




'''simple docstring'''





import os
import unittest
from tempfile import TemporaryDirectory

import torch
import torch.nn as nn

from accelerate.utils import (
    OffloadedWeightsLoader,
    extract_submodules_state_dict,
    load_offloaded_weight,
    offload_state_dict,
    offload_weight,
)




class 					snake_case__							(nn.Module     ):
				"""simple docstring"""



				def __init__(   self       :  str							)      ->  Dict:
							super().__init__()
							a					=    nn.Linear(3      ,   4							)
							a					=    nn.BatchNormad(4							)
							a					=    nn.Linear(4      ,   5							)





				def 							__UpperCAmelCase							(   self       :  List[Any]      ,   __lowerCamelCase       :  int							)      ->  List[str]:
							return self.lineara(self.batchnorm(self.lineara(__lowerCamelCase							)							)							)




class 					snake_case__							(unittest.TestCase     ):
				"""simple docstring"""



				def 							__UpperCAmelCase							(   self       :  str							)      ->  List[str]:
							a					=    ModelForTest()
							with TemporaryDirectory() as tmp_dir:
										offload_state_dict(__lowerCamelCase      ,   model.state_dict()							)
										a					=    os.path.join(__lowerCamelCase      ,   "index.json"							)
										self.assertTrue(os.path.isfile(__lowerCamelCase							)							)
										# TODO: add tests on what is inside the index

										for key in ["linear1.weight", "linear1.bias", "linear2.weight", "linear2.bias"]:
													a					=    os.path.join(__lowerCamelCase      ,   f"""{key}.dat"""							)
													self.assertTrue(os.path.isfile(__lowerCamelCase							)							)
													# TODO: add tests on the fact weights are properly loaded





				def 							__UpperCAmelCase							(   self       :  List[str]							)      ->  Optional[Any]:
							a					=    [torch.floataa, torch.floataa, torch.bfloataa]

							for dtype in dtypes:
										a					=    torch.randn(2      ,   3      ,   dtype=__lowerCamelCase							)
										with TemporaryDirectory() as tmp_dir:
													a					=    offload_weight(__lowerCamelCase      ,   "weight"      ,   __lowerCamelCase      ,   {}							)
													a					=    os.path.join(__lowerCamelCase      ,   "weight.dat"							)
													self.assertTrue(os.path.isfile(__lowerCamelCase							)							)
													self.assertDictEqual(__lowerCamelCase      ,   {"weight": {"shape": [2, 3], "dtype": str(__lowerCamelCase							).split("."							)[1]}}							)

													a					=    load_offloaded_weight(__lowerCamelCase      ,   index["weight"]							)
													self.assertTrue(torch.equal(__lowerCamelCase      ,   __lowerCamelCase							)							)





				def 							__UpperCAmelCase							(   self       :  Union[str, Any]							)      ->  Any:
							a					=    ModelForTest()
							a					=    model.state_dict()
							a					=    {k: v for k, v in state_dict.items() if "linear2" not in k}
							a					=    {k: v for k, v in state_dict.items() if "linear2" in k}

							with TemporaryDirectory() as tmp_dir:
										offload_state_dict(__lowerCamelCase      ,   __lowerCamelCase							)
										a					=    OffloadedWeightsLoader(state_dict=__lowerCamelCase      ,   save_folder=__lowerCamelCase							)

										# Every key is there with the right value
										self.assertEqual(sorted(__lowerCamelCase							)      ,   sorted(state_dict.keys()							)							)
										for key, param in state_dict.items():
													self.assertTrue(torch.allclose(__lowerCamelCase      ,   weight_map[key]							)							)

							a					=    {k: v for k, v in state_dict.items() if "weight" in k}
							a					=    {k: v for k, v in state_dict.items() if "weight" not in k}

							with TemporaryDirectory() as tmp_dir:
										offload_state_dict(__lowerCamelCase      ,   __lowerCamelCase							)
										a					=    OffloadedWeightsLoader(state_dict=__lowerCamelCase      ,   save_folder=__lowerCamelCase							)

										# Every key is there with the right value
										self.assertEqual(sorted(__lowerCamelCase							)      ,   sorted(state_dict.keys()							)							)
										for key, param in state_dict.items():
													self.assertTrue(torch.allclose(__lowerCamelCase      ,   weight_map[key]							)							)

							with TemporaryDirectory() as tmp_dir:
										offload_state_dict(__lowerCamelCase      ,   __lowerCamelCase							)
										# Duplicates are removed
										a					=    OffloadedWeightsLoader(state_dict=__lowerCamelCase      ,   save_folder=__lowerCamelCase							)

										# Every key is there with the right value
										self.assertEqual(sorted(__lowerCamelCase							)      ,   sorted(state_dict.keys()							)							)
										for key, param in state_dict.items():
													self.assertTrue(torch.allclose(__lowerCamelCase      ,   weight_map[key]							)							)





				def 							__UpperCAmelCase							(   self       :  Union[str, Any]							)      ->  str:
							a					=    {"a.1": 0, "a.10": 1, "a.2": 2}
							a					=    extract_submodules_state_dict(__lowerCamelCase      ,   ["a.1", "a.2"]							)
							self.assertDictEqual(__lowerCamelCase      ,   {"a.1": 0, "a.2": 2}							)

							a					=    {"a.1.a": 0, "a.10.a": 1, "a.2.a": 2}
							a					=    extract_submodules_state_dict(__lowerCamelCase      ,   ["a.1", "a.2"]							)
							self.assertDictEqual(__lowerCamelCase      ,   {"a.1.a": 0, "a.2.a": 2}							)












def     __magic_name__       (				A	:      list     ):






			'''simple docstring'''







			for i in range(len(A     ) - 1,						0,						-1     ):
						a					=    False

						for j in range(A,						0,						-1     ):
									if unsorted[j] < unsorted[j - 1]:
												a					,	a					=    unsorted[j - 1], unsorted[j]
												a					=    True

						for j in range(A     ):
									if unsorted[j] > unsorted[j + 1]:
												a					,	a					=    unsorted[j + 1], unsorted[j]
												a					=    True

						if not swapped:
									break
			return unsorted


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		__lowerCAmelCase	:       Tuple     =	input('Enter numbers separated by a comma:\n').strip()
		__lowerCAmelCase	:       List[Any]     =	[int(item) for item in user_input.split(',')]
		print(F'''{cocktail_shaker_sort(unsorted) = }''')






