


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	:		Tuple    =       'docs/source/en'
A	:		Optional[int]    =       '.'






def 			UpperCamelCase (     __magic_name__					:							List[Any]   ,   __magic_name__					:							int   ,   __magic_name__					:							int					):
		"""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	:		Dict    =       'Model|Encoder|Decoder|ForConditionalGeneration'
# Regexes that match TF/Flax/PT model names.
A	:		List[str]    =       re.compile(r'TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)')
A	:		Optional[Any]    =       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	:		str    =       re.compile(r'(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)')


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






def 			UpperCamelCase (     __magic_name__					:							Optional[int]					):
		"""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__					:							Dict   ,   __magic_name__					:							Optional[Any]					):
		"""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 (     ):
		"""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					):
		"""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	:		Optional[int]    =       argparse.ArgumentParser()
	parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
	A	:		List[Any]    =       parser.parse_args()

	check_model_table(args.fix_and_overwrite)





A	:		Tuple    =       'ABCDEFGHIJKLMNOPQRSTUVWXYZ'






def 			UpperCamelCase (     )       ->  None:
		"""simple docstring"""




		lowercase__					      =		input("""Enter message: """					)
		lowercase__					      =		input("""Enter key [alphanumeric]: """					)
		lowercase__					      =		input("""Encrypt/Decrypt [e/d]: """					)

		if mode.lower().startswith("""e"""					):
				lowercase__					      =		"""encrypt"""
				lowercase__					      =		encrypt_message(__magic_name__   ,   __magic_name__					)
		elif mode.lower().startswith("""d"""					):
				lowercase__					      =		"""decrypt"""
				lowercase__					      =		decrypt_message(__magic_name__   ,   __magic_name__					)

		print(f'''\n{mode.title()}ed message:'''					)
		print(__magic_name__					)






def 			UpperCamelCase (     __magic_name__					:							str   ,   __magic_name__					:							str					)       ->  str:
		"""simple docstring"""




		return translate_message(__magic_name__   ,   __magic_name__   ,   """encrypt"""					)






def 			UpperCamelCase (     __magic_name__					:							str   ,   __magic_name__					:							str					)       ->  str:
		"""simple docstring"""




		return translate_message(__magic_name__   ,   __magic_name__   ,   """decrypt"""					)






def 			UpperCamelCase (     __magic_name__					:							str   ,   __magic_name__					:							str   ,   __magic_name__					:							str					)       ->  str:
		"""simple docstring"""




		lowercase__					      =		[]
		lowercase__					      =		0
		lowercase__					      =		key.upper()

		for symbol in message:
				lowercase__					      =		LETTERS.find(symbol.upper()					)
				if num != -1:
						if mode == "encrypt":
								num += LETTERS.find(key[key_index]					)
						elif mode == "decrypt":
								num -= LETTERS.find(key[key_index]					)

						num %= len(__magic_name__					)

						if symbol.isupper():
								translated.append(LETTERS[num]					)
						elif symbol.islower():
								translated.append(LETTERS[num].lower()					)

						key_index += 1
						if key_index == len(__magic_name__					):
								lowercase__					      =		0
				else:
						translated.append(__magic_name__					)
		return "".join(__magic_name__					)


if __name__ == "__main__":
	main()

