


"""simple docstring"""


import os
import shutil
from pathlib import Path
from typing import Optional, Union

import numpy as np
from huggingface_hub import hf_hub_download

from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging


if is_onnx_available():
	import onnxruntime as ort


UpperCamelCase    :					Any							   =   logging.get_logger(__name__)

UpperCamelCase    :					str							   =   {
    '''tensor(bool)''': np.bool_,
    '''tensor(int8)''': np.inta,
    '''tensor(uint8)''': np.uinta,
    '''tensor(int16)''': np.intaa,
    '''tensor(uint16)''': np.uintaa,
    '''tensor(int32)''': np.intaa,
    '''tensor(uint32)''': np.uintaa,
    '''tensor(int64)''': np.intaa,
    '''tensor(uint64)''': np.uintaa,
    '''tensor(float16)''': np.floataa,
    '''tensor(float)''': np.floataa,
    '''tensor(double)''': np.floataa,
}



class       lowerCamelCase__    :







						def __init__(				self :     List[str]      ,      _lowercase :     Dict=None      ,      **_lowercase :     int		):
								logger.info('`diffusers.OnnxRuntimeModel` is experimental and might change in the future.'		)
								A       							=			model
								A       							=			kwargs.get('model_save_dir'      ,      lowerCAmelCase__		)
								A       							=			kwargs.get('latest_model_name'      ,      lowerCAmelCase__		)







						def __call__(				self :     str      ,      **_lowercase :     Tuple		):
								A       							=			{k: np.array(lowerCAmelCase__		) for k, v in kwargs.items()}
								return self.model.run(lowerCAmelCase__      ,      lowerCAmelCase__		)







						@staticmethod
						def __a    (				_lowercase :     int      ,      _lowercase :     int=None      ,      _lowercase :     int=None		):
								if provider is None:
										logger.info('No onnxruntime provider specified, using CPUExecutionProvider'		)
										A       							=			"CPUExecutionProvider"

								return ort.InferenceSession(lowerCAmelCase__      ,      providers=[provider]      ,      sess_options=lowerCAmelCase__		)







						def __a    (				self :     Dict      ,      _lowercase :     Union[str, Any]      ,      _lowercase :     str = None      ,      **_lowercase :     str		):
								A       							=			file_name if file_name is not None else ONNX_WEIGHTS_NAME

								A       							=			self.model_save_dir.joinpath(self.latest_model_name		)
								A       							=			Path(lowerCAmelCase__		).joinpath(lowerCAmelCase__		)
								try:
										shutil.copyfile(lowerCAmelCase__      ,      lowerCAmelCase__		)
								except shutil.SameFileError:
										pass

								# copy external weights (for models >2GB)
								A       							=			self.model_save_dir.joinpath(lowerCAmelCase__		)
								if src_path.exists():
										A       							=			Path(lowerCAmelCase__		).joinpath(lowerCAmelCase__		)
										try:
												shutil.copyfile(lowerCAmelCase__      ,      lowerCAmelCase__		)
										except shutil.SameFileError:
												pass







						def __a    (				self :     int      ,      _lowercase :     Any      ,      **_lowercase :     List[Any]      ,      ):
								if os.path.isfile(lowerCAmelCase__		):
										logger.error(f'Provided path ({save_directory}) should be a directory, not a file'		)
										return

								os.makedirs(lowerCAmelCase__      ,      exist_ok=lowerCAmelCase__		)

								# saving model weights/files
								self._save_pretrained(lowerCAmelCase__      ,      **lowerCAmelCase__		)







						@classmethod
						def __a    (				cls :     str      ,      _lowercase :     Optional[int]      ,      _lowercase :     Optional[int] = None      ,      _lowercase :     List[Any] = None      ,      _lowercase :     List[str] = False      ,      _lowercase :     Tuple = None      ,      _lowercase :     Optional[Any] = None      ,      _lowercase :     List[str] = None      ,      _lowercase :     Union[str, Any] = None      ,      **_lowercase :     Tuple      ,      ):
								A       							=			file_name if file_name is not None else ONNX_WEIGHTS_NAME
								# load model from local directory
								if os.path.isdir(lowerCAmelCase__		):
										A       							=			OnnxRuntimeModel.load_model(
										    os.path.join(lowerCAmelCase__      ,      lowerCAmelCase__		)      ,      provider=lowerCAmelCase__      ,      sess_options=lowerCAmelCase__		)
										A       							=			Path(lowerCAmelCase__		)
								# load model from hub
								else:
										# download model
										A       							=			hf_hub_download(
										    repo_id=lowerCAmelCase__      ,      filename=lowerCAmelCase__      ,      use_auth_token=lowerCAmelCase__      ,      revision=lowerCAmelCase__      ,      cache_dir=lowerCAmelCase__      ,      force_download=lowerCAmelCase__      ,      )
										A       							=			Path(lowerCAmelCase__		).parent
										A       							=			Path(lowerCAmelCase__		).name
										A       							=			OnnxRuntimeModel.load_model(lowerCAmelCase__      ,      provider=lowerCAmelCase__      ,      sess_options=lowerCAmelCase__		)
								return cls(model=lowerCAmelCase__      ,      **lowerCAmelCase__		)







