






"""simple docstring"""





import argparse
import json
import logging
import os
import sys
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


_SCREAMING_SNAKE_CASE					:				Any					    =						[
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        '''text-classification''',
        '''language-modeling''',
        '''summarization''',
        '''token-classification''',
        '''question-answering''',
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
  import run_clm_flax
  import run_flax_glue
  import run_flax_ner
  import run_mlm_flax
  import run_qa
  import run_summarization_flax
  import run_ta_mlm_flax


logging.basicConfig(level=logging.DEBUG)

_SCREAMING_SNAKE_CASE					:				Dict					    =						logging.getLogger()







def      lowerCamelCase__       (							)      ->				Union[str, Any]:
  lowerCamelCase_         =						argparse.ArgumentParser()
  parser.add_argument('-f' )
  lowerCamelCase_         =						parser.parse_args()
  return args.f







def      lowerCamelCase__       (							_lowerCamelCase       :		Optional[Any]		,				_lowerCamelCase       :		int="eval" )      ->				str:
  lowerCamelCase_         =						os.path.join(_lowerCamelCase		,				F'''{split}_results.json''' )
  if os.path.exists(_lowerCamelCase ):
    with open(_lowerCamelCase		,				'r' ) as f:
      return json.load(_lowerCamelCase )
  raise ValueError(F'''can\'t find {path}''' )


_SCREAMING_SNAKE_CASE					:				List[Any]					    =						logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)






class      a						(					__snake_case		):






    def    UpperCamelCase       (       self     :							Dict					)     ->		List[str]:
      lowerCamelCase_         =						self.get_auto_remove_tmp_dir()
      lowerCamelCase_         =						F'''
            run_glue.py
            --model_name_or_path distilbert-base-uncased
            --output_dir {tmp_dir}
            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --learning_rate=1e-4
            --eval_steps=2
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            '''.split()

      with patch.object(__SCREAMING_SNAKE_CASE       ,						'argv'       ,						__SCREAMING_SNAKE_CASE					):
        run_flax_glue.main()
        lowerCamelCase_         =						get_results(__SCREAMING_SNAKE_CASE					)
        self.assertGreaterEqual(result['eval_accuracy']       ,						0.75					)






    @slow
    def    UpperCamelCase       (       self     :							Dict					)     ->		List[str]:
      lowerCamelCase_         =						self.get_auto_remove_tmp_dir()
      lowerCamelCase_         =						F'''
            run_clm_flax.py
            --model_name_or_path distilgpt2
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --block_size 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --num_train_epochs 2
            --logging_steps 2 --eval_steps 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            '''.split()

      with patch.object(__SCREAMING_SNAKE_CASE       ,						'argv'       ,						__SCREAMING_SNAKE_CASE					):
        run_clm_flax.main()
        lowerCamelCase_         =						get_results(__SCREAMING_SNAKE_CASE					)
        self.assertLess(result['eval_perplexity']       ,						100					)






    @slow
    def    UpperCamelCase       (       self     :							str					)     ->		Dict:
      lowerCamelCase_         =						self.get_auto_remove_tmp_dir()
      lowerCamelCase_         =						F'''
            run_summarization.py
            --model_name_or_path t5-small
            --train_file tests/fixtures/tests_samples/xsum/sample.json
            --validation_file tests/fixtures/tests_samples/xsum/sample.json
            --test_file tests/fixtures/tests_samples/xsum/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --num_train_epochs=3
            --warmup_steps=8
            --do_train
            --do_eval
            --do_predict
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --predict_with_generate
        '''.split()

      with patch.object(__SCREAMING_SNAKE_CASE       ,						'argv'       ,						__SCREAMING_SNAKE_CASE					):
        run_summarization_flax.main()
        lowerCamelCase_         =						get_results(__SCREAMING_SNAKE_CASE       ,						split='test'					)
        self.assertGreaterEqual(result['test_rouge1']       ,						10					)
        self.assertGreaterEqual(result['test_rouge2']       ,						2					)
        self.assertGreaterEqual(result['test_rougeL']       ,						7					)
        self.assertGreaterEqual(result['test_rougeLsum']       ,						7					)






