

import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


a		=logging.get_logger(__name__)

a		={
    """vocab_file""": """vocab.txt""",
    """merges_file""": """bpe.codes""",
}

a		={
    """vocab_file""": {
        """vinai/phobert-base""": """https://huggingface.co/vinai/phobert-base/resolve/main/vocab.txt""",
        """vinai/phobert-large""": """https://huggingface.co/vinai/phobert-large/resolve/main/vocab.txt""",
    },
    """merges_file""": {
        """vinai/phobert-base""": """https://huggingface.co/vinai/phobert-base/resolve/main/bpe.codes""",
        """vinai/phobert-large""": """https://huggingface.co/vinai/phobert-large/resolve/main/bpe.codes""",
    },
}

a		={
    """vinai/phobert-base""": 256,
    """vinai/phobert-large""": 256,
}






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__      )  ->					Optional[Any]:
	__lowerCamelCase    :    List[str] 	=			set()
	__lowerCamelCase    :    int 	=			word[0]
	for char in word[1:]:
		pairs.add((prev_char, char)      )
		__lowerCamelCase    :    Any 	=			char

	__lowerCamelCase    :    Union[str, Any] 	=			set(lowerCamelCase__      )
	return pairs






class 	A_		(	SCREAMING_SNAKE_CASE    ):
							_UpperCAmelCase   :  List[str]										=				VOCAB_FILES_NAMES
							_UpperCAmelCase   :  str										=				PRETRAINED_VOCAB_FILES_MAP
							_UpperCAmelCase   :  str										=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							def __init__(		self		:      List[Any]       ,SCREAMING_SNAKE_CASE__		:      List[Any]       ,SCREAMING_SNAKE_CASE__		:      int       ,SCREAMING_SNAKE_CASE__		:      Any="<s>"       ,SCREAMING_SNAKE_CASE__		:      Dict="</s>"       ,SCREAMING_SNAKE_CASE__		:      int="</s>"       ,SCREAMING_SNAKE_CASE__		:      Dict="<s>"       ,SCREAMING_SNAKE_CASE__		:      Optional[int]="<unk>"       ,SCREAMING_SNAKE_CASE__		:      Dict="<pad>"       ,SCREAMING_SNAKE_CASE__		:      List[str]="<mask>"       ,**SCREAMING_SNAKE_CASE__		:      Any       ,):
								super().__init__(
								    bos_token=SCREAMING_SNAKE_CASE__       ,eos_token=SCREAMING_SNAKE_CASE__       ,unk_token=SCREAMING_SNAKE_CASE__       ,sep_token=SCREAMING_SNAKE_CASE__       ,cls_token=SCREAMING_SNAKE_CASE__       ,pad_token=SCREAMING_SNAKE_CASE__       ,mask_token=SCREAMING_SNAKE_CASE__       ,**SCREAMING_SNAKE_CASE__       ,)

								__lowerCamelCase    :    Tuple 	=			vocab_file
								__lowerCamelCase    :    Any 	=			merges_file

								__lowerCamelCase    :    Optional[int] 	=			{}
								__lowerCamelCase    :    Optional[int] 	=			0
								__lowerCamelCase    :    List[Any] 	=			1
								__lowerCamelCase    :    Any 	=			2
								__lowerCamelCase    :    str 	=			3

								self.add_from_file(SCREAMING_SNAKE_CASE__)

								__lowerCamelCase    :    List[str] 	=			{v: k for k, v in self.encoder.items()}

								with open(SCREAMING_SNAKE_CASE__       ,encoding='utf-8') as merges_handle:
									__lowerCamelCase    :    Tuple 	=			merges_handle.read().split('\n')[:-1]
								__lowerCamelCase    :    int 	=			[tuple(merge.split()[:-1]) for merge in merges]
								__lowerCamelCase    :    Union[str, Any] 	=			dict(zip(SCREAMING_SNAKE_CASE__       ,range(len(SCREAMING_SNAKE_CASE__))))
								__lowerCamelCase    :    Tuple 	=			{}
							def    lowerCAmelCase					(		self		:      Optional[int]       ,SCREAMING_SNAKE_CASE__		:      List[int]       ,SCREAMING_SNAKE_CASE__		:      Optional[List[int]] = None):

