


'''simple docstring'''







# This test is meant to be run in on an instance with TPUs like this:
#
#   python examples/pytorch/xla_spawn.py --num_cores=8 tests/test_trainer_tpu.py
#
# Replace 8 with the number of TPU cores you have.
#

import sys
from typing import Dict

from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.utils import logging


A      :     Dict										= logging.get_logger(__name__)


if is_torch_available():
   import torch
   from torch import nn
   from torch.utils.data import Dataset

   from transformers import Trainer


   class  __lowerCamelCase (       a_       ):
       """simple docstring"""


       def __init__(  self			:							Dict      ,							SCREAMING_SNAKE_CASE			:							int = 101):
              _A     :	Dict      =					length


       def __len__(  self			:							Optional[Any]):
              return self.length


       def __getitem__(  self			:							List[str]      ,							SCREAMING_SNAKE_CASE			:							Optional[Any]):
              return i




   class  __lowerCamelCase :
       """simple docstring"""


       def __call__(  self			:							int      ,							SCREAMING_SNAKE_CASE			:							str):
              return {"input_ids": torch.tensor(SCREAMING_SNAKE_CASE), "labels": torch.tensor(SCREAMING_SNAKE_CASE)}




   class  __lowerCamelCase (       nn.Module       ):
       """simple docstring"""


       def __init__(  self			:							str):
              super().__init__()
              # Add some (unused) params otherwise DDP will complain.
              _A     :	Union[str, Any]      =					nn.Linear(120      ,							80)


       def    A    (  self			:							List[Any]      ,							SCREAMING_SNAKE_CASE			:							str      ,							SCREAMING_SNAKE_CASE			:							Union[str, Any]=None):
              if labels is not None:
                     return torch.tensor(0.0      ,							device=input_ids.device), input_ids
              else:
                     return input_ids






def       lowerCAmelCase__       (				):
       _A     :	Dict      =					HfArgumentParser((TrainingArguments,)   )
       sys.argv += ["--output_dir", "./examples"]
       _A     :	Tuple      =					parser.parse_args_into_dataclasses()[0]

       logger.warning(
           F'Process rank: {training_args.local_rank}, device: {training_args.device}, '
           F'tpu_num_cores: {training_args.tpu_num_cores}'  ,)

       # Essentially, what we want to verify in the distributed case is
       # that we get all samples back, in the right order.
       # (this is crucial for prediction for instance)
       for dataset_length in [1001, 256, 15]:
              _A     :	List[Any]      =					DummyDataset(lowerCamelCase   )

              def compute_metrics(lowerCamelCase     :			EvalPrediction   ) -> Dict:
                     _A     :	Optional[Any]      =					list(range(len(lowerCamelCase   )   )   )
                     _A     :	List[str]      =					p.predictions.tolist() == sequential and p.label_ids.tolist() == sequential
                     return {"success": success}

              _A     :	List[Any]      =					Trainer(
                  model=DummyModel()  ,args=lowerCamelCase  ,data_collator=DummyDataCollator()  ,eval_dataset=lowerCamelCase  ,compute_metrics=lowerCamelCase  ,)
              _A     :	List[Any]      =					trainer.evaluate()
              logger.info(lowerCamelCase   )
              if metrics["eval_success"] is not True:
                     logger.error(lowerCamelCase   )
                     exit(1   )

              _A     :	int      =					trainer.predict(lowerCamelCase   )
              logger.info(p.metrics   )
              if p.metrics["test_success"] is not True:
                     logger.error(p.metrics   )
                     exit(1   )

              _A     :	List[str]      =					2

              _A     :	List[str]      =					trainer.evaluate()
              logger.info(lowerCamelCase   )
              if metrics["eval_success"] is not True:
                     logger.error(lowerCamelCase   )
                     exit(1   )

              _A     :	List[str]      =					trainer.predict(lowerCamelCase   )
              logger.info(p.metrics   )
              if p.metrics["test_success"] is not True:
                     logger.error(p.metrics   )
                     exit(1   )

              _A     :	Any      =					None

       logger.info('🔥 All distributed tests successful'   )






def       lowerCAmelCase__       (				lowerCamelCase     :			Any   ):
       # For xla_spawn (TPUs)
       main()


if __name__ == "__main__":
   main()










