          =    [
     "FlaxViTForImageClassification",
     "FlaxViTModel",
     "FlaxViTPreTrainedModel",
 ]

if TYPE_CHECKING:
 from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_vit import ViTFeatureExtractor
  from .image_processing_vit import ViTImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_vit import (
      VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
      ViTForImageClassification,
      ViTForMaskedImageModeling,
      ViTModel,
      ViTPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
 import sys

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

