


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
SCREAMING_SNAKE_CASE						:str			=  '''src/transformers'''
SCREAMING_SNAKE_CASE						:str			=  '''docs/source/en'''
SCREAMING_SNAKE_CASE						:Tuple			=  '''.'''



def       _lowerCAmelCase    (				lowerCAmelCase_				:Optional[Any]		,    lowerCAmelCase_				:Dict		,    lowerCAmelCase_				:Tuple				)->Tuple:
   '''simple docstring'''






   with open(lowerCAmelCase_		,    "r"		,    encoding="utf-8"		,    newline="\n"				) as f:
      snake_case_            =       f.readlines()
   # Find the start prompt.
   snake_case_            =       0
   while not lines[start_index].startswith(lowerCAmelCase_				):
      start_index += 1
   start_index += 1

   snake_case_            =       start_index
   while not lines[end_index].startswith(lowerCAmelCase_				):
      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 |
SCREAMING_SNAKE_CASE						:Optional[int]			=  '''Model|Encoder|Decoder|ForConditionalGeneration'''
# Regexes that match TF/Flax/PT model names.
SCREAMING_SNAKE_CASE						:Tuple			=  re.compile(R'''TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')
SCREAMING_SNAKE_CASE						: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.
SCREAMING_SNAKE_CASE						:int			=  re.compile(R'''(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')


# This is to make sure the transformers module imported is the one in the repo.
SCREAMING_SNAKE_CASE						:List[str]			=  direct_transformers_import(TRANSFORMERS_PATH)



def       _lowerCAmelCase    (				lowerCAmelCase_				:int				)->Union[str, Any]:
   '''simple docstring'''






   snake_case_            =       re.finditer(".+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)"		,    lowerCAmelCase_				)
   return [m.group(0				) for m in matches]



def       _lowerCAmelCase    (				lowerCAmelCase_				:Any		,    lowerCAmelCase_				:Any				)->Tuple:
   '''simple docstring'''






   snake_case_            =       2 if text == "✅" or text == "❌" else len(lowerCAmelCase_				)
   snake_case_            =       (width - text_length) // 2
   snake_case_            =       width - text_length - left_indent
   return " " * left_indent + text + " " * right_indent



def       _lowerCAmelCase    (				)->List[Any]:
   '''simple docstring'''






   snake_case_            =       transformers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
   snake_case_            =       {
       name: config_maping_names[code]
       for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
       if code in config_maping_names
   }
   snake_case_            =       {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.
   snake_case_            =       collections.defaultdict(lowerCAmelCase_				)
   snake_case_            =       collections.defaultdict(lowerCAmelCase_				)
   snake_case_            =       collections.defaultdict(lowerCAmelCase_				)
   snake_case_            =       collections.defaultdict(lowerCAmelCase_				)
   snake_case_            =       collections.defaultdict(lowerCAmelCase_				)

   # Let's lookup through all transformers object (once).
   for attr_name in dir(lowerCAmelCase_				):
      snake_case_            =       None
      if attr_name.endswith("Tokenizer"				):
         snake_case_            =       slow_tokenizers
         snake_case_            =       attr_name[:-9]
      elif attr_name.endswith("TokenizerFast"				):
         snake_case_            =       fast_tokenizers
         snake_case_            =       attr_name[:-13]
      elif _re_tf_models.match(lowerCAmelCase_				) is not None:
         snake_case_            =       tf_models
         snake_case_            =       _re_tf_models.match(lowerCAmelCase_				).groups()[0]
      elif _re_flax_models.match(lowerCAmelCase_				) is not None:
         snake_case_            =       flax_models
         snake_case_            =       _re_flax_models.match(lowerCAmelCase_				).groups()[0]
      elif _re_pt_models.match(lowerCAmelCase_				) is not None:
         snake_case_            =       pt_models
         snake_case_            =       _re_pt_models.match(lowerCAmelCase_				).groups()[0]

      if lookup_dict is not None:
         while len(lowerCAmelCase_				) > 0:
            if attr_name in model_name_to_prefix.values():
               snake_case_            =       True
               break
            # Try again after removing the last word in the name
            snake_case_            =       "".join(camel_case_split(lowerCAmelCase_				)[:-1]				)

    # Let's build that table!
   snake_case_            =       list(model_name_to_config.keys()				)
   model_names.sort(key=str.lower				)
   snake_case_            =       ["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).
   snake_case_            =       [len(lowerCAmelCase_				) + 2 for c in columns]
   snake_case_            =       max([len(lowerCAmelCase_				) for name in model_names]				) + 2

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

   snake_case_            =       {True: "✅", False: "❌"}
   for name in model_names:
      snake_case_            =       model_name_to_prefix[name]
      snake_case_            =       [
          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(lowerCAmelCase_		,    lowerCAmelCase_				) for l, w in zip(lowerCAmelCase_		,    lowerCAmelCase_				)]				) + "|\n"
   return table



def       _lowerCAmelCase    (				lowerCAmelCase_				:int=False				)->str:
   '''simple docstring'''






   snake_case_     ,     snake_case_     ,     snake_case_     ,     snake_case_            =       _find_text_in_file(
       filename=os.path.join(lowerCAmelCase_		,    "index.md"				)		,    start_prompt="<!--This table is updated automatically from the auto modules"		,    end_prompt="<!-- End table-->"		,    )
   snake_case_            =       get_model_table_from_auto_modules()

   if current_table != new_table:
      if overwrite:
         with open(os.path.join(lowerCAmelCase_		,    "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__":
   SCREAMING_SNAKE_CASE						:Optional[Any]			=  argparse.ArgumentParser()
   parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
   SCREAMING_SNAKE_CASE						:Any			=  parser.parse_args()

   check_model_table(args.fix_and_overwrite)








from math import factorial



def       _lowerCAmelCase    (				lowerCAmelCase_				:int = 20				)->int:
   '''simple docstring'''






   snake_case_            =       2 * n  # middle entry of odd rows starting at row 3 is the solution for n = 1,
   # 2, 3,...
   snake_case_            =       n // 2

   return int(factorial(lowerCAmelCase_				) / (factorial(lowerCAmelCase_				) * factorial(n - k				))				)


if __name__ == "__main__":
   import sys

   if len(sys.argv) == 1:
      print(solution(20))
   else:
      try:
         SCREAMING_SNAKE_CASE						:Any			=  int(sys.argv[1])
         print(solution(n))
      except ValueError:
         print('''Invalid entry - please enter a number.''')




