

"""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


__A						   =			logging.get_logger(__name__)

__A						   =			"▁"

__A						   =			{"vocab_file": "sentencepiece.bpe.model"}

__A						   =			{
    "vocab_file": {
        "facebook/nllb-200-distilled-600M": (
            "https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model"
        ),
    }
}

__A						   =			{
    "facebook/nllb-200-distilled-600M": 1024,
}

# fmt: off
__A						   =			["ace_Arab", "ace_Latn", "acm_Arab", "acq_Arab", "aeb_Arab", "afr_Latn", "ajp_Arab", "aka_Latn", "amh_Ethi", "apc_Arab", "arb_Arab", "ars_Arab", "ary_Arab", "arz_Arab", "asm_Beng", "ast_Latn", "awa_Deva", "ayr_Latn", "azb_Arab", "azj_Latn", "bak_Cyrl", "bam_Latn", "ban_Latn", "bel_Cyrl", "bem_Latn", "ben_Beng", "bho_Deva", "bjn_Arab", "bjn_Latn", "bod_Tibt", "bos_Latn", "bug_Latn", "bul_Cyrl", "cat_Latn", "ceb_Latn", "ces_Latn", "cjk_Latn", "ckb_Arab", "crh_Latn", "cym_Latn", "dan_Latn", "deu_Latn", "dik_Latn", "dyu_Latn", "dzo_Tibt", "ell_Grek", "eng_Latn", "epo_Latn", "est_Latn", "eus_Latn", "ewe_Latn", "fao_Latn", "pes_Arab", "fij_Latn", "fin_Latn", "fon_Latn", "fra_Latn", "fur_Latn", "fuv_Latn", "gla_Latn", "gle_Latn", "glg_Latn", "grn_Latn", "guj_Gujr", "hat_Latn", "hau_Latn", "heb_Hebr", "hin_Deva", "hne_Deva", "hrv_Latn", "hun_Latn", "hye_Armn", "ibo_Latn", "ilo_Latn", "ind_Latn", "isl_Latn", "ita_Latn", "jav_Latn", "jpn_Jpan", "kab_Latn", "kac_Latn", "kam_Latn", "kan_Knda", "kas_Arab", "kas_Deva", "kat_Geor", "knc_Arab", "knc_Latn", "kaz_Cyrl", "kbp_Latn", "kea_Latn", "khm_Khmr", "kik_Latn", "kin_Latn", "kir_Cyrl", "kmb_Latn", "kon_Latn", "kor_Hang", "kmr_Latn", "lao_Laoo", "lvs_Latn", "lij_Latn", "lim_Latn", "lin_Latn", "lit_Latn", "lmo_Latn", "ltg_Latn", "ltz_Latn", "lua_Latn", "lug_Latn", "luo_Latn", "lus_Latn", "mag_Deva", "mai_Deva", "mal_Mlym", "mar_Deva", "min_Latn", "mkd_Cyrl", "plt_Latn", "mlt_Latn", "mni_Beng", "khk_Cyrl", "mos_Latn", "mri_Latn", "zsm_Latn", "mya_Mymr", "nld_Latn", "nno_Latn", "nob_Latn", "npi_Deva", "nso_Latn", "nus_Latn", "nya_Latn", "oci_Latn", "gaz_Latn", "ory_Orya", "pag_Latn", "pan_Guru", "pap_Latn", "pol_Latn", "por_Latn", "prs_Arab", "pbt_Arab", "quy_Latn", "ron_Latn", "run_Latn", "rus_Cyrl", "sag_Latn", "san_Deva", "sat_Beng", "scn_Latn", "shn_Mymr", "sin_Sinh", "slk_Latn", "slv_Latn", "smo_Latn", "sna_Latn", "snd_Arab", "som_Latn", "sot_Latn", "spa_Latn", "als_Latn", "srd_Latn", "srp_Cyrl", "ssw_Latn", "sun_Latn", "swe_Latn", "swh_Latn", "szl_Latn", "tam_Taml", "tat_Cyrl", "tel_Telu", "tgk_Cyrl", "tgl_Latn", "tha_Thai", "tir_Ethi", "taq_Latn", "taq_Tfng", "tpi_Latn", "tsn_Latn", "tso_Latn", "tuk_Latn", "tum_Latn", "tur_Latn", "twi_Latn", "tzm_Tfng", "uig_Arab", "ukr_Cyrl", "umb_Latn", "urd_Arab", "uzn_Latn", "vec_Latn", "vie_Latn", "war_Latn", "wol_Latn", "xho_Latn", "ydd_Hebr", "yor_Latn", "yue_Hant", "zho_Hans", "zho_Hant", "zul_Latn"]





class     snake_case	(				a_  ):
				SCREAMING_SNAKE_CASE_   :      Tuple         =  VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_   :      Any         =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_   :      str         =  PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_   :      Dict         =  ["""input_ids""", """attention_mask"""]

