




'''simple docstring'''







from __future__ import annotations

from random import randrange



def 					lowerCamelCase__							(			__lowercase							):
     if len(__lowercase							) < 2:
          return collection
     snake_case :			int					   = randrange(len(__lowercase							)							)  # Use random element as pivot
     snake_case :			List[Any]					   = collection[pivot_index]
     snake_case :			list[int]					   = []  # All elements greater than pivot
     snake_case :			list[int]					   = []  # All elements less than or equal to pivot

     for element in collection[:pivot_index]:
          (greater if element > pivot else lesser).append(__lowercase							)

     for element in collection[pivot_index + 1 :]:
          (greater if element > pivot else lesser).append(__lowercase							)

     return [*quick_sort(__lowercase							), pivot, *quick_sort(__lowercase							)]


if __name__ == "__main__":
      lowercase			:      str			=					input("""Enter numbers separated by a comma:\n""").strip()
      lowercase			:      int			=					[int(item) for item in user_input.split(""",""")]
      print(quick_sort(unsorted))









'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


lowercase			:      Tuple			=					{"""configuration_bert_generation""": ["""BertGenerationConfig"""]}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase			:      Tuple			=					["""BertGenerationTokenizer"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase			:      List[Any]			=					[
          """BertGenerationDecoder""",
          """BertGenerationEncoder""",
          """BertGenerationPreTrainedModel""",
          """load_tf_weights_in_bert_generation""",
      ]


if TYPE_CHECKING:
      from .configuration_bert_generation import BertGenerationConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_bert_generation import BertGenerationTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_bert_generation import (
                BertGenerationDecoder,
                BertGenerationEncoder,
                BertGenerationPreTrainedModel,
                load_tf_weights_in_bert_generation,
            )

else:
      import sys

      lowercase			:      Optional[Any]			=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