								if token_ids_a is None:
									return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								__lowerCamelCase    :    str 	=			[self.cls_token_id]
								__lowerCamelCase    :    List[str] 	=			[self.sep_token_id]
								return cls + token_ids_a + sep + sep + token_ids_a + sep
							def    lowerCAmelCase					(		self		:      int       ,SCREAMING_SNAKE_CASE__		:      List[int]       ,SCREAMING_SNAKE_CASE__		:      Optional[List[int]] = None       ,SCREAMING_SNAKE_CASE__		:      bool = False):

								if already_has_special_tokens:
									return super().get_special_tokens_mask(
									    token_ids_a=SCREAMING_SNAKE_CASE__       ,token_ids_a=SCREAMING_SNAKE_CASE__       ,already_has_special_tokens=SCREAMING_SNAKE_CASE__)

								if token_ids_a is None:
									return [1] + ([0] * len(SCREAMING_SNAKE_CASE__)) + [1]
								return [1] + ([0] * len(SCREAMING_SNAKE_CASE__)) + [1, 1] + ([0] * len(SCREAMING_SNAKE_CASE__)) + [1]
							def    lowerCAmelCase					(		self		:      List[Any]       ,SCREAMING_SNAKE_CASE__		:      List[int]       ,SCREAMING_SNAKE_CASE__		:      Optional[List[int]] = None):
								__lowerCamelCase    :    Any 	=			[self.sep_token_id]
								__lowerCamelCase    :    Optional[int] 	=			[self.cls_token_id]

								if token_ids_a is None:
									return len(cls + token_ids_a + sep) * [0]
								return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]
							@property
							def    lowerCAmelCase					(		self		:      List[Any]):
								return len(self.encoder)
							def    lowerCAmelCase					(		self		:      Any):
								return dict(self.encoder       ,**self.added_tokens_encoder)
							def    lowerCAmelCase					(		self		:      List[Any]       ,SCREAMING_SNAKE_CASE__		:      List[str]):
								if token in self.cache:
									return self.cache[token]
								__lowerCamelCase    :    str 	=			tuple(SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    Dict 	=			tuple(list(word[:-1]) + [word[-1] + '</w>'])
								__lowerCamelCase    :    Optional[int] 	=			get_pairs(SCREAMING_SNAKE_CASE__)

								if not pairs:
									return token

								while True:
									__lowerCamelCase    :    str 	=			min(SCREAMING_SNAKE_CASE__       ,key=lambda SCREAMING_SNAKE_CASE__: self.bpe_ranks.get(SCREAMING_SNAKE_CASE__       ,float('inf')))
									if bigram not in self.bpe_ranks:
										break
									__lowerCamelCase	,			__lowerCamelCase    :    Dict 	=			bigram
									__lowerCamelCase    :    str 	=			[]
									__lowerCamelCase    :    Dict 	=			0
									while i < len(SCREAMING_SNAKE_CASE__):
										try:
											__lowerCamelCase    :    List[Any] 	=			word.index(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
										except ValueError:
											new_word.extend(word[i:])
											break
										else:
											new_word.extend(word[i:j])
											__lowerCamelCase    :    List[str] 	=			j

										if word[i] == first and i < len(SCREAMING_SNAKE_CASE__) - 1 and word[i + 1] == second:
											new_word.append(first + second)
											i += 2
										else:
											new_word.append(word[i])
											i += 1
									__lowerCamelCase    :    List[str] 	=			tuple(SCREAMING_SNAKE_CASE__)
									__lowerCamelCase    :    Any 	=			new_word
									if len(SCREAMING_SNAKE_CASE__) == 1:
										break
									else:
										__lowerCamelCase    :    Any 	=			get_pairs(SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    str 	=			'@@ '.join(SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    Optional[Any] 	=			word[:-4]
								__lowerCamelCase    :    int 	=			word
								return word
							def    lowerCAmelCase					(		self		:      int       ,SCREAMING_SNAKE_CASE__		:      List[str]):
								__lowerCamelCase    :    Tuple 	=			[]

