



"""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


lowerCamelCase      =		[
    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)

lowerCamelCase      =		logging.getLogger()
def      a__			(   ):
      UpperCAmelCase_    				=							argparse.ArgumentParser()
      parser.add_argument("-f"   )
      UpperCAmelCase_    				=							parser.parse_args()
      return args.f
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__="eval"   ):
      UpperCAmelCase_    				=							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}"""   )


lowerCamelCase      =		logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)


class    lowercase__     (					SCREAMING_SNAKE_CASE   ):







       '''simple docstring'''


       def   lowercase__       (							self    :						Optional[Any]					)				->		str:


             '''simple docstring'''




             UpperCAmelCase_    				=							self.get_auto_remove_tmp_dir()
             UpperCAmelCase_    				=							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(_UpperCAmelCase	,       "argv"	,       _UpperCAmelCase					):
                   run_flax_glue.main()
                   UpperCAmelCase_    				=							get_results(_UpperCAmelCase					)
                   self.assertGreaterEqual(result["eval_accuracy"]	,       0.75					)



       @slow
       def   lowercase__       (							self    :						Optional[Any]					)				->		List[Any]:


             '''simple docstring'''




             UpperCAmelCase_    				=							self.get_auto_remove_tmp_dir()
             UpperCAmelCase_    				=							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(_UpperCAmelCase	,       "argv"	,       _UpperCAmelCase					):
                   run_clm_flax.main()
                   UpperCAmelCase_    				=							get_results(_UpperCAmelCase					)
                   self.assertLess(result["eval_perplexity"]	,       100					)



       @slow
       def   lowercase__       (							self    :						Optional[Any]					)				->		Union[str, Any]:


             '''simple docstring'''




             UpperCAmelCase_    				=							self.get_auto_remove_tmp_dir()
             UpperCAmelCase_    				=							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(_UpperCAmelCase	,       "argv"	,       _UpperCAmelCase					):
                   run_summarization_flax.main()
                   UpperCAmelCase_    				=							get_results(_UpperCAmelCase	,       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   lowercase__       (							self    :						Union[str, Any]					)				->		Tuple:


             '''simple docstring'''




             UpperCAmelCase_    				=							self.get_auto_remove_tmp_dir()
             UpperCAmelCase_    				=							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(_UpperCAmelCase	,       "argv"	,       _UpperCAmelCase					):
                   run_mlm_flax.main()
                   UpperCAmelCase_    				=							get_results(_UpperCAmelCase					)
                   self.assertLess(result["eval_perplexity"]	,       42					)



       @slow
       def   lowercase__       (							self    :						List[str]					)				->		Tuple:


             '''simple docstring'''




             UpperCAmelCase_    				=							self.get_auto_remove_tmp_dir()
             UpperCAmelCase_    				=							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(_UpperCAmelCase	,       "argv"	,       _UpperCAmelCase					):
                   run_ta_mlm_flax.main()
                   UpperCAmelCase_    				=							get_results(_UpperCAmelCase					)
                   self.assertGreaterEqual(result["eval_accuracy"]	,       0.42					)



       @slow
       def   lowercase__       (							self    :						Tuple					)				->		Optional[Any]:


             '''simple docstring'''




             UpperCAmelCase_    				=							7 if get_gpu_count() > 1 else 2

             UpperCAmelCase_    				=							self.get_auto_remove_tmp_dir()
             UpperCAmelCase_    				=							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(_UpperCAmelCase	,       "argv"	,       _UpperCAmelCase					):
                   run_flax_ner.main()
                   UpperCAmelCase_    				=							get_results(_UpperCAmelCase					)
                   self.assertGreaterEqual(result["eval_accuracy"]	,       0.75					)
                   self.assertGreaterEqual(result["eval_f1"]	,       0.3					)







       @slow
       def   lowercase__       (							self    :						Tuple					)				->		int:


             '''simple docstring'''




             UpperCAmelCase_    				=							self.get_auto_remove_tmp_dir()
             UpperCAmelCase_    				=							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(_UpperCAmelCase	,       "argv"	,       _UpperCAmelCase					):
                   run_qa.main()
                   UpperCAmelCase_    				=							get_results(_UpperCAmelCase					)
                   self.assertGreaterEqual(result["eval_f1"]	,       30					)
                   self.assertGreaterEqual(result["eval_exact"]	,       30					)









"""simple docstring"""





import string
def      a__			(   lowerCAmelCase__   ):
      for key in range(len(string.ascii_uppercase   )   ):
            UpperCAmelCase_    				=							""
            for symbol in message:
                  if symbol in string.ascii_uppercase:
                        UpperCAmelCase_    				=							string.ascii_uppercase.find(lowerCAmelCase__   )
                        UpperCAmelCase_    				=							num - key
                        if num < 0:
                              UpperCAmelCase_    				=							num + len(string.ascii_uppercase   )
                        UpperCAmelCase_    				=							translated + string.ascii_uppercase[num]
                  else:
                        UpperCAmelCase_    				=							translated + symbol
            print(f"""Decryption using Key #{key}: {translated}"""   )
def      a__			(   ):
      UpperCAmelCase_    				=							input("Encrypted message: "   )
      UpperCAmelCase_    				=							message.upper()
      decrypt(lowerCAmelCase__   )


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()




