
from random import randint
from tempfile import TemporaryFile

import numpy as np


def 				SCREAMING_SNAKE_CASE_   (      UpperCamelCase__			,		UpperCamelCase__			,		UpperCamelCase__		):
      UpperCamelCase__     : int											=					0
      if start < end:
            UpperCamelCase__     : int											=					randint(UpperCamelCase__			,		UpperCamelCase__		)
            UpperCamelCase__     : Optional[Any]											=					a[end]
            UpperCamelCase__     : List[Any]											=					a[pivot]
            UpperCamelCase__     : Union[str, Any]											=					temp

            UpperCamelCase__					,UpperCamelCase__     : Union[str, Any]											=					_in_place_partition(UpperCamelCase__			,		UpperCamelCase__			,		UpperCamelCase__		)
            count += _in_place_quick_sort(UpperCamelCase__			,		UpperCamelCase__			,		p - 1		)
            count += _in_place_quick_sort(UpperCamelCase__			,		p + 1			,		UpperCamelCase__		)
      return count


def 				SCREAMING_SNAKE_CASE_   (      UpperCamelCase__			,		UpperCamelCase__			,		UpperCamelCase__		):
      UpperCamelCase__     : Optional[Any]											=					0
      UpperCamelCase__     : Optional[Any]											=					randint(UpperCamelCase__			,		UpperCamelCase__		)
      UpperCamelCase__     : List[Any]											=					a[end]
      UpperCamelCase__     : Optional[Any]											=					a[pivot]
      UpperCamelCase__     : int											=					temp
      UpperCamelCase__     : int											=					start - 1
      for index in range(UpperCamelCase__			,		UpperCamelCase__		):
            count += 1
            if a[index] < a[end]:  # check if current val is less than pivot value
                  UpperCamelCase__     : Dict											=					new_pivot_index + 1
                  UpperCamelCase__     : List[Any]											=					a[new_pivot_index]
                  UpperCamelCase__     : Optional[int]											=					a[index]
                  UpperCamelCase__     : Any											=					temp

      UpperCamelCase__     : int											=					a[new_pivot_index + 1]
      UpperCamelCase__     : int											=					a[end]
      UpperCamelCase__     : Any											=					temp
      return new_pivot_index + 1, count


lowerCamelCase  =TemporaryFile()
lowerCamelCase  =1_0_0  # 1000 elements are to be sorted


lowerCamelCase ,  lowerCamelCase  =0, 1  # mean and standard deviation
lowerCamelCase  =np.random.normal(mu, sigma, p)
np.save(outfile, X)
print("The array is")
print(X)


outfile.seek(0)  # using the same array
lowerCamelCase  =np.load(outfile)
lowerCamelCase  =len(M) - 1
lowerCamelCase  =_in_place_quick_sort(M, 0, r)

print(
    "No of Comparisons for 100 elements selected from a standard normal distribution"
    "is :"
)
print(z)




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase  ={
    "configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
    "tokenization_luke": ["LukeTokenizer"],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase  =[
        "LUKE_PRETRAINED_MODEL_ARCHIVE_LIST",
        "LukeForEntityClassification",
        "LukeForEntityPairClassification",
        "LukeForEntitySpanClassification",
        "LukeForMultipleChoice",
        "LukeForQuestionAnswering",
        "LukeForSequenceClassification",
        "LukeForTokenClassification",
        "LukeForMaskedLM",
        "LukeModel",
        "LukePreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
    from .tokenization_luke import LukeTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_luke import (
            LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
            LukeForEntityClassification,
            LukeForEntityPairClassification,
            LukeForEntitySpanClassification,
            LukeForMaskedLM,
            LukeForMultipleChoice,
            LukeForQuestionAnswering,
            LukeForSequenceClassification,
            LukeForTokenClassification,
            LukeModel,
            LukePreTrainedModel,
        )

else:
    import sys

    lowerCamelCase  =_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


