





'''simple docstring'''




import argparse
import collections
import os
import re

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
lowercase__   :				Optional[int]      =   '''src/transformers'''
lowercase__   :				List[Any]      =   '''docs/source/en'''
lowercase__   :				Any      =   '''.'''






def 	_lowerCAmelCase      (  __snake_case  :			str			,							__snake_case  :			Optional[int]			,							__snake_case  :			List[str]      )					->					Optional[Any]:
     with open(__snake_case			,							'r'			,							encoding='utf-8'			,							newline='\n'      ) as f:
          __A						:			int								=	f.readlines()
     # Find the start prompt.
     __A						:			int								=	0
     while not lines[start_index].startswith(__snake_case      ):
          start_index += 1
     start_index += 1

     __A						:			Tuple								=	start_index
     while not lines[end_index].startswith(__snake_case      ):
          end_index += 1
     end_index -= 1

     while len(lines[start_index]      ) <= 1:
          start_index += 1
     while len(lines[end_index]      ) <= 1:
          end_index -= 1
     end_index += 1
     return "".join(lines[start_index:end_index]      ), start_index, end_index, lines


# Add here suffixes that are used to identify models, separated by |
lowercase__   :				str      =   '''Model|Encoder|Decoder|ForConditionalGeneration'''
# Regexes that match TF/Flax/PT model names.
lowercase__   :				Optional[Any]      =   re.compile(r'''TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')
lowercase__   :				List[str]      =   re.compile(r'''Flax(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')
# Will match any TF or Flax model too so need to be in an else branch afterthe two previous regexes.
lowercase__   :				Optional[Any]      =   re.compile(r'''(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')


# This is to make sure the transformers module imported is the one in the repo.
lowercase__   :				Optional[Any]      =   direct_transformers_import(TRANSFORMERS_PATH)






def 	_lowerCAmelCase      (  __snake_case  :			Tuple      )					->					Optional[Any]:
     __A						:			Optional[Any]								=	re.finditer('.+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)'			,							__snake_case      )
     return [m.group(0      ) for m in matches]






def 	_lowerCAmelCase      (  __snake_case  :			Any			,							__snake_case  :			Union[str, Any]      )					->					int:
     __A						:			int								=	2 if text == '✅' or text == '❌' else len(__snake_case      )
     __A						:			Union[str, Any]								=	(width - text_length) // 2
     __A						:			Optional[int]								=	width - text_length - left_indent
     return " " * left_indent + text + " " * right_indent






def 	_lowerCAmelCase      (  )					->					Optional[int]:
     __A						:			str								=	transformers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
     __A						:			List[Any]								=	{
         name: config_maping_names[code]
         for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
         if code in config_maping_names
     }
     __A						:			Optional[Any]								=	{name: config.replace('Config'			,							''      ) for name, config in model_name_to_config.items()}

     # Dictionaries flagging if each model prefix has a slow/fast tokenizer, backend in PT/TF/Flax.
     __A						:			Optional[Any]								=	collections.defaultdict(__snake_case      )
     __A						:			int								=	collections.defaultdict(__snake_case      )
     __A						:			Any								=	collections.defaultdict(__snake_case      )
     __A						:			Optional[int]								=	collections.defaultdict(__snake_case      )
     __A						:			List[str]								=	collections.defaultdict(__snake_case      )

     # Let's lookup through all transformers object (once).
     for attr_name in dir(__snake_case      ):
          __A						:			str								=	None
          if attr_name.endswith('Tokenizer'      ):
               __A						:			Optional[int]								=	slow_tokenizers
               __A						:			List[str]								=	attr_name[:-9]
          elif attr_name.endswith('TokenizerFast'      ):
               __A						:			Tuple								=	fast_tokenizers
               __A						:			Optional[Any]								=	attr_name[:-13]
          elif _re_tf_models.match(__snake_case      ) is not None:
               __A						:			Any								=	tf_models
               __A						:			List[Any]								=	_re_tf_models.match(__snake_case      ).groups()[0]
          elif _re_flax_models.match(__snake_case      ) is not None:
               __A						:			List[str]								=	flax_models
               __A						:			Optional[int]								=	_re_flax_models.match(__snake_case      ).groups()[0]
          elif _re_pt_models.match(__snake_case      ) is not None:
               __A						:			Tuple								=	pt_models
               __A						:			Optional[int]								=	_re_pt_models.match(__snake_case      ).groups()[0]

          if lookup_dict is not None:
               while len(__snake_case      ) > 0:
                    if attr_name in model_name_to_prefix.values():
                         __A						:			Union[str, Any]								=	True
                         break
                    # Try again after removing the last word in the name
                    __A						:			List[str]								=	''.join(camel_case_split(__snake_case      )[:-1]      )

