



'''simple docstring'''

from typing import TYPE_CHECKING

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


snake_case_     :   Tuple			=     {
    """configuration_swiftformer""": [
        """SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SwiftFormerConfig""",
        """SwiftFormerOnnxConfig""",
    ]
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_     :   Optional[Any]			=     [
	    """SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """SwiftFormerForImageClassification""",
	    """SwiftFormerModel""",
	    """SwiftFormerPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_swiftformer import (
	    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    SwiftFormerConfig,
	    SwiftFormerOnnxConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_swiftformer import (
		    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    SwiftFormerForImageClassification,
		    SwiftFormerModel,
		    SwiftFormerPreTrainedModel,
		)

else:
	import sys

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









'''simple docstring'''

from random import randint
from tempfile import TemporaryFile

import numpy as np






def       __lowercase  (_SCREAMING_SNAKE_CASE      :List[str]    ,	_SCREAMING_SNAKE_CASE      :Any    ,	_SCREAMING_SNAKE_CASE      :str       ):
				SCREAMING_SNAKE_CASE  :						int      					= 0
				if start < end:
								SCREAMING_SNAKE_CASE  :						Optional[int]      					= randint(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE       )
								SCREAMING_SNAKE_CASE  :						List[str]      					= a[end]
								SCREAMING_SNAKE_CASE  :						List[str]      					= a[pivot]
								SCREAMING_SNAKE_CASE  :						Dict      					= temp

								SCREAMING_SNAKE_CASE					,					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= _in_place_partition(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE       )
								count += _in_place_quick_sort(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE    ,	p - 1       )
								count += _in_place_quick_sort(_SCREAMING_SNAKE_CASE    ,	p + 1    ,	_SCREAMING_SNAKE_CASE       )
				return count






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

				SCREAMING_SNAKE_CASE  :						List[Any]      					= a[new_pivot_index + 1]
				SCREAMING_SNAKE_CASE  :						Any      					= a[end]
				SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= temp
				return new_pivot_index + 1, count


snake_case_			=     TemporaryFile()
snake_case_			=     100  # 1000 elements are to be sorted


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


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

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




print(z)