								__lowerCamelCase    :    Tuple 	=			re.findall(R'\S+\n?'       ,SCREAMING_SNAKE_CASE__)

								for token in words:
									split_tokens.extend(list(self.bpe(SCREAMING_SNAKE_CASE__).split(' ')))
								return split_tokens
							def    lowerCAmelCase					(		self		:      Dict       ,SCREAMING_SNAKE_CASE__		:      Optional[int]):
								return self.encoder.get(SCREAMING_SNAKE_CASE__       ,self.encoder.get(self.unk_token))
							def    lowerCAmelCase					(		self		:      Union[str, Any]       ,SCREAMING_SNAKE_CASE__		:      int):
								return self.decoder.get(SCREAMING_SNAKE_CASE__       ,self.unk_token)
							def    lowerCAmelCase					(		self		:      Dict       ,SCREAMING_SNAKE_CASE__		:      Dict):
								__lowerCamelCase    :    Dict 	=			' '.join(SCREAMING_SNAKE_CASE__).replace('@@ '       ,'').strip()
								return out_string
							def    lowerCAmelCase					(		self		:      Tuple       ,SCREAMING_SNAKE_CASE__		:      str       ,SCREAMING_SNAKE_CASE__		:      Optional[str] = None):
								if not os.path.isdir(SCREAMING_SNAKE_CASE__):
									logger.error(F"Vocabulary path ({save_directory}) should be a directory")
									return
								__lowerCamelCase    :    str 	=			os.path.join(
								    SCREAMING_SNAKE_CASE__       ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])
								__lowerCamelCase    :    Tuple 	=			os.path.join(
								    SCREAMING_SNAKE_CASE__       ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file'])

								if os.path.abspath(self.vocab_file) != os.path.abspath(SCREAMING_SNAKE_CASE__):
									copyfile(self.vocab_file       ,SCREAMING_SNAKE_CASE__)

								if os.path.abspath(self.merges_file) != os.path.abspath(SCREAMING_SNAKE_CASE__):
									copyfile(self.merges_file       ,SCREAMING_SNAKE_CASE__)

								return out_vocab_file, out_merge_file


							def    lowerCAmelCase					(		self		:      Union[str, Any]       ,SCREAMING_SNAKE_CASE__		:      Union[str, Any]):
								if isinstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__):
									try:
										with open(SCREAMING_SNAKE_CASE__       ,'r'       ,encoding='utf-8') as fd:
											self.add_from_file(SCREAMING_SNAKE_CASE__)
									except FileNotFoundError as fnfe:
										raise fnfe
									except UnicodeError:
										raise Exception(F"Incorrect encoding detected in {f}, please rebuild the dataset")
									return

								__lowerCamelCase    :    Optional[Any] 	=			f.readlines()
								for lineTmp in lines:
									__lowerCamelCase    :    Union[str, Any] 	=			lineTmp.strip()
									__lowerCamelCase    :    Optional[Any] 	=			line.rfind(' ')
									if idx == -1:
										raise ValueError('Incorrect dictionary format, expected \'<token> <cnt>\'')
									__lowerCamelCase    :    Union[str, Any] 	=			line[:idx]
									__lowerCamelCase    :    Tuple 	=			len(self.encoder)







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		="""src/transformers"""
a		="""docs/source/en"""
a		="""."""