    # Let's build that table!
     __A						:			int								=	list(model_name_to_config.keys()      )
     model_names.sort(key=str.lower      )
     __A						:			Optional[Any]								=	['Model', 'Tokenizer slow', 'Tokenizer fast', 'PyTorch support', 'TensorFlow support', 'Flax Support']
     # We'll need widths to properly display everything in the center (+2 is to leave one extra space on each side).
     __A						:			Optional[int]								=	[len(__snake_case      ) + 2 for c in columns]
     __A						:			Tuple								=	max([len(__snake_case      ) for name in model_names]      ) + 2

     # Build the table per se
     __A						:			Tuple								=	'|' + '|'.join([_center_text(__snake_case			,							__snake_case      ) for c, w in zip(__snake_case			,							__snake_case      )]      ) + '|\n'
     # Use ":-----:" format to center-aligned table cell texts
     table += "|" + "|".join([':' + '-' * (w - 2) + ':' for w in widths]      ) + "|\n"

     __A						:			Optional[int]								=	{True: '✅', False: '❌'}
     for name in model_names:
          __A						:			Any								=	model_name_to_prefix[name]
          __A						:			str								=	[
              name,
              check[slow_tokenizers[prefix]],
              check[fast_tokenizers[prefix]],
              check[pt_models[prefix]],
              check[tf_models[prefix]],
              check[flax_models[prefix]],
          ]
          table += "|" + "|".join([_center_text(__snake_case			,							__snake_case      ) for l, w in zip(__snake_case			,							__snake_case      )]      ) + "|\n"
     return table






def 	_lowerCAmelCase      (  __snake_case  :			Any=False      )					->					Dict:
     __A			,__A			,__A			,__A						:			Union[str, Any]								=	_find_text_in_file(
         filename=os.path.join(__snake_case			,							'index.md'      )			,							start_prompt='<!--This table is updated automatically from the auto modules'			,							end_prompt='<!-- End table-->'			,							)
     __A						:			Optional[int]								=	get_model_table_from_auto_modules()

     if current_table != new_table:
          if overwrite:
               with open(os.path.join(__snake_case			,							'index.md'      )			,							'w'			,							encoding='utf-8'			,							newline='\n'      ) as f:
                    f.writelines(lines[:start_index] + [new_table] + lines[end_index:]      )
          else:
               raise ValueError(
                   'The model table in the `index.md` has not been updated. Run `make fix-copies` to fix this.'      )


if __name__ == "__main__":
  lowercase__   :				str      =   argparse.ArgumentParser()
  parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
  lowercase__   :				int      =   parser.parse_args()

  check_model_table(args.fix_and_overwrite)






'''simple docstring'''




import math






def 	_lowerCAmelCase      (  __snake_case  :			int      )					->					bool:

     if 1 < number < 4:
          # 2 and 3 are primes
          return True
     elif number < 2 or number % 2 == 0 or number % 3 == 0:
          # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
          return False

     # All primes number are in format of 6k +/- 1
     for i in range(5			,							int(math.sqrt(__snake_case      ) + 1      )			,							6      ):
          if number % i == 0 or number % (i + 2) == 0:
               return False
     return True






def 	_lowerCAmelCase      (  __snake_case  :			float = 0.1      )					->					int:
     __A						:			Dict								=	3
     __A						:			int								=	3

     while primes / (2 * j - 1) >= ratio:
          for i in range(j * j + j + 1			,							(j + 2) * (j + 2)			,							j + 1      ):
               primes += is_prime(__snake_case      )
          j += 2
     return j


if __name__ == "__main__":
  import doctest

  doctest.testmod()