
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowercase__	:Tuple										=					logging.get_logger(__name__)
lowercase__	:str										=					{"vocab_file": "spiece.model"}

lowercase__	:List[str]										=					{
    "vocab_file": {
        "albert-base-v1": "https://huggingface.co/albert-base-v1/resolve/main/spiece.model",
        "albert-large-v1": "https://huggingface.co/albert-large-v1/resolve/main/spiece.model",
        "albert-xlarge-v1": "https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model",
        "albert-xxlarge-v1": "https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model",
        "albert-base-v2": "https://huggingface.co/albert-base-v2/resolve/main/spiece.model",
        "albert-large-v2": "https://huggingface.co/albert-large-v2/resolve/main/spiece.model",
        "albert-xlarge-v2": "https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model",
        "albert-xxlarge-v2": "https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model",
    }
}

lowercase__	:int										=					{
    "albert-base-v1": 512,
    "albert-large-v1": 512,
    "albert-xlarge-v1": 512,
    "albert-xxlarge-v1": 512,
    "albert-base-v2": 512,
    "albert-large-v2": 512,
    "albert-xlarge-v2": 512,
    "albert-xxlarge-v2": 512,
}

lowercase__	:Optional[Any]										=					"▁"







class        lowercase	(      SCREAMING_SNAKE_CASE__	):
							lowercase_ : Optional[int]       =VOCAB_FILES_NAMES
							lowercase_ : List[str]       =PRETRAINED_VOCAB_FILES_MAP
							lowercase_ : Optional[Any]       =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES




							def __init__(       self     ,A__     ,A__=True     ,A__=True     ,A__=False     ,A__="[CLS]"     ,A__="[SEP]"     ,A__="<unk>"     ,A__="[SEP]"     ,A__="<pad>"     ,A__="[CLS]"     ,A__="[MASK]"     ,A__ = None     ,**A__     ,):
												# Mask token behave like a normal word, i.e. include the space before it and
												# is included in the raw text, there should be a match in a non-normalized sentence.
												lowercase					=		(
												    AddedToken(A__     ,lstrip=A__     ,rstrip=A__     ,normalized=A__)
												    if isinstance(A__     ,A__)
												    else mask_token
												)

												lowercase					=		{} if sp_model_kwargs is None else sp_model_kwargs

												super().__init__(
												    do_lower_case=A__     ,remove_space=A__     ,keep_accents=A__     ,bos_token=A__     ,eos_token=A__     ,unk_token=A__     ,sep_token=A__     ,pad_token=A__     ,cls_token=A__     ,mask_token=A__     ,sp_model_kwargs=self.sp_model_kwargs     ,**A__     ,)

												lowercase					=		do_lower_case
												lowercase					=		remove_space
												lowercase					=		keep_accents
												lowercase					=		vocab_file

												lowercase					=		spm.SentencePieceProcessor(**self.sp_model_kwargs)
												self.sp_model.Load(A__)




							@property
							def 				A__   (       self):
												return len(self.sp_model)




							def 				A__   (       self):
												lowercase					=		{self.convert_ids_to_tokens(A__): i for i in range(self.vocab_size)}
												vocab.update(self.added_tokens_encoder)
												return vocab




							def __getstate__(       self):
												lowercase					=		self.__dict__.copy()
												lowercase					=		None
												return state




							def __setstate__(       self     ,A__):
												lowercase					=		d

												# for backward compatibility
												if not hasattr(self     ,'''sp_model_kwargs'''):
																	lowercase					=		{}

												lowercase					=		spm.SentencePieceProcessor(**self.sp_model_kwargs)
												self.sp_model.Load(self.vocab_file)




							def 				A__   (       self     ,A__):
												if self.remove_space:
																	lowercase					=		''' '''.join(inputs.strip().split())
												else:
																	lowercase					=		inputs
												lowercase					=		outputs.replace('''``'''     ,'''"''').replace('''\'\''''     ,'''"''')

												if not self.keep_accents:
																	lowercase					=		unicodedata.normalize('''NFKD'''     ,A__)
																	lowercase					=		''''''.join([c for c in outputs if not unicodedata.combining(A__)])
												if self.do_lower_case:
																	lowercase					=		outputs.lower()

												return outputs




							def 				A__   (       self     ,A__):
												lowercase					=		self.preprocess_text(A__)
												lowercase					=		self.sp_model.encode(A__     ,out_type=A__)
												lowercase					=		[]
												for piece in pieces:
																	if len(A__) > 1 and piece[-1] == str(''',''') and piece[-2].isdigit():
																						lowercase					=		self.sp_model.EncodeAsPieces(piece[:-1].replace(A__     ,''''''))
																						if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																											if len(cur_pieces[0]) == 1:
																																lowercase					=		cur_pieces[1:]
																											else:
																																lowercase					=		cur_pieces[0][1:]
																						cur_pieces.append(piece[-1])
																						new_pieces.extend(A__)
																	else:
																						new_pieces.append(A__)