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__     ,			lowerCamelCase__     ,			lowerCamelCase__      )  ->					Optional[int]:
	with open(lowerCamelCase__     ,			'r'     ,			encoding='utf-8'     ,			newline='\n'      ) as f:
		__lowerCamelCase    :    Any 	=			f.readlines()
	# Find the start prompt.
	__lowerCamelCase    :    List[str] 	=			0
	while not lines[start_index].startswith(lowerCamelCase__      ):
		start_index += 1
	start_index += 1

	__lowerCamelCase    :    int 	=			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 |
a		="""Model|Encoder|Decoder|ForConditionalGeneration"""
# Regexes that match TF/Flax/PT model names.
a		=re.compile(r"""TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")
a		=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		=re.compile(r"""(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")


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






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__      )  ->					List[str]:
	__lowerCamelCase    :    int 	=			re.finditer('.+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)'     ,			lowerCamelCase__      )
	return [m.group(0      ) for m in matches]






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__     ,			lowerCamelCase__      )  ->					Tuple:
	__lowerCamelCase    :    int 	=			2 if text == '✅' or text == '❌' else len(lowerCamelCase__      )
	__lowerCamelCase    :    Union[str, Any] 	=			(width - text_length) // 2
	__lowerCamelCase    :    List[Any] 	=			width - text_length - left_indent
	return " " * left_indent + text + " " * right_indent






def        SCREAMING_SNAKE_CASE__	(  )  ->					str:
	__lowerCamelCase    :    Union[str, Any] 	=			transformers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
	__lowerCamelCase    :    List[str] 	=			{
	    name: config_maping_names[code]
	    for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
	    if code in config_maping_names
	}
	__lowerCamelCase    :    Dict 	=			{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.
	__lowerCamelCase    :    Union[str, Any] 	=			collections.defaultdict(lowerCamelCase__      )
	__lowerCamelCase    :    Union[str, Any] 	=			collections.defaultdict(lowerCamelCase__      )
	__lowerCamelCase    :    Union[str, Any] 	=			collections.defaultdict(lowerCamelCase__      )
	__lowerCamelCase    :    List[str] 	=			collections.defaultdict(lowerCamelCase__      )
	__lowerCamelCase    :    Union[str, Any] 	=			collections.defaultdict(lowerCamelCase__      )

	# Let's lookup through all transformers object (once).
	for attr_name in dir(lowerCamelCase__      ):
		__lowerCamelCase    :    List[Any] 	=			None
		if attr_name.endswith('Tokenizer'      ):
			__lowerCamelCase    :    Dict 	=			slow_tokenizers
			__lowerCamelCase    :    List[Any] 	=			attr_name[:-9]
		elif attr_name.endswith('TokenizerFast'      ):
			__lowerCamelCase    :    Union[str, Any] 	=			fast_tokenizers
			__lowerCamelCase    :    str 	=			attr_name[:-1_3]
		elif _re_tf_models.match(lowerCamelCase__      ) is not None:
			__lowerCamelCase    :    List[str] 	=			tf_models
			__lowerCamelCase    :    Optional[int] 	=			_re_tf_models.match(lowerCamelCase__      ).groups()[0]
		elif _re_flax_models.match(lowerCamelCase__      ) is not None:
			__lowerCamelCase    :    List[Any] 	=			flax_models
			__lowerCamelCase    :    Optional[Any] 	=			_re_flax_models.match(lowerCamelCase__      ).groups()[0]
		elif _re_pt_models.match(lowerCamelCase__      ) is not None:
			__lowerCamelCase    :    Optional[int] 	=			pt_models
			__lowerCamelCase    :    Any 	=			_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():
					__lowerCamelCase    :    List[Any] 	=			True
					break
				# Try again after removing the last word in the name
				__lowerCamelCase    :    str 	=			''.join(camel_case_split(lowerCamelCase__      )[:-1]      )

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

	# Build the table per se
	__lowerCamelCase    :    Union[str, Any] 	=			'|' + '|'.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"

	__lowerCamelCase    :    List[str] 	=			{True: '✅', False: '❌'}
	for name in model_names:
		__lowerCamelCase    :    Optional[int] 	=			model_name_to_prefix[name]
		__lowerCamelCase    :    Any 	=			[
		    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        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__=False      )  ->					Any:
	__lowerCamelCase	,			__lowerCamelCase	,			__lowerCamelCase	,			__lowerCamelCase    :    List[str] 	=			_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-->'     ,			)
	__lowerCamelCase    :    List[Any] 	=			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__":
					a		=argparse.ArgumentParser()
					parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
					a		=parser.parse_args()

					check_model_table(args.fix_and_overwrite)




