
'''simple docstring'''





import os
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
 import torch

 from transformers import GPTaLMHeadModel


@require_torch
@require_sentencepiece
@require_tokenizers
class 	UpperCamelCase__					(      unittest.TestCase	):






 @slow
 @unittest.skip('Model is not available.'     )
 def 		lowercase_  (     self					:Any     )			->     Tuple:







       '''simple docstring'''



       __A    		=     'nvidia/megatron-gpt2-345m/'
       if "MYDIR" in os.environ:
             __A    		=     os.path.join(os.environ['MYDIR']		,			lowercase_     )
       __A    		=     GPTaLMHeadModel.from_pretrained(lowercase_     )
       model.to(lowercase_     )
       model.half()

       __A    		=     torch.tensor(
           [[101, 7_110, 1_005, 1_056, 2_023, 11_333, 17_413, 1_029, 102]]		,			device=lowercase_		,			dtype=torch.long		,			)

       with torch.no_grad():
             __A    		=     model(lowercase_     ).logits

       __A    		=     torch.Size((1, 9, 50_257)     )
       self.assertEqual(output.shape		,			lowercase_     )

       __A    		=     torch.tensor(
           [
               4.9_414,
               -0.2_920,
               -1.2_148,
               -4.0_273,
               -0.5_161,
               -5.2_109,
               -1.2_412,
               -1.8_301,
               -1.7_734,
               -4.7_148,
               -0.2_317,
               -1.0_811,
               -2.1_777,
               0.4_141,
               -3.7_969,
               -4.0_586,
               -2.5_332,
               -3.3_809,
               4.3_867,
           ]		,			device=lowercase_		,			dtype=torch.half		,			)

       for i in range(19     ):
             __A		, __A    		=     8 * i // 17, 2_792 * i  # along the diagonal
             __A		, __A    		=     output[0, r, c], expected_diag[i]
             __A    		=     F'row={r} col={c} computed={computed} expected={expected}'
             self.assertAlmostEqual(lowercase_		,			lowercase_		,			delta=1E-4		,			msg=lowercase_     )








'''simple docstring'''





import itertools
from pathlib import Path





def     snake_case							(						UpperCAmelCase		)->     int:







      """simple docstring"""
      __A    		=     [tuple(UpperCAmelCase		) for login in logins]

      __A    		=     {char for login in split_logins for char in login}

      for permutation in itertools.permutations(UpperCAmelCase		):
            __A    		=     True
            for login in logins:
                  if not (
                      permutation.index(login[0]		)
                      < permutation.index(login[1]		)
                      < permutation.index(login[2]		)
                  ):
                        __A    		=     False
                        break

            if satisfied:
                  return int(''.join(UpperCAmelCase		)		)

      raise Exception('Unable to find the secret passcode'		)





def     snake_case							(						UpperCAmelCase = "keylog.txt"		)->     int:







      """simple docstring"""
      __A    		=     Path(UpperCAmelCase		).parent.joinpath(UpperCAmelCase		).read_text().splitlines()

      return find_secret_passcode(UpperCAmelCase		)


if __name__ == "__main__":
 print(f'''{solution() = }''')






