
'''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


snake_case_ :  Union[str, 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)

snake_case_ :  Optional[Any]     =					logging.getLogger()



def  __snake_case     (    ):
   UpperCamelCase       =  argparse.ArgumentParser()
   parser.add_argument('''-f''')
   UpperCamelCase       =  parser.parse_args()
   return args.f



def  __snake_case     (    _UpperCAmelCase					:       Union[str, Any],      _UpperCAmelCase					:       Dict="eval"):
   UpperCamelCase       =  os.path.join(_UpperCAmelCase,      f'{split}_results.json')
   if os.path.exists(_UpperCAmelCase):
      with open(_UpperCAmelCase,      '''r''') as f:
         return json.load(_UpperCAmelCase)
   raise ValueError(f'can\'t find {path}')


snake_case_ :  List[str]     =					logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)


class 						lowercase__	(  snake_case_   ):






   '''simple docstring'''







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  self.get_auto_remove_tmp_dir()
      UpperCamelCase       =  f'\n            run_glue.py\n            --model_name_or_path distilbert-base-uncased\n            --output_dir {tmp_dir}\n            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv\n            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --learning_rate=1e-4\n            --eval_steps=2\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            '.split()

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







   @slow
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  self.get_auto_remove_tmp_dir()
      UpperCamelCase       =  f'\n            run_clm_flax.py\n            --model_name_or_path distilgpt2\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --block_size 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            '.split()

      with patch.object(lowerCamelCase__ ,   '''argv''' ,   lowerCamelCase__   ):
         run_clm_flax.main()
         UpperCamelCase       =  get_results(lowerCamelCase__   )
         self.assertLess(result['''eval_perplexity'''] ,   1_0_0   )







   @slow
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  self.get_auto_remove_tmp_dir()
      UpperCamelCase       =  f'\n            run_summarization.py\n            --model_name_or_path t5-small\n            --train_file tests/fixtures/tests_samples/xsum/sample.json\n            --validation_file tests/fixtures/tests_samples/xsum/sample.json\n            --test_file tests/fixtures/tests_samples/xsum/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=8\n            --do_train\n            --do_eval\n            --do_predict\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --predict_with_generate\n        '.split()

      with patch.object(lowerCamelCase__ ,   '''argv''' ,   lowerCamelCase__   ):
         run_summarization_flax.main()
         UpperCamelCase       =  get_results(lowerCamelCase__ ,   split='''test'''   )
         self.assertGreaterEqual(result['''test_rouge1'''] ,   1_0   )
         self.assertGreaterEqual(result['''test_rouge2'''] ,   2   )
         self.assertGreaterEqual(result['''test_rougeL'''] ,   7   )
         self.assertGreaterEqual(result['''test_rougeLsum'''] ,   7   )







   @slow
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  self.get_auto_remove_tmp_dir()
      UpperCamelCase       =  f'\n            run_mlm.py\n            --model_name_or_path distilroberta-base\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --logging_steps 2 --eval_steps 2\n            --do_train\n            --do_eval\n            --num_train_epochs=1\n        '.split()

      with patch.object(lowerCamelCase__ ,   '''argv''' ,   lowerCamelCase__   ):
         run_mlm_flax.main()
         UpperCamelCase       =  get_results(lowerCamelCase__   )
         self.assertLess(result['''eval_perplexity'''] ,   4_2   )







   @slow
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  self.get_auto_remove_tmp_dir()
      UpperCamelCase       =  f'\n            run_t5_mlm_flax.py\n            --model_name_or_path t5-small\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            '.split()

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







   @slow
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  7 if get_gpu_count() > 1 else 2

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

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







   @slow
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  self.get_auto_remove_tmp_dir()
      UpperCamelCase       =  f'\n            run_qa.py\n            --model_name_or_path bert-base-uncased\n            --version_2_with_negative\n            --train_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=2\n            --do_train\n            --do_eval\n            --logging_steps 2 --eval_steps 2\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n        '.split()

      with patch.object(lowerCamelCase__ ,   '''argv''' ,   lowerCamelCase__   ):
         run_qa.main()
         UpperCamelCase       =  get_results(lowerCamelCase__   )
         self.assertGreaterEqual(result['''eval_f1'''] ,   3_0   )
         self.assertGreaterEqual(result['''eval_exact'''] ,   3_0   )





'''simple docstring'''


def  __snake_case     (    _UpperCAmelCase					:       Optional[int]):
   UpperCamelCase       =  []
   UpperCamelCase       =  []
   UpperCamelCase       =  {
       '''^''': 3,
       '''*''': 2,
       '''/''': 2,
       '''%''': 2,
       '''+''': 1,
       '''-''': 1,
   }  # Priority of each operator
   UpperCamelCase       =  len(_UpperCAmelCase) if (len(_UpperCAmelCase) > 7) else 7

   # Print table header for output
   print(
       '''Symbol'''.center(8),      '''Stack'''.center(_UpperCAmelCase),      '''Postfix'''.center(_UpperCAmelCase),      sep=''' | ''',      )
   print('''-''' * (print_width * 3 + 7))

   for x in infix:
      if x.isalpha() or x.isdigit():
         post_fix.append(_UpperCAmelCase)  # if x is Alphabet / Digit, add it to Postfix
      elif x == "(":
         stack.append(_UpperCAmelCase)  # if x is "(" push to Stack
      elif x == ")":  # if x is ")" pop stack until "(" is encountered
         while stack[-1] != "(":
            post_fix.append(stack.pop())  # Pop stack & add the content to Postfix
         stack.pop()
      else:
         if len(_UpperCAmelCase) == 0:
            stack.append(_UpperCAmelCase)  # If stack is empty, push x to stack
         else:  # while priority of x is not > priority of element in the stack
            while len(_UpperCAmelCase) > 0 and priority[x] <= priority[stack[-1]]:
               post_fix.append(stack.pop())  # pop stack & add to Postfix
            stack.append(_UpperCAmelCase)  # push x to stack

      print(
          x.center(8),      (''''''.join(_UpperCAmelCase)).ljust(_UpperCAmelCase),      (''''''.join(_UpperCAmelCase)).ljust(_UpperCAmelCase),      sep=''' | ''',      )  # Output in tabular format

   while len(_UpperCAmelCase) > 0:  # while stack is not empty
      post_fix.append(stack.pop())  # pop stack & add to Postfix
      print(
          ''' '''.center(8),      (''''''.join(_UpperCAmelCase)).ljust(_UpperCAmelCase),      (''''''.join(_UpperCAmelCase)).ljust(_UpperCAmelCase),      sep=''' | ''',      )  # Output in tabular format

   return "".join(_UpperCAmelCase)  # return Postfix as str



def  __snake_case     (    _UpperCAmelCase					:       str):
   UpperCamelCase       =  list(infix[::-1])  # reverse the infix equation

   for i in range(len(_UpperCAmelCase)):
      if infix[i] == "(":
         UpperCamelCase       =  ''')'''  # change "(" to ")"
      elif infix[i] == ")":
         UpperCamelCase       =  '''('''  # change ")" to "("

   return (infix_2_postfix(''''''.join(_UpperCAmelCase)))[
       ::-1
   ]  # call infix_2_postfix on Infix, return reverse of Postfix


if __name__ == "__main__":
   snake_case_ :  str     =					input('\nEnter an Infix Equation = ')  # Input an Infix equation
   snake_case_ :  Union[str, Any]     =					''.join(Infix.split())  # Remove spaces from the input
   print('\n\t', Infix, '(Infix) -> ', infix_2_prefix(Infix), '(Prefix)')





