


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
A			:						List[Any]        =  'src/transformers'
A			:						Dict        =  'docs/source/en'
A			:						int        =  '.'






def 					UpperCamelCase   (      __magic_name__	:				Dict       ,       __magic_name__	:				int       ,       __magic_name__	:				Optional[int]	)  ->    List[Any]:
		"""simple docstring"""




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

		lowercase__	     =						start_index
		while not lines[end_index].startswith(__magic_name__	):
				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 |
A			:						List[Any]        =  'Model|Encoder|Decoder|ForConditionalGeneration'
# Regexes that match TF/Flax/PT model names.
A			:						Optional[int]        =  re.compile(r'TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)')
A			:						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.
A			:						Union[str, Any]        =  re.compile(r'(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)')


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






def 					UpperCamelCase   (      __magic_name__	:				int	)  ->    Dict:
		"""simple docstring"""




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






def 					UpperCamelCase   (      __magic_name__	:				Any       ,       __magic_name__	:				Any	)  ->    Optional[int]:
		"""simple docstring"""




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






def 					UpperCamelCase   (      )  ->    List[Any]:
		"""simple docstring"""




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

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

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

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

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

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






def 					UpperCamelCase   (      __magic_name__	:				Union[str, Any]=False	)  ->    Optional[int]:
		"""simple docstring"""




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

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

	check_model_table(args.fix_and_overwrite)





from __future__ import annotations
def 	_UpperCamelCase					(    lowerCAmelCase_	,    lowerCAmelCase_ )    ->Optional[int]:
   # Checks if the entire collection has been sorted
   if len(lowerCAmelCase_ ) <= 1 or n <= 1:
      return

   insert_next(lowerCAmelCase_	,    n - 1 )
   rec_insertion_sort(lowerCAmelCase_	,    n - 1 )
def 	_UpperCamelCase					(    lowerCAmelCase_	,    lowerCAmelCase_ )    ->Dict:
   # Checks order between adjacent elements
   if index >= len(lowerCAmelCase_ ) or collection[index - 1] <= collection[index]:
      return

   # Swaps adjacent elements since they are not in ascending order
   UpperCAmelCase					,	UpperCAmelCase      					=  (
       collection[index],
       collection[index - 1],
   )

   insert_next(lowerCAmelCase_	,    index + 1 )


if __name__ == "__main__":
 __a	 =      input("""Enter integers separated by spaces: """)
 __a	 =      [int(num) for num in numbers.split()]
 rec_insertion_sort(number_list, len(number_list))
 print(number_list)