    @slow
    def    UpperCamelCase       (       self     :							str					)     ->		List[Any]:
      lowerCamelCase_         =						self.get_auto_remove_tmp_dir()
      lowerCamelCase_         =						F'''
            run_mlm.py
            --model_name_or_path distilroberta-base
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --max_seq_length 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --logging_steps 2 --eval_steps 2
            --do_train
            --do_eval
            --num_train_epochs=1
        '''.split()

      with patch.object(__SCREAMING_SNAKE_CASE       ,						'argv'       ,						__SCREAMING_SNAKE_CASE					):
        run_mlm_flax.main()
        lowerCamelCase_         =						get_results(__SCREAMING_SNAKE_CASE					)
        self.assertLess(result['eval_perplexity']       ,						42					)






    @slow
    def    UpperCamelCase       (       self     :							Union[str, Any]					)     ->		Union[str, Any]:
      lowerCamelCase_         =						self.get_auto_remove_tmp_dir()
      lowerCamelCase_         =						F'''
            run_t5_mlm_flax.py
            --model_name_or_path t5-small
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --max_seq_length 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --num_train_epochs 2
            --logging_steps 2 --eval_steps 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            '''.split()

      with patch.object(__SCREAMING_SNAKE_CASE       ,						'argv'       ,						__SCREAMING_SNAKE_CASE					):
        run_ta_mlm_flax.main()
        lowerCamelCase_         =						get_results(__SCREAMING_SNAKE_CASE					)
        self.assertGreaterEqual(result['eval_accuracy']       ,						0.42					)






    @slow
    def    UpperCamelCase       (       self     :							Any					)     ->		int:
      # with so little data distributed training needs more epochs to get the score on par with 0/1 gpu
      lowerCamelCase_         =						7 if get_gpu_count() > 1 else 2

      lowerCamelCase_         =						self.get_auto_remove_tmp_dir()
      lowerCamelCase_         =						F'''
            run_flax_ner.py
            --model_name_or_path bert-base-uncased
            --train_file tests/fixtures/tests_samples/conll/sample.json
            --validation_file tests/fixtures/tests_samples/conll/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --do_train
            --do_eval
            --warmup_steps=2
            --learning_rate=2e-4
            --logging_steps 2 --eval_steps 2
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=2
            --num_train_epochs={epochs}
            --seed 7
        '''.split()

      with patch.object(__SCREAMING_SNAKE_CASE       ,						'argv'       ,						__SCREAMING_SNAKE_CASE					):
        run_flax_ner.main()
        lowerCamelCase_         =						get_results(__SCREAMING_SNAKE_CASE					)
        self.assertGreaterEqual(result['eval_accuracy']       ,						0.75					)
        self.assertGreaterEqual(result['eval_f1']       ,						0.3					)






    @slow
    def    UpperCamelCase       (       self     :							str					)     ->		Dict:
      lowerCamelCase_         =						self.get_auto_remove_tmp_dir()
      lowerCamelCase_         =						F'''
            run_qa.py
            --model_name_or_path bert-base-uncased
            --version_2_with_negative
            --train_file tests/fixtures/tests_samples/SQUAD/sample.json
            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --num_train_epochs=3
            --warmup_steps=2
            --do_train
            --do_eval
            --logging_steps 2 --eval_steps 2
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
        '''.split()

      with patch.object(__SCREAMING_SNAKE_CASE       ,						'argv'       ,						__SCREAMING_SNAKE_CASE					):
        run_qa.main()
        lowerCamelCase_         =						get_results(__SCREAMING_SNAKE_CASE					)
        self.assertGreaterEqual(result['eval_f1']       ,						30					)
        self.assertGreaterEqual(result['eval_exact']       ,						30					)












"""simple docstring"""





import string







def      lowerCamelCase__       (							_lowerCamelCase       :		str )      ->				None:
  for key in range(len(string.ascii_uppercase ) ):
    lowerCamelCase_         =						''
    for symbol in message:
      if symbol in string.ascii_uppercase:
        lowerCamelCase_         =						string.ascii_uppercase.find(_lowerCamelCase )
        lowerCamelCase_         =						num - key
        if num < 0:
          lowerCamelCase_         =						num + len(string.ascii_uppercase )
        lowerCamelCase_         =						translated + string.ascii_uppercase[num]
      else:
        lowerCamelCase_         =						translated + symbol
    print(F'''Decryption using Key #{key}: {translated}''' )







def      lowerCamelCase__       (							)      ->				None:
  lowerCamelCase_         =						input('Encrypted message: ' )
  lowerCamelCase_         =						message.upper()
  decrypt(_lowerCamelCase )


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()




