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   :					Optional[Any]      )					->				Any:



												'''simple docstring'''

												super().__init__()
												SCREAMING_SNAKE_CASE    			=       nn.Linear(3	,							4      )
												SCREAMING_SNAKE_CASE    			=       nn.BatchNormad(4      )
												SCREAMING_SNAKE_CASE    			=       nn.Linear(4	,							5      )





							def 	__snake_case(						self   :					Tuple	,							_UpperCamelCase   :					List[Any]      )					->				Optional[Any]:



												'''simple docstring'''

												return self.lineara(self.batchnorm(self.lineara(_UpperCamelCase      )      )      )



class 						lowercase    (     unittest.TestCase     ):




							def 	__snake_case(						self   :					Optional[int]      )					->				Any:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       ModelForTest()
												with TemporaryDirectory() as tmp_dir:
																	offload_state_dict(_UpperCamelCase	,							model.state_dict()      )
																	SCREAMING_SNAKE_CASE    			=       os.path.join(_UpperCamelCase	,							"index.json"      )
																	self.assertTrue(os.path.isfile(_UpperCamelCase      )      )
																	# TODO: add tests on what is inside the index

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




							def 	__snake_case(						self   :					Any      )					->				int:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       [torch.floataa, torch.floataa, torch.bfloataa]

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

																						SCREAMING_SNAKE_CASE    			=       load_offloaded_weight(_UpperCamelCase	,							index["weight"]      )
																						self.assertTrue(torch.equal(_UpperCamelCase	,							_UpperCamelCase      )      )




							def 	__snake_case(						self   :					Dict      )					->				Any:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       ModelForTest()
												SCREAMING_SNAKE_CASE    			=       model.state_dict()
												SCREAMING_SNAKE_CASE    			=       {k: v for k, v in state_dict.items() if "linear2" not in k}
												SCREAMING_SNAKE_CASE    			=       {k: v for k, v in state_dict.items() if "linear2" in k}

												with TemporaryDirectory() as tmp_dir:
																	offload_state_dict(_UpperCamelCase	,							_UpperCamelCase      )
																	SCREAMING_SNAKE_CASE    			=       OffloadedWeightsLoader(state_dict=_UpperCamelCase	,							save_folder=_UpperCamelCase      )

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

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

												with TemporaryDirectory() as tmp_dir:
																	offload_state_dict(_UpperCamelCase	,							_UpperCamelCase      )
																	SCREAMING_SNAKE_CASE    			=       OffloadedWeightsLoader(state_dict=_UpperCamelCase	,							save_folder=_UpperCamelCase      )

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

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

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





							def 	__snake_case(						self   :					List[Any]      )					->				Tuple:



												'''simple docstring'''

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

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





def 	__lowerCamelCase							(UpperCAmelCase__     :							int  ):
					assert isinstance(UpperCAmelCase__      , UpperCAmelCase__  ), F"The input value of [n={number}] is not an integer"

					if number == 1:
										return 2
					elif number < 1:
										SCREAMING_SNAKE_CASE    			=       F"The input value of [n={number}] has to be > 0"
										raise ValueError(UpperCAmelCase__  )
					else:
										SCREAMING_SNAKE_CASE    			=       sylvester(number - 1  )
										SCREAMING_SNAKE_CASE    			=       num - 1
										SCREAMING_SNAKE_CASE    			=       num
										return lower * upper + 1


if __name__ == "__main__":
							print(f"""The 8th number in Sylvester's sequence: {sylvester(8)}""")




