






"""simple docstring"""

from typing import Union

import fire
import torch
from tqdm import tqdm

def 		__lowerCamelCase	(  __UpperCamelCase      ,       __UpperCamelCase = "cpu"      ,       __UpperCamelCase = None       )						->    None:

		"""simple docstring"""







		lowerCAmelCase_   :							List[Any]									=			torch.load(__UpperCamelCase      ,       map_location=__UpperCamelCase       )
		for k, v in tqdm(state_dict.items()       ):
				if not isinstance(__UpperCamelCase      ,       torch.Tensor       ):
						raise TypeError("FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin"       )
				lowerCAmelCase_   :							int									=			v.half()
		if save_path is None:  # overwrite src_path
				lowerCAmelCase_   :							Tuple									=			src_path
		torch.save(__UpperCamelCase      ,       __UpperCamelCase       )


if __name__ == "__main__":
					fire.Fire(convert)








"""simple docstring"""

from random import randint
from tempfile import TemporaryFile

import numpy as np

def 		__lowerCamelCase	(  __UpperCamelCase      ,       __UpperCamelCase      ,       __UpperCamelCase       )						->    Dict:

		"""simple docstring"""







		lowerCAmelCase_   :							Union[str, Any]									=			0
		if start < end:
				lowerCAmelCase_   :							Dict									=			randint(__UpperCamelCase      ,       __UpperCamelCase       )
				lowerCAmelCase_   :							List[str]									=			a[end]
				lowerCAmelCase_   :							List[str]									=			a[pivot]
				lowerCAmelCase_   :							Any									=			temp

				lowerCAmelCase_				,	lowerCAmelCase_   :							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 		__lowerCamelCase	(  __UpperCamelCase      ,       __UpperCamelCase      ,       __UpperCamelCase       )						->    str:

		"""simple docstring"""







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

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


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


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


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

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



print(z)