				SCREAMING_SNAKE_CASE_   :      str         =  []
				SCREAMING_SNAKE_CASE_   :      Tuple         =  []

				def __init__(	self							:				str     ,  UpperCamelCase__							:				Tuple     ,  UpperCamelCase__							:				List[Any]="<s>"     ,  UpperCamelCase__							:				Optional[Any]="</s>"     ,  UpperCamelCase__							:				int="</s>"     ,  UpperCamelCase__							:				List[Any]="<s>"     ,  UpperCamelCase__							:				str="<unk>"     ,  UpperCamelCase__							:				Dict="<pad>"     ,  UpperCamelCase__							:				str="<mask>"     ,  UpperCamelCase__							:				str=None     ,  UpperCamelCase__							:				Optional[int]=None     ,  UpperCamelCase__							:				List[str]=None     ,  UpperCamelCase__							:				Dict = None     ,  UpperCamelCase__							:				Optional[Any]=None     ,  UpperCamelCase__							:				Any=False     ,  **UpperCamelCase__							:				int     ,  )->   List[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[int]          =			AddedToken(_A     ,  lstrip=_A     ,  rstrip=_A) if isinstance(_A     ,  _A) else mask_token

						__lowerCAmelCase:       Optional[int]          =			{} if sp_model_kwargs is None else sp_model_kwargs
						__lowerCAmelCase:       List[str]          =			legacy_behaviour

						super().__init__(
						    bos_token=_A     ,  eos_token=_A     ,  unk_token=_A     ,  sep_token=_A     ,  cls_token=_A     ,  pad_token=_A     ,  mask_token=_A     ,  tokenizer_file=_A     ,  src_lang=_A     ,  tgt_lang=_A     ,  additional_special_tokens=_A     ,  sp_model_kwargs=self.sp_model_kwargs     ,  legacy_behaviour=_A     ,  **_A     ,  )

						__lowerCAmelCase:       int          =			spm.SentencePieceProcessor(**self.sp_model_kwargs)
						self.sp_model.Load(str(_A))
						__lowerCAmelCase:       str          =			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>' | 'an' | '▁n' | '▁m' | '▁t' | '▁k' | '▁a'
						# spm      | '<unk>' | '<s>'   | '</s>' | 'an'    | '▁n' | '▁m' | '▁t' | '▁k' | '▁a' | '▁s'

						# Mimic fairseq token-to-id alignment for the first 4 token
						__lowerCAmelCase:       Tuple          =			{"<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
						__lowerCAmelCase:       int          =			1

						__lowerCAmelCase:       Optional[int]          =			len(self.sp_model)
						__lowerCAmelCase:       Union[str, Any]          =			{
						    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(_A)
						}
						__lowerCAmelCase:       Dict          =			{v: k for k, v in self.lang_code_to_id.items()}
						__lowerCAmelCase:       Optional[int]          =			len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset

						self.fairseq_tokens_to_ids.update(self.lang_code_to_id)
						__lowerCAmelCase:       Union[str, Any]          =			{v: k for k, v in self.fairseq_tokens_to_ids.items()}
						__lowerCAmelCase:       Optional[int]          =			list(self.lang_code_to_id.keys())

						if additional_special_tokens is not None:
								# Only add those special tokens if they are not already there.
								self._additional_special_tokens.extend(
								    [t for t in additional_special_tokens if t not in self._additional_special_tokens])

						__lowerCAmelCase:       str          =			src_lang if src_lang is not None else "eng_Latn"
						__lowerCAmelCase:       Tuple          =			self.lang_code_to_id[self._src_lang]
						__lowerCAmelCase:       Optional[int]          =			tgt_lang
						self.set_src_lang_special_tokens(self._src_lang)

				def __getstate__(	self							:				List[Any])->   Union[str, Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Union[str, Any]          =			self.__dict__.copy()
						__lowerCAmelCase:       Tuple          =			None
						__lowerCAmelCase:       List[str]          =			self.sp_model.serialized_model_proto()
						return state

				def __setstate__(	self							:				Dict     ,  UpperCamelCase__							:				Optional[int])->   Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			d