'''simple docstring'''







from __future__ import annotations






def       lowerCAmelCase__       (				lowerCamelCase     :			str  ,lowerCamelCase     :			dict[str, str]   ):
       _A  , _A  , _A     :	int      =					'', '', ''
       _A     :	Optional[int]      =					[]

       for character in message_part:
              tmp.append(character_to_number[character]   )

       for each in tmp:
              one += each[0]
              two += each[1]
              three += each[2]

       return one + two + three






def       lowerCAmelCase__       (				lowerCamelCase     :			str  ,lowerCamelCase     :			dict[str, str]   ):
       _A  , _A     :	Tuple      =					'', ''
       _A     :	Tuple      =					[]

       for character in message_part:
              this_part += character_to_number[character]

       for digit in this_part:
              tmp += digit
              if len(lowerCamelCase   ) == len(lowerCamelCase   ):
                     result.append(lowerCamelCase   )
                     _A     :	str      =					''

       return result[0], result[1], result[2]






def       lowerCAmelCase__       (				lowerCamelCase     :			str  ,lowerCamelCase     :			str   ):
       # Validate message and alphabet, set to upper and remove spaces
       _A     :	str      =					alphabet.replace(' '  ,''   ).upper()
       _A     :	Optional[Any]      =					message.replace(' '  ,''   ).upper()

       # Check length and characters
       if len(lowerCamelCase   ) != 27:
              raise KeyError('Length of alphabet has to be 27.'   )
       for each in message:
              if each not in alphabet:
                     raise ValueError('Each message character has to be included in alphabet!'   )

    # Generate dictionares
       _A     :	int      =					(
           '111',
           '112',
           '113',
           '121',
           '122',
           '123',
           '131',
           '132',
           '133',
           '211',
           '212',
           '213',
           '221',
           '222',
           '223',
           '231',
           '232',
           '233',
           '311',
           '312',
           '313',
           '321',
           '322',
           '323',
           '331',
           '332',
           '333',
       )
       _A     :	Optional[int]      =					{}
       _A     :	Any      =					{}
       for letter, number in zip(lowerCamelCase  ,lowerCamelCase   ):
              _A     :	str      =					number
              _A     :	List[str]      =					letter

       return message, alphabet, character_to_number, number_to_character






def       lowerCAmelCase__       (				lowerCamelCase     :			str  ,lowerCamelCase     :			str = "ABCDEFGHIJKLMNOPQRSTUVWXYZ."  ,lowerCamelCase     :			int = 5   ):
       _A  , _A  , _A  , _A     :	Union[str, Any]      =					__prepare(
           lowerCamelCase  ,lowerCamelCase   )
       _A  , _A     :	Any      =					'', ''

       for i in range(0  ,len(lowerCamelCase   ) + 1  ,lowerCamelCase   ):
              encrypted_numeric += __encrypt_part(
                  message[i : i + period]  ,lowerCamelCase   )

       for i in range(0  ,len(lowerCamelCase   )  ,3   ):
              encrypted += number_to_character[encrypted_numeric[i : i + 3]]

       return encrypted






def       lowerCAmelCase__       (				lowerCamelCase     :			str  ,lowerCamelCase     :			str = "ABCDEFGHIJKLMNOPQRSTUVWXYZ."  ,lowerCamelCase     :			int = 5   ):
       _A  , _A  , _A  , _A     :	Optional[Any]      =					__prepare(
           lowerCamelCase  ,lowerCamelCase   )
       _A     :	Tuple      =					[]
       _A     :	List[str]      =					''

       for i in range(0  ,len(lowerCamelCase   ) + 1  ,lowerCamelCase   ):
              _A  , _A  , _A     :	Tuple      =					__decrypt_part(message[i : i + period]  ,lowerCamelCase   )

              for j in range(0  ,len(lowerCamelCase   )   ):
                     decrypted_numeric.append(a[j] + b[j] + c[j]   )

       for each in decrypted_numeric:
              decrypted += number_to_character[each]

       return decrypted


if __name__ == "__main__":
   A      :     Dict										= '''DEFEND THE EAST WALL OF THE CASTLE.'''
   A      :     Any										= encrypt_message(msg, '''EPSDUCVWYM.ZLKXNBTFGORIJHAQ''')
   A      :     List[Any]										= decrypt_message(encrypted, '''EPSDUCVWYM.ZLKXNBTFGORIJHAQ''')
   print(f"""Encrypted: {encrypted}\nDecrypted: {decrypted}""")






