




'''simple docstring'''





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

import sentencepiece as spm

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


_SCREAMING_SNAKE_CASE							:       Tuple						=			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							:       List[str]						=			"▁"

_SCREAMING_SNAKE_CASE							:       Tuple						=			{"vocab_file": "sentencepiece.bpe.model"}

_SCREAMING_SNAKE_CASE							:       List[Any]						=			{
    "vocab_file": {
        "facebook/mbart-large-50-one-to-many-mmt": (
            "https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model"
        ),
    }
}

_SCREAMING_SNAKE_CASE							:       List[str]						=			{
    "facebook/mbart-large-50-one-to-many-mmt": 1024,
}

# fmt: off
_SCREAMING_SNAKE_CASE							:       Union[str, Any]						=			["ar_AR", "cs_CZ", "de_DE", "en_XX", "es_XX", "et_EE", "fi_FI", "fr_XX", "gu_IN", "hi_IN", "it_IT", "ja_XX", "kk_KZ", "ko_KR", "lt_LT", "lv_LV", "my_MM", "ne_NP", "nl_XX", "ro_RO", "ru_RU", "si_LK", "tr_TR", "vi_VN", "zh_CN", "af_ZA", "az_AZ", "bn_IN", "fa_IR", "he_IL", "hr_HR", "id_ID", "ka_GE", "km_KH", "mk_MK", "ml_IN", "mn_MN", "mr_IN", "pl_PL", "ps_AF", "pt_XX", "sv_SE", "sw_KE", "ta_IN", "te_IN", "th_TH", "tl_XX", "uk_UA", "ur_PK", "xh_ZA", "gl_ES", "sl_SI"]




class 			_snake_case		(     lowercase_							):
			lowerCAmelCase_					:				int							=   VOCAB_FILES_NAMES
			lowerCAmelCase_					:				Optional[Any]							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCAmelCase_					:				Optional[Any]							=   PRETRAINED_VOCAB_FILES_MAP
			lowerCAmelCase_					:				str							=   ["input_ids", "attention_mask"]

			lowerCAmelCase_					:				List[int]							=   []
			lowerCAmelCase_					:				List[int]							=   []




			def __init__( self    ,							a__    ,							a__=None    ,							a__=None    ,							a__="</s>"    ,							a__="</s>"    ,							a__="<s>"    ,							a__="<unk>"    ,							a__="<pad>"    ,							a__="<mask>"    ,							a__ = None    ,							**a__    ,							)    ->    None:

										'''simple docstring'''




										snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else mask_token

										snake_case_      =				{} if sp_model_kwargs is None else sp_model_kwargs

										snake_case_      =				kwargs.get("additional_special_tokens"    ,							[]							)
										kwargs["additional_special_tokens"] += [
										    code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
										]

										super().__init__(
										    src_lang=a__    ,							tgt_lang=a__    ,							eos_token=a__    ,							unk_token=a__    ,							sep_token=a__    ,							cls_token=a__    ,							pad_token=a__    ,							mask_token=a__    ,							sp_model_kwargs=self.sp_model_kwargs    ,							**a__    ,							)

										snake_case_      =				spm.SentencePieceProcessor(**self.sp_model_kwargs							)
										self.sp_model.Load(str(a__							)							)
										snake_case_      =				vocab_file

										# Original fairseq vocab and spm vocab must be "aligned":
										# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
										# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
										# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
										# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

										# Mimic fairseq token-to-id alignment for the first 4 token
										snake_case_      =				{"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

										# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
										snake_case_      =				1

										snake_case_      =				len(self.sp_model							)
										snake_case_      =				{
										    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(a__							)
										}
										snake_case_      =				{v: k for k, v in self.lang_code_to_id.items()}
										snake_case_      =				len(self.sp_model							) + len(self.lang_code_to_id							) + self.fairseq_offset

										self.fairseq_tokens_to_ids.update(self.lang_code_to_id							)
										snake_case_      =				{v: k for k, v in self.fairseq_tokens_to_ids.items()}

										snake_case_      =				src_lang if src_lang is not None else "en_XX"
										snake_case_      =				self.lang_code_to_id[self._src_lang]
										snake_case_      =				tgt_lang
										self.set_src_lang_special_tokens(self._src_lang							)




			@property
			def        lowerCAmelCase__    ( self							)    ->    int:

										'''simple docstring'''




										return len(self.sp_model							) + len(self.lang_code_to_id							) + self.fairseq_offset + 1  # Plus 1 for the mask token




			@property
			def        lowerCAmelCase__    ( self							)    ->    str:

										'''simple docstring'''




										return self._src_lang




			@src_lang.setter
			def        lowerCAmelCase__    ( self    ,							a__							)    ->    None:

										'''simple docstring'''




										snake_case_      =				new_src_lang
										self.set_src_lang_special_tokens(self._src_lang							)




			def __getstate__( self							)    ->    Dict:

										'''simple docstring'''




										snake_case_      =				self.__dict__.copy()
										snake_case_      =				None
										return state




			def __setstate__( self    ,							a__							)    ->    None:

										'''simple docstring'''




										snake_case_      =				d

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

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




			def        lowerCAmelCase__    ( self							)    ->    Dict:

										'''simple docstring'''




										snake_case_      =				{self.convert_ids_to_tokens(a__							): i for i in range(self.vocab_size							)}
										vocab.update(self.added_tokens_encoder							)
										return vocab




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    List[str]:

										'''simple docstring'''




										return self.sp_model.encode(a__    ,							out_type=a__							)