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

						__lowerCAmelCase:       List[str]          =			spm.SentencePieceProcessor(**self.sp_model_kwargs)
						self.sp_model.LoadFromSerializedProto(self.sp_model_proto)

				@property
				def 							lowercase_     (	self							:				Any)->   Optional[Any]:



						'''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 							lowercase_     (	self							:				Union[str, Any])->   List[str]:



						'''simple docstring'''


						return self._src_lang

				@src_lang.setter
				def 							lowercase_     (	self							:				Optional[int]     ,  UpperCamelCase__							:				Optional[int])->   Union[str, Any]:



						'''simple docstring'''


						__lowerCAmelCase:       List[Any]          =			new_src_lang
						self.set_src_lang_special_tokens(self._src_lang)

				def 							lowercase_     (	self							:				str     ,  UpperCamelCase__							:				Optional[int]     ,  UpperCamelCase__							:				str = None     ,  UpperCamelCase__							:				List[Any] = False)->   List[Any]:



						'''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)

						__lowerCAmelCase:       int          =			[1] * len(self.prefix_tokens)
						__lowerCAmelCase:       Dict          =			[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 							lowercase_     (	self							:				List[str]     ,  UpperCamelCase__							:				Dict     ,  UpperCamelCase__							:				Optional[Any] = None)->   Any:



						'''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 							lowercase_     (	self							:				str     ,  UpperCamelCase__							:				Tuple     ,  UpperCamelCase__							:				Optional[int] = None)->   Tuple:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[Any]          =			[self.sep_token_id]
						__lowerCAmelCase:       Optional[Any]          =			[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]

				def 							lowercase_     (	self							:				int     ,  UpperCamelCase__							:				Dict     ,  UpperCamelCase__							:				str     ,  UpperCamelCase__							:				Optional[int]     ,  UpperCamelCase__							:				Tuple     ,  **UpperCamelCase__							:				Union[str, Any])->   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")
						__lowerCAmelCase:       Dict          =			src_lang
						__lowerCAmelCase:       Optional[Any]          =			self(_A     ,  add_special_tokens=_A     ,  return_tensors=_A     ,  **_A)
						__lowerCAmelCase:       Union[str, Any]          =			self.convert_tokens_to_ids(_A)
						__lowerCAmelCase:       Dict          =			tgt_lang_id
						return inputs

				def 							lowercase_     (	self							:				List[str])->   Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       str          =			{self.convert_ids_to_tokens(_A): i for i in range(self.vocab_size)}
						vocab.update(self.added_tokens_encoder)
						return vocab

				def 							lowercase_     (	self							:				Any     ,  UpperCamelCase__							:				Tuple)->   Optional[int]:



						'''simple docstring'''


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

				def 							lowercase_     (	self							:				Optional[int]     ,  UpperCamelCase__							:				int)->   Union[str, Any]:



						'''simple docstring'''


						if token in self.fairseq_tokens_to_ids:
								return self.fairseq_tokens_to_ids[token]
						__lowerCAmelCase:       List[Any]          =			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 							lowercase_     (	self							:				str     ,  UpperCamelCase__							:				Optional[Any])->   Union[str, Any]:



						'''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 							lowercase_     (	self							:				Optional[Any]     ,  UpperCamelCase__							:				Dict)->   Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Dict          =			"".join(_A).replace(_A     ,  " ").strip()
						return out_string

				def 							lowercase_     (	self							:				Union[str, Any]     ,  UpperCamelCase__							:				Any     ,  UpperCamelCase__							:				Dict = None)->   Optional[Any]:



