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        lowercase_   (					nn.Module		):



							def __init__(						self    ):
													super().__init__()
													_snake_case						:					int    =   nn.Linear(3				,    4    )
													_snake_case						:					int    =   nn.BatchNormad(4    )
													_snake_case						:					int    =   nn.Linear(4				,    5    )



							def 	UpperCamelCase	(						self				,    lowercase_    ):
													return self.lineara(self.batchnorm(self.lineara(lowercase_    )    )    )




class        lowercase_   (					unittest.TestCase		):



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Optional[int]    =   ModelForTest()
													with TemporaryDirectory() as tmp_dir:
																			offload_state_dict(lowercase_				,    model.state_dict()    )
																			_snake_case						:					List[str]    =   os.path.join(lowercase_				,    "index.json"    )
																			self.assertTrue(os.path.isfile(lowercase_    )    )
																			# TODO: add tests on what is inside the index

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



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Any    =   [torch.floataa, torch.floataa, torch.bfloataa]

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

																									_snake_case						:					Dict    =   load_offloaded_weight(lowercase_				,    index["weight"]    )
																									self.assertTrue(torch.equal(lowercase_				,    lowercase_    )    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Dict    =   ModelForTest()
													_snake_case						:					int    =   model.state_dict()
													_snake_case						:					int    =   {k: v for k, v in state_dict.items() if "linear2" not in k}
													_snake_case						:					Tuple    =   {k: v for k, v in state_dict.items() if "linear2" in k}

													with TemporaryDirectory() as tmp_dir:
																			offload_state_dict(lowercase_				,    lowercase_    )
																			_snake_case						:					Tuple    =   OffloadedWeightsLoader(state_dict=lowercase_				,    save_folder=lowercase_    )

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

													_snake_case						:					Union[str, Any]    =   {k: v for k, v in state_dict.items() if "weight" in k}
													_snake_case						:					str    =   {k: v for k, v in state_dict.items() if "weight" not in k}

													with TemporaryDirectory() as tmp_dir:
																			offload_state_dict(lowercase_				,    lowercase_    )
																			_snake_case						:					Any    =   OffloadedWeightsLoader(state_dict=lowercase_				,    save_folder=lowercase_    )

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

													with TemporaryDirectory() as tmp_dir:
																			offload_state_dict(lowercase_				,    lowercase_    )
																			# Duplicates are removed
																			_snake_case						:					int    =   OffloadedWeightsLoader(state_dict=lowercase_				,    save_folder=lowercase_    )

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



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Any    =   {"a.1": 0, "a.10": 1, "a.2": 2}
													_snake_case						:					Optional[Any]    =   extract_submodules_state_dict(lowercase_				,    ["a.1", "a.2"]    )
													self.assertDictEqual(lowercase_				,    {"a.1": 0, "a.2": 2}    )

													_snake_case						:					Tuple    =   {"a.1.a": 0, "a.10.a": 1, "a.2.a": 2}
													_snake_case						:					str    =   extract_submodules_state_dict(lowercase_				,    ["a.1", "a.2"]    )
													self.assertDictEqual(lowercase_				,    {"a.1.a": 0, "a.2.a": 2}    )
def  snake_case						()	->	Dict:

						'''simple docstring'''



						_snake_case						:					List[str]    =   0
						for i in range(1 ,      1_001						):
												total += i**i
						return str(__lowercase						)[-10:]


if __name__ == "__main__":
				print(solution())