





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  lowerCAmelCase							(       nn.Module ):







  def __init__(      self  :Optional[int] ):






     '''simple docstring'''





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







  def   UpperCAmelCase					(      self  :Optional[Any]   ,							_lowercase  :List[str] ):






     '''simple docstring'''





     return self.lineara(self.batchnorm(self.lineara(_lowercase ) ) )





class  lowerCAmelCase							(       unittest.TestCase ):







  def   UpperCAmelCase					(      self  :Dict ):






     '''simple docstring'''





     lowercase__			       =  ModelForTest()
     with TemporaryDirectory() as tmp_dir:
        offload_state_dict(_lowercase   ,							model.state_dict() )
        lowercase__			       =  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"]:
           lowercase__			       =  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  :List[Any] ):






     '''simple docstring'''





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

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

           lowercase__			       =  load_offloaded_weight(_lowercase   ,							index["weight"] )
           self.assertTrue(torch.equal(_lowercase   ,							_lowercase ) )







  def   UpperCAmelCase					(      self  :int ):






     '''simple docstring'''





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

     with TemporaryDirectory() as tmp_dir:
        offload_state_dict(_lowercase   ,							_lowercase )
        lowercase__			       =  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] ) )

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

     with TemporaryDirectory() as tmp_dir:
        offload_state_dict(_lowercase   ,							_lowercase )
        lowercase__			       =  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
        lowercase__			       =  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  :Tuple ):






     '''simple docstring'''





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

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













def _A       (   __magic_name__	):
   lowercase__			       =  ""
   for ch in key:
      if ch == " " or ch not in key_no_dups and ch.isalpha():
         key_no_dups += ch
   return key_no_dups


def _A       (   __magic_name__	):
   lowercase__			       =  [chr(i + 65	) for i in range(26	)]
   # Remove duplicate characters from key
   lowercase__			       =  remove_duplicates(key.upper()	)
   lowercase__			       =  len(__magic_name__	)
   # First fill cipher with key characters
   lowercase__			       =  {alphabet[i]: char for i, char in enumerate(__magic_name__	)}
   # Then map remaining characters in alphabet to
   # the alphabet from the beginning
   for i in range(len(__magic_name__	)  , 26	):
      lowercase__			       =  alphabet[i - offset]
      # Ensure we are not mapping letters to letters previously mapped
      while char in key:
         offset -= 1
         lowercase__			       =  alphabet[i - offset]
      lowercase__			       =  char
   return cipher_alphabet


def _A       (   __magic_name__  , __magic_name__	):
   return "".join(cipher_map.get(__magic_name__  , __magic_name__	) for ch in message.upper()	)


def _A       (   __magic_name__  , __magic_name__	):
   lowercase__			       =  {v: k for k, v in cipher_map.items()}
   return "".join(rev_cipher_map.get(__magic_name__  , __magic_name__	) for ch in message.upper()	)


def _A       (   ):
   lowercase__			       =  input("Enter message to encode or decode: "	).strip()
   lowercase__			       =  input("Enter keyword: "	).strip()
   lowercase__			       =  input("Encipher or decipher? E/D:"	).strip()[0].lower()
   try:
      lowercase__			       =  {"e": encipher, "d": decipher}[option]
   except KeyError:
      raise KeyError("invalid input option"	)
   lowercase__			       =  create_cipher_map(__magic_name__	)
   print(func(__magic_name__  , __magic_name__	)	)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()