						'''simple docstring'''


						if not os.path.isdir(_A):
								logger.error(f"Vocabulary path ({save_directory}) should be a directory")
								return
						__lowerCAmelCase:       Tuple          =			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:
										__lowerCAmelCase:       str          =			self.sp_model.serialized_model_proto()
										fi.write(_A)

						return (out_vocab_file,)

				def 							lowercase_     (	self							:				str     ,  UpperCamelCase__							:				Optional[Any]     ,  UpperCamelCase__							:				Dict = "eng_Latn"     ,  UpperCamelCase__							:				Dict = None     ,  UpperCamelCase__							:				Tuple = "fra_Latn"     ,  **UpperCamelCase__							:				Optional[int]     ,  )->   Union[str, Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			src_lang
						__lowerCAmelCase:       Optional[Any]          =			tgt_lang
						return super().prepare_seqaseq_batch(_A     ,  _A     ,  **_A)

				def 							lowercase_     (	self							:				List[str])->   str:



						'''simple docstring'''


						return self.set_src_lang_special_tokens(self.src_lang)

				def 							lowercase_     (	self							:				Optional[Any])->   int:



						'''simple docstring'''


						return self.set_tgt_lang_special_tokens(self.tgt_lang)

				def 							lowercase_     (	self							:				Any     ,  UpperCamelCase__							:				Any)->   List[str]:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			self.lang_code_to_id[src_lang]
						if self.legacy_behaviour:
								__lowerCAmelCase:       str          =			[]
								__lowerCAmelCase:       Tuple          =			[self.eos_token_id, self.cur_lang_code]
						else:
								__lowerCAmelCase:       str          =			[self.cur_lang_code]
								__lowerCAmelCase:       int          =			[self.eos_token_id]




				def 							lowercase_     (	self							:				str     ,  UpperCamelCase__							:				Any)->   Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Any          =			self.lang_code_to_id[lang]
						if self.legacy_behaviour:
								__lowerCAmelCase:       Union[str, Any]          =			[]
								__lowerCAmelCase:       List[str]          =			[self.eos_token_id, self.cur_lang_code]
						else:
								__lowerCAmelCase:       Any          =			[self.cur_lang_code]
								__lowerCAmelCase:       Dict          =			[self.eos_token_id]









from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__A				:    int       =   logging.get_logger(__name__)

__A				:    Tuple       =   {
    "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json",
    "google/bigbird-roberta-large": "https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json",
    "google/bigbird-base-trivia-itc": "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json",
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}

class 	A_       (a_			):
	UpperCAmelCase__					=			'''big_bird'''
	def __init__(    self							,					_A=5_0_3_5_8							,					_A=7_6_8							,					_A=1_2							,					_A=1_2							,					_A=3_0_7_2							,					_A="gelu_new"							,					_A=0.1							,					_A=0.1							,					_A=4_0_9_6							,					_A=2							,					_A=0.02							,					_A=1E-12							,					_A=True							,					_A=0							,					_A=1							,					_A=2							,					_A=6_6							,					_A="block_sparse"							,					_A=True							,					_A=False							,					_A=6_4							,					_A=3							,					_A=None							,					**_A							,					):






				'''simple docstring'''







				super().__init__(
				    pad_token_id=_A							,					bos_token_id=_A							,					eos_token_id=_A							,					sep_token_id=_A							,					**_A							,					)

				UpperCAmelCase   		=				vocab_size
				UpperCAmelCase   		=				max_position_embeddings
				UpperCAmelCase   		=				hidden_size
				UpperCAmelCase   		=				num_hidden_layers
				UpperCAmelCase   		=				num_attention_heads
				UpperCAmelCase   		=				intermediate_size
				UpperCAmelCase   		=				hidden_act
				UpperCAmelCase   		=				hidden_dropout_prob
				UpperCAmelCase   		=				attention_probs_dropout_prob
				UpperCAmelCase   		=				initializer_range
				UpperCAmelCase   		=				type_vocab_size
				UpperCAmelCase   		=				layer_norm_eps
				UpperCAmelCase   		=				use_cache

				UpperCAmelCase   		=				rescale_embeddings
				UpperCAmelCase   		=				attention_type
				UpperCAmelCase   		=				use_bias
				UpperCAmelCase   		=				block_size
				UpperCAmelCase   		=				num_random_blocks
				UpperCAmelCase   		=				classifier_dropout

class 	A_       (a_			):
	@property
	def      _lowercase				(    self		):






				'''simple docstring'''







				if self.task == "multiple-choice":
							UpperCAmelCase   		=				{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
				else:
							UpperCAmelCase   		=				{0: '''batch''', 1: '''sequence'''}
				return OrderedDict(
				    [
				        ('''input_ids''', dynamic_axis),
				        ('''attention_mask''', dynamic_axis),
				    ]		)