						@classmethod
						def __a    (				cls :     Optional[int]      ,      _lowercase :     List[Any]      ,      _lowercase :     str = True      ,      _lowercase :     List[str] = None      ,      _lowercase :     List[Any] = None      ,      **_lowercase :     List[Any]      ,      ):
								A       							=			None
								if len(str(lowerCAmelCase__		).split('@'		)		) == 2:
										A       							=			model_id.split('@'		)

								return cls._from_pretrained(
								    model_id=lowerCAmelCase__      ,      revision=lowerCAmelCase__      ,      cache_dir=lowerCAmelCase__      ,      force_download=lowerCAmelCase__      ,      use_auth_token=lowerCAmelCase__      ,      **lowerCAmelCase__      ,      )












"""simple docstring"""




import math






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       list       ,			_lowercase		:       int = 0       ,			_lowercase		:       int = 0   )					->list:






	'''simple docstring'''






	a :						Optional[Any]      =							end or len(_lowercase   )
	for i in range(_lowercase       ,			_lowercase   ):
		a :						List[str]      =							i
		a :						Any      =							array[i]
		while temp_index != start and temp_index_value < array[temp_index - 1]:
			a :						Optional[Any]      =							array[temp_index - 1]
			temp_index -= 1
		a :						Any      =							temp_index_value
	return array






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       list       ,			_lowercase		:       int       ,			_lowercase		:       int   )					->None:  # Max Heap






	'''simple docstring'''






	a :						Tuple      =							index
	a :						List[Any]      =							2 * index + 1  # Left Node
	a :						Dict      =							2 * index + 2  # Right Node

	if left_index < heap_size and array[largest] < array[left_index]:
		a :						Dict      =							left_index

	if right_index < heap_size and array[largest] < array[right_index]:
		a :						int      =							right_index

	if largest != index:
		a,			a :						List[Any]      =							array[largest], array[index]
		heapify(_lowercase       ,			_lowercase       ,			_lowercase   )






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       list   )					->list:






	'''simple docstring'''






	a :						int      =							len(_lowercase   )

	for i in range(n // 2       ,			-1       ,			-1   ):
		heapify(_lowercase       ,			_lowercase       ,			_lowercase   )

	for i in range(n - 1       ,			0       ,			-1   ):
		a,			a :						str      =							array[0], array[i]
		heapify(_lowercase       ,			0       ,			_lowercase   )

	return array






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       list       ,			_lowercase		:       int       ,			_lowercase		:       int       ,			_lowercase		:       int   )					->int:






	'''simple docstring'''






	if (array[first_index] > array[middle_index]) != (
	    array[first_index] > array[last_index]
	):
		return array[first_index]
	elif (array[middle_index] > array[first_index]) != (
	    array[middle_index] > array[last_index]
	):
		return array[middle_index]
	else:
		return array[last_index]






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       list       ,			_lowercase		:       int       ,			_lowercase		:       int       ,			_lowercase		:       int   )					->int:






	'''simple docstring'''






	a :						List[Any]      =							low
	a :						int      =							high
	while True:
		while array[i] < pivot:
			i += 1
		j -= 1
		while pivot < array[j]:
			j -= 1
		if i >= j:
			return i
		a,			a :						Union[str, Any]      =							array[j], array[i]
		i += 1






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       list   )					->list:






	'''simple docstring'''






	if len(_lowercase   ) == 0:
		return array
	a :						Tuple      =							2 * math.ceil(math.loga(len(_lowercase   )   )   )
	a :						List[str]      =							16
	return intro_sort(_lowercase       ,			0       ,			len(_lowercase   )       ,			_lowercase       ,			_lowercase   )






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       list       ,			_lowercase		:       int       ,			_lowercase		:       int       ,			_lowercase		:       int       ,			_lowercase		:       int   )					->list:






	'''simple docstring'''






	while end - start > size_threshold:
		if max_depth == 0:
			return heap_sort(_lowercase   )
		max_depth -= 1
		a :						List[str]      =							median_of_a(_lowercase       ,			_lowercase       ,			start + ((end - start) // 2) + 1       ,			end - 1   )
		a :						Tuple      =							partition(_lowercase       ,			_lowercase       ,			_lowercase       ,			_lowercase   )
		intro_sort(_lowercase       ,			_lowercase       ,			_lowercase       ,			_lowercase       ,			_lowercase   )
		a :						Union[str, Any]      =							p
	return insertion_sort(_lowercase       ,			_lowercase       ,			_lowercase   )


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		a		:					Optional[int]	      =     input('''Enter numbers separated by a comma : ''').strip()
		a		:					List[str]	      =     [float(item) for item in user_input.split(''',''')]
		print(sort(unsorted))


