



'''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_		       =  "src/transformers"
lowercase_		       =  "docs/source/en"
lowercase_		       =  "."




def lowerCAmelCase  (__A  ,	__A  ,	__A):



     """simple docstring"""



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

     _a      =  start_index
     while not lines[end_index].startswith(__A):
          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_		       =  "Model|Encoder|Decoder|ForConditionalGeneration"
# Regexes that match TF/Flax/PT model names.
lowercase_		       =  re.compile(R"TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)")
lowercase_		       =  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_		       =  re.compile(R"(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)")


# This is to make sure the transformers module imported is the one in the repo.
lowercase_		       =  direct_transformers_import(TRANSFORMERS_PATH)




def lowerCAmelCase  (__A):



     """simple docstring"""



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




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



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




def lowerCAmelCase  ():



     """simple docstring"""



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

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

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

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

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

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




def lowerCAmelCase  (__A=False):



     """simple docstring"""



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

     if current_table != new_table:
          if overwrite:
               with open(os.path.join(__A  ,	'''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_		       =  argparse.ArgumentParser()
  parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
  lowercase_		       =  parser.parse_args()

  check_model_table(args.fix_and_overwrite)








'''simple docstring'''





from collections.abc import Generator
from math import sin




def lowerCAmelCase  (__A):



     """simple docstring"""



     if len(__A) != 32:
          raise ValueError('''Input must be of length 32''')

     _a      =  b''''''
     for i in [3, 2, 1, 0]:
          little_endian += string_aa[8 * i : 8 * i + 8]
     return little_endian




def lowerCAmelCase  (__A):



     """simple docstring"""



     if i < 0:
          raise ValueError('''Input must be non-negative''')

     _a      =  format(__A  ,	'''08x''')[-8:]
     _a      =  b''''''
     for i in [3, 2, 1, 0]:
          little_endian_hex += hex_rep[2 * i : 2 * i + 2].encode('''utf-8''')
     return little_endian_hex




def lowerCAmelCase  (__A):



     """simple docstring"""



     _a      =  b''''''
     for char in message:
          bit_string += format(__A  ,	'''08b''').encode('''utf-8''')
     _a      =  format(len(__A)  ,	'''064b''').encode('''utf-8''')

     # Pad bit_string to a multiple of 512 chars
     bit_string += b"1"
     while len(__A) % 512 != 448:
          bit_string += b"0"
     bit_string += to_little_endian(start_len[32:]) + to_little_endian(start_len[:32])

     return bit_string




def lowerCAmelCase  (__A):



     """simple docstring"""



     if len(__A) % 512 != 0:
          raise ValueError('''Input must have length that\'s a multiple of 512''')

     for pos in range(0  ,	len(__A)  ,	512):
          _a      =  bit_string[pos : pos + 512]
          _a      =  []
          for i in range(0  ,	512  ,	32):
               block_words.append(int(to_little_endian(block[i : i + 32])  ,	2))
          yield block_words




def lowerCAmelCase  (__A):



     """simple docstring"""



     if i < 0:
          raise ValueError('''Input must be non-negative''')

     _a      =  format(__A  ,	'''032b''')
     _a      =  ''''''
     for c in i_str:
          new_str += "1" if c == "0" else "0"
     return int(__A  ,	2)




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     return (a + b) % 2**32




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     if i < 0:
          raise ValueError('''Input must be non-negative''')
     if shift < 0:
          raise ValueError('''Shift must be non-negative''')
     return ((i << shift) ^ (i >> (32 - shift))) % 2**32




def lowerCAmelCase  (__A):



     """simple docstring"""



     _a      =  preprocess(__A)

     _a      =  [int(2**32 * abs(sin(i + 1))) for i in range(64)]

     # Starting states
     _a      =  0x67_452_301
     _a      =  0xEF_CDA_B89
     _a      =  0x98_BAD_CFE
     _a      =  0x10_325_476

     _a      =  [
         7,
         12,
         17,
         22,
         7,
         12,
         17,
         22,
         7,
         12,
         17,
         22,
         7,
         12,
         17,
         22,
         5,
         9,
         14,
         20,
         5,
         9,
         14,
         20,
         5,
         9,
         14,
         20,
         5,
         9,
         14,
         20,
         4,
         11,
         16,
         23,
         4,
         11,
         16,
         23,
         4,
         11,
         16,
         23,
         4,
         11,
         16,
         23,
         6,
         10,
         15,
         21,
         6,
         10,
         15,
         21,
         6,
         10,
         15,
         21,
         6,
         10,
         15,
         21,
     ]

     # Process bit string in chunks, each with 16 32-char words
     for block_words in get_block_words(__A):
          _a      =  aa
          _a      =  ba
          _a      =  ca
          _a      =  da

          # Hash current chunk
          for i in range(64):
               if i <= 15:
                    # f = (b & c) | (not_32(b) & d)     # Alternate definition for f
                    _a      =  d ^ (b & (c ^ d))
                    _a      =  i
               elif i <= 31:
                    # f = (d & b) | (not_32(d) & c)     # Alternate definition for f
                    _a      =  c ^ (d & (b ^ c))
                    _a      =  (5 * i + 1) % 16
               elif i <= 47:
                    _a      =  b ^ c ^ d
                    _a      =  (3 * i + 5) % 16
               else:
                    _a      =  c ^ (b | not_aa(__A))
                    _a      =  (7 * i) % 16
               _a      =  (f + a + added_consts[i] + block_words[g]) % 2**32
               _a      =  d
               _a      =  c
               _a      =  b
               _a      =  sum_aa(__A  ,	left_rotate_aa(__A  ,	shift_amounts[i]))

          # Add hashed chunk to running total
          _a      =  sum_aa(__A  ,	__A)
          _a      =  sum_aa(__A  ,	__A)
          _a      =  sum_aa(__A  ,	__A)
          _a      =  sum_aa(__A  ,	__A)

     _a      =  reformat_hex(__A) + reformat_hex(__A) + reformat_hex(__A) + reformat_hex(__A)
     return digest


if __name__ == "__main__":
  import doctest

  doctest.testmod()