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    int:

										'''simple docstring'''




										if token in self.fairseq_tokens_to_ids:
																	return self.fairseq_tokens_to_ids[token]
										snake_case_      =				self.sp_model.PieceToId(a__							)

										# Need to return unknown token if the SP model returned 0
										return spm_id + self.fairseq_offset if spm_id else self.unk_token_id




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    str:

										'''simple docstring'''




										if index in self.fairseq_ids_to_tokens:
																	return self.fairseq_ids_to_tokens[index]
										return self.sp_model.IdToPiece(index - self.fairseq_offset							)




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    str:

										'''simple docstring'''




										snake_case_      =				[]
										snake_case_      =				""
										snake_case_      =				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
																								snake_case_      =				True
																								snake_case_      =				[]
																	else:
																								current_sub_tokens.append(a__							)
																								snake_case_      =				False
										out_string += self.sp_model.decode(a__							)
										return out_string.strip()




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    Tuple[str]:

										'''simple docstring'''




										if not os.path.isdir(a__							):
																	logger.error(F'Vocabulary path ({save_directory}) should be a directory'							)
																	return
										snake_case_      =				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:
																								snake_case_      =				self.sp_model.serialized_model_proto()
																								fi.write(a__							)

										return (out_vocab_file,)




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None    ,							a__ = False							)    ->    List[int]:

										'''simple docstring'''




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

										snake_case_      =				[1] * len(self.prefix_tokens							)
										snake_case_      =				[1] * len(self.suffix_tokens							)
										if token_ids_a is None:
																	return prefix_ones + ([0] * len(a__							)) + suffix_ones
										return prefix_ones + ([0] * len(a__							)) + ([0] * len(a__							)) + suffix_ones




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    List[int]:

										'''simple docstring'''




										if token_ids_a is None:
																	return self.prefix_tokens + token_ids_a + self.suffix_tokens
										# We don't expect to process pairs, but leave the pair logic for API consistency
										return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__    ,							a__    ,							a__    ,							**a__							)    ->    Union[str, Any]:

										'''simple docstring'''




										if src_lang is None or tgt_lang is None:
																	raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"							)
										snake_case_      =				src_lang
										snake_case_      =				self(a__    ,							add_special_tokens=a__    ,							return_tensors=a__    ,							**a__							)
										snake_case_      =				self.convert_tokens_to_ids(a__							)
										snake_case_      =				tgt_lang_id
										return inputs




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = "en_XX"    ,							a__ = None    ,							a__ = "ro_RO"    ,							**a__    ,							)    ->    BatchEncoding:

										'''simple docstring'''




										snake_case_      =				src_lang
										snake_case_      =				tgt_lang
										return super().prepare_seqaseq_batch(a__    ,							a__    ,							**a__							)




			def        lowerCAmelCase__    ( self							)    ->    List[Any]:

										'''simple docstring'''




										return self.set_src_lang_special_tokens(self.src_lang							)




			def        lowerCAmelCase__    ( self							)    ->    str:

										'''simple docstring'''




										return self.set_tgt_lang_special_tokens(self.tgt_lang							)




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    None:

										'''simple docstring'''




										snake_case_      =				self.lang_code_to_id[src_lang]
										snake_case_      =				[self.cur_lang_code_id]
										snake_case_      =				[self.eos_token_id]




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    None:

										'''simple docstring'''




										snake_case_      =				self.lang_code_to_id[tgt_lang]
										snake_case_      =				[self.cur_lang_code_id]
										snake_case_      =				[self.eos_token_id]











'''simple docstring'''





import argparse
from collections import defaultdict

import yaml


_SCREAMING_SNAKE_CASE							:       Optional[Any]						=			"docs/source/en/_toctree.yml"


def 					UpperCamelCase_(     snake_case							:	Optional[Any]					):

							'''simple docstring'''






							snake_case_      =				defaultdict(snake_case					)
							for doc in model_doc:
														counts[doc["local"]] += 1
							snake_case_      =				[key for key, value in counts.items() if value > 1]

							snake_case_      =				[]
							for duplicate_key in duplicates:
														snake_case_      =				list({doc["title"] for doc in model_doc if doc["local"] == duplicate_key}					)
														if len(snake_case					) > 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(snake_case							,    key=lambda snake_case					: s["title"].lower()					)


def 					UpperCamelCase_(     snake_case							:	Optional[int]=False					):

							'''simple docstring'''






							with open(snake_case							,    encoding="utf-8"					) as f:
														snake_case_      =				yaml.safe_load(f.read()					)

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

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

							snake_case_      =				api_doc[model_idx]["sections"]

							snake_case_      =				[(idx, section) for idx, section in enumerate(snake_case					) if "sections" in section]
							snake_case_      =				False
							for idx, modality_doc in modalities_docs:
														snake_case_      =				modality_doc["sections"]
														snake_case_      =				clean_model_doc_toc(snake_case					)

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

							if diff:
														if overwrite:
																					snake_case_      =				model_doc
																					snake_case_      =				api_doc
																					with open(snake_case							,    "w"							,    encoding="utf-8"					) as f:
																												f.write(yaml.dump(snake_case							,    allow_unicode=snake_case					)					)
														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__":
		_SCREAMING_SNAKE_CASE							:       List[str]						=			argparse.ArgumentParser()
		parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
		_SCREAMING_SNAKE_CASE							:       Any						=			parser.parse_args()

		check_model_doc(args.fix_and_overwrite)




