






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 					A__     (     nn.Module ):

     '''simple docstring'''






     def __init__( self      :    List[Any] ):






           """simple docstring"""




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







     def   _SCREAMING_SNAKE_CASE     ( self      :    Dict   ,						_SCREAMING_SNAKE_CASE      :    Union[str, Any] ):






           """simple docstring"""




           return self.lineara(self.batchnorm(self.lineara(_SCREAMING_SNAKE_CASE ) ) )





class 					A__     (     unittest.TestCase ):

     '''simple docstring'''






     def   _SCREAMING_SNAKE_CASE     ( self      :    Any ):






           """simple docstring"""




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

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







     def   _SCREAMING_SNAKE_CASE     ( self      :    str ):






           """simple docstring"""




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

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

                       UpperCamelCase					       =  load_offloaded_weight(_SCREAMING_SNAKE_CASE   ,						index['weight'] )
                       self.assertTrue(torch.equal(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE ) )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Optional[int] ):






           """simple docstring"""




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

           with TemporaryDirectory() as tmp_dir:
                 offload_state_dict(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )
                 UpperCamelCase					       =  OffloadedWeightsLoader(state_dict=_SCREAMING_SNAKE_CASE   ,						save_folder=_SCREAMING_SNAKE_CASE )

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

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

           with TemporaryDirectory() as tmp_dir:
                 offload_state_dict(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )
                 UpperCamelCase					       =  OffloadedWeightsLoader(state_dict=_SCREAMING_SNAKE_CASE   ,						save_folder=_SCREAMING_SNAKE_CASE )

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

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

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







     def   _SCREAMING_SNAKE_CASE     ( self      :    str ):






           """simple docstring"""




           UpperCamelCase					       =  {'a.1': 0, 'a.10': 1, 'a.2': 2}
           UpperCamelCase					       =  extract_submodules_state_dict(_SCREAMING_SNAKE_CASE   ,						['a.1', 'a.2'] )
           self.assertDictEqual(_SCREAMING_SNAKE_CASE   ,						{'a.1': 0, 'a.2': 2} )

           UpperCamelCase					       =  {'a.1.a': 0, 'a.10.a': 1, 'a.2.a': 2}
           UpperCamelCase					       =  extract_submodules_state_dict(_SCREAMING_SNAKE_CASE   ,						['a.1', 'a.2'] )
           self.assertDictEqual(_SCREAMING_SNAKE_CASE   ,						{'a.1.a': 0, 'a.2.a': 2} )











from collections.abc import Sequence
def 		lowercase__  (				_UpperCamelCase       ,							_UpperCamelCase) ->			float:
      """simple docstring"""

      return sum(c * (x**i) for i, c in enumerate(_UpperCamelCase))
def 		lowercase__  (				_UpperCamelCase       ,							_UpperCamelCase) ->			float:
      """simple docstring"""

      UpperCamelCase					       =  0.0
      for coeff in reversed(_UpperCamelCase):
            UpperCamelCase					       =  result * x + coeff
      return result


if __name__ == "__main__":
       __magic_name__   :  Union[str, Any]        =							(0.0, 0.0, 5.0, 9.3, 7.0)
       __magic_name__   :  List[str]        =							10.0
       print(evaluate_poly(poly, x))
       print(horner(poly, x))



