






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
__UpperCAmelCase     							=						'src/transformers'
__UpperCAmelCase     							=						'docs/source/en'
__UpperCAmelCase     							=						'.'




def 					lowercase__				(					__snake_case   :							List[Any]					,	__snake_case   :							Dict					,	__snake_case   :							str  ):


					'''simple docstring'''


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

					UpperCAmelCase_   :				List[Any]						=						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 |
__UpperCAmelCase     							=						'Model|Encoder|Decoder|ForConditionalGeneration'
# Regexes that match TF/Flax/PT model names.
__UpperCAmelCase     							=						re.compile(R'TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)')
__UpperCAmelCase     							=						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.
__UpperCAmelCase     							=						re.compile(R'(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)')


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




def 					lowercase__				(					__snake_case   :							int  ):


					'''simple docstring'''


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




def 					lowercase__				(					__snake_case   :							Dict					,	__snake_case   :							Union[str, Any]  ):


					'''simple docstring'''


					UpperCAmelCase_   :				List[Any]						=						2 if text == '✅' or text == '❌' else len(__snake_case  )
					UpperCAmelCase_   :				List[Any]						=						(width - text_length) // 2
					UpperCAmelCase_   :				Dict						=						width - text_length - left_indent
					return " " * left_indent + text + " " * right_indent




def 					lowercase__				(					):


					'''simple docstring'''


					UpperCAmelCase_   :				Optional[int]						=						transformers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
					UpperCAmelCase_   :				Optional[Any]						=						{
					    name: config_maping_names[code]
					    for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
					    if code in config_maping_names
					}
					UpperCAmelCase_   :				Tuple						=						{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.
					UpperCAmelCase_   :				Optional[int]						=						collections.defaultdict(__snake_case  )
					UpperCAmelCase_   :				Tuple						=						collections.defaultdict(__snake_case  )
					UpperCAmelCase_   :				Union[str, Any]						=						collections.defaultdict(__snake_case  )
					UpperCAmelCase_   :				Any						=						collections.defaultdict(__snake_case  )
					UpperCAmelCase_   :				str						=						collections.defaultdict(__snake_case  )

					# Let's lookup through all transformers object (once).
					for attr_name in dir(__snake_case  ):
										UpperCAmelCase_   :				Optional[Any]						=						None
										if attr_name.endswith('Tokenizer'  ):
															UpperCAmelCase_   :				int						=						slow_tokenizers
															UpperCAmelCase_   :				Optional[Any]						=						attr_name[:-9]
										elif attr_name.endswith('TokenizerFast'  ):
															UpperCAmelCase_   :				int						=						fast_tokenizers
															UpperCAmelCase_   :				Tuple						=						attr_name[:-13]
										elif _re_tf_models.match(__snake_case  ) is not None:
															UpperCAmelCase_   :				Tuple						=						tf_models
															UpperCAmelCase_   :				List[str]						=						_re_tf_models.match(__snake_case  ).groups()[0]
										elif _re_flax_models.match(__snake_case  ) is not None:
															UpperCAmelCase_   :				Any						=						flax_models
															UpperCAmelCase_   :				List[str]						=						_re_flax_models.match(__snake_case  ).groups()[0]
										elif _re_pt_models.match(__snake_case  ) is not None:
															UpperCAmelCase_   :				Union[str, Any]						=						pt_models
															UpperCAmelCase_   :				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():
																									UpperCAmelCase_   :				Any						=						True
																									break
																				# Try again after removing the last word in the name
																				UpperCAmelCase_   :				List[str]						=						''.join(camel_case_split(__snake_case  )[:-1]  )

    # Let's build that table!
					UpperCAmelCase_   :				List[str]						=						list(model_name_to_config.keys()  )
					model_names.sort(key=str.lower  )
					UpperCAmelCase_   :				List[str]						=						['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).
					UpperCAmelCase_   :				Union[str, Any]						=						[len(__snake_case  ) + 2 for c in columns]
					UpperCAmelCase_   :				str						=						max([len(__snake_case  ) for name in model_names]  ) + 2

					# Build the table per se
					UpperCAmelCase_   :				Optional[Any]						=						'|' + '|'.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"

					UpperCAmelCase_   :				int						=						{True: '✅', False: '❌'}
					for name in model_names:
										UpperCAmelCase_   :				List[str]						=						model_name_to_prefix[name]
										UpperCAmelCase_   :				Dict						=						[
										    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 					lowercase__				(					__snake_case   :							Dict=False  ):


					'''simple docstring'''


					UpperCAmelCase_	,  UpperCAmelCase_	,  UpperCAmelCase_	,  UpperCAmelCase_   :				Optional[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-->'					,	)
					UpperCAmelCase_   :				Union[str, Any]						=						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__":
		__UpperCAmelCase     							=						argparse.ArgumentParser()
		parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
		__UpperCAmelCase     							=						parser.parse_args()

		check_model_table(args.fix_and_overwrite)














from __future__ import annotations




def 					lowercase__				(					__snake_case   :							list[int]					,	__snake_case   :							int  ):


					'''simple docstring'''


					if len(__snake_case  ) == 0:
										return False
					UpperCAmelCase_   :				Optional[int]						=						len(__snake_case  ) // 2
					if a_list[midpoint] == item:
										return True
					if item < a_list[midpoint]:
										return binary_search(a_list[:midpoint]					,	__snake_case  )
					else:
										return binary_search(a_list[midpoint + 1 :]					,	__snake_case  )


if __name__ == "__main__":
		__UpperCAmelCase     							=						input('Enter numbers separated by comma:\n').strip()
		__UpperCAmelCase     							=						[int(item.strip()) for item in user_input.split(',')]
		__UpperCAmelCase     							=						int(input('Enter the number to be found in the list:\n').strip())
		__UpperCAmelCase     							=						'' if binary_search(sequence, target) else 'not '
		print(F'{target} was {not_str}found in {sequence}')