												return new_pieces




							def 				A__   (       self     ,A__):
												return self.sp_model.PieceToId(A__)




							def 				A__   (       self     ,A__):
												return self.sp_model.IdToPiece(A__)




							def 				A__   (       self     ,A__):
												lowercase					=		[]
												lowercase					=		''''''
												lowercase					=		False
												for token in tokens:
																	# make sure that special tokens are not decoded using sentencepiece model
																	if token in self.all_special_tokens:
																						if not prev_is_special:
																											out_string += " "
																						out_string += self.sp_model.decode(A__) + token
																						lowercase					=		True
																						lowercase					=		[]
																	else:
																						current_sub_tokens.append(A__)
																						lowercase					=		False
												out_string += self.sp_model.decode(A__)
												return out_string.strip()




							def 				A__   (       self     ,A__     ,A__ = None):
												lowercase					=		[self.sep_token_id]
												lowercase					=		[self.cls_token_id]
												if token_ids_a is None:
																	return cls + token_ids_a + sep
												return cls + token_ids_a + sep + token_ids_a + sep




							def 				A__   (       self     ,A__     ,A__ = None     ,A__ = False):

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

												if token_ids_a is not None:
																	return [1] + ([0] * len(A__)) + [1] + ([0] * len(A__)) + [1]
												return [1] + ([0] * len(A__)) + [1]




							def 				A__   (       self     ,A__     ,A__ = None):
												lowercase					=		[self.sep_token_id]
												lowercase					=		[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) * [0] + len(token_ids_a + sep) * [1]





							def 				A__   (       self     ,A__     ,A__ = None):
												if not os.path.isdir(A__):
																	logger.error(f'Vocabulary path ({save_directory}) should be a directory')
																	return
												lowercase					=		os.path.join(
												    A__     ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''])

												if os.path.abspath(self.vocab_file) != os.path.abspath(A__) and os.path.isfile(self.vocab_file):
																	copyfile(self.vocab_file     ,A__)
												elif not os.path.isfile(self.vocab_file):
																	with open(A__     ,'''wb''') as fi:
																						lowercase					=		self.sp_model.serialized_model_proto()
																						fi.write(A__)

												return (out_vocab_file,)






import argparse
from collections import defaultdict

import yaml


lowercase__	:Optional[int]										=					"docs/source/en/_toctree.yml"



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					lowercase					=		defaultdict(lowerCAmelCase__	)
					for doc in model_doc:
										counts[doc["local"]] += 1
					lowercase					=		[key for key, value in counts.items() if value > 1]

					lowercase					=		[]
					for duplicate_key in duplicates:
										lowercase					=		list({doc['''title'''] for doc in model_doc if doc['''local'''] == duplicate_key}	)
										if len(lowerCAmelCase__	) > 1:
															raise ValueError(
															    f'{duplicate_key} is present several times in the documentation table of content at '
															    '''`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the '''
															    '''others.'''	)
										# Only add this once
										new_doc.append({'''local''': duplicate_key, '''title''': titles[0]}	)

					# Add none duplicate-keys
					new_doc.extend([doc for doc in model_doc if counts[doc['''local''']] == 1]	)

					# Sort
					return sorted(lowerCAmelCase__				,    key=lambda lowerCAmelCase__	: s["title"].lower()	)



def  UpperCamelCase					(							lowerCAmelCase__=False	):
					'''simple docstring'''
					with open(lowerCAmelCase__				,    encoding='''utf-8'''	) as f:
										lowercase					=		yaml.safe_load(f.read()	)

					# Get to the API doc
					lowercase					=		0
					while content[api_idx]["title"] != "API":
										api_idx += 1
					lowercase					=		content[api_idx]['''sections''']

					# Then to the model doc
					lowercase					=		0
					while api_doc[model_idx]["title"] != "Models":
										model_idx += 1

					lowercase					=		api_doc[model_idx]['''sections''']

					lowercase					=		[(idx, section) for idx, section in enumerate(lowerCAmelCase__	) if '''sections''' in section]
					lowercase					=		False
					for idx, modality_doc in modalities_docs:
										lowercase					=		modality_doc['''sections''']
										lowercase					=		clean_model_doc_toc(lowerCAmelCase__	)

										if old_modality_doc != new_modality_doc:
															lowercase					=		True
															if overwrite:
																				lowercase					=		new_modality_doc

					if diff:
										if overwrite:
															lowercase					=		model_doc
															lowercase					=		api_doc
															with open(lowerCAmelCase__				,    '''w'''				,    encoding='''utf-8'''	) as f:
																				f.write(yaml.dump(lowerCAmelCase__				,    allow_unicode=lowerCAmelCase__	)	)
										else:
															raise ValueError(
															    '''The model doc part of the table of content is not properly sorted, run `make style` to fix this.'''	)


if __name__ == "__main__":
							lowercase__	:Any										=					argparse.ArgumentParser()
							parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
							lowercase__	:int										=					parser.parse_args()

							check_model_doc(args.fix_and_overwrite)




