"""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__      						=  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__      						=  "▁"

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

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

SCREAMING_SNAKE_CASE__      						=  {
    "facebook/nllb-200-distilled-600M": 1_024,
}

# fmt: off
SCREAMING_SNAKE_CASE__      						=  ["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   lowerCAmelCase_    (			a__					):



    """simple docstring"""
    _lowerCAmelCase     :    Tuple			  =						VOCAB_FILES_NAMES
    _lowerCAmelCase     :    List[str]			  =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _lowerCAmelCase     :    Any			  =						PRETRAINED_VOCAB_FILES_MAP
    _lowerCAmelCase     :    Any			  =						["""input_ids""", """attention_mask"""]

    _lowerCAmelCase     :    List[str]			  =						[]
    _lowerCAmelCase     :    str			  =						[]

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






          """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								=			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		,    )

          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>' | '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
          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								=			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]    )

          snake_case								=			src_lang if src_lang is not None else 'eng_Latn'
          snake_case								=			self.lang_code_to_id[self._src_lang]
          snake_case								=			tgt_lang
          self.set_src_lang_special_tokens(self._src_lang    )

    def __getstate__(				self    ):






          """simple docstring"""

          snake_case								=			self.__dict__.copy()
          snake_case								=			None
          snake_case								=			self.sp_model.serialized_model_proto()
          return state

    def __setstate__(				self		,    lowerCAmelCase    ):






          """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.LoadFromSerializedProto(self.sp_model_proto    )

    @property
    def 		snake_case (				self    ):






          """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 		snake_case (				self    ):






          """simple docstring"""

          return self._src_lang

    @src_lang.setter
    def 		snake_case (				self		,    lowerCAmelCase    ):






          """simple docstring"""

          snake_case								=			new_src_lang
          self.set_src_lang_special_tokens(self._src_lang    )

    def 		snake_case (				self		,    lowerCAmelCase		,    lowerCAmelCase = None		,    lowerCAmelCase = False    ):






          """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 		snake_case (				self		,    lowerCAmelCase		,    lowerCAmelCase = None    ):






          """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 		snake_case (				self		,    lowerCAmelCase		,    lowerCAmelCase = None    ):






          """simple docstring"""

          snake_case								=			[self.sep_token_id]
          snake_case								=			[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 		snake_case (				self		,    lowerCAmelCase		,    lowerCAmelCase		,    lowerCAmelCase		,    lowerCAmelCase		,    **lowerCAmelCase    ):






          """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 		snake_case (				self    ):






          """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 		snake_case (				self		,    lowerCAmelCase    ):






          """simple docstring"""

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

    def 		snake_case (				self		,    lowerCAmelCase    ):






          """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 		snake_case (				self		,    lowerCAmelCase    ):






          """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 		snake_case (				self		,    lowerCAmelCase    ):






          """simple docstring"""

          snake_case								=			''.join(_A    ).replace(_A		,    ' '    ).strip()
          return out_string

    def 		snake_case (				self		,    lowerCAmelCase		,    lowerCAmelCase = None    ):






          """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 		snake_case (				self		,    lowerCAmelCase		,    lowerCAmelCase = "eng_Latn"		,    lowerCAmelCase = None		,    lowerCAmelCase = "fra_Latn"		,    **lowerCAmelCase		,    ):






          """simple docstring"""

          snake_case								=			src_lang
          snake_case								=			tgt_lang
          return super().prepare_seqaseq_batch(_A		,    _A		,    **_A    )

    def 		snake_case (				self    ):






          """simple docstring"""

          return self.set_src_lang_special_tokens(self.src_lang    )

    def 		snake_case (				self    ):






          """simple docstring"""

          return self.set_tgt_lang_special_tokens(self.tgt_lang    )

    def 		snake_case (				self		,    lowerCAmelCase    ):






          """simple docstring"""

          snake_case								=			self.lang_code_to_id[src_lang]
          if self.legacy_behaviour:
                snake_case								=			[]
                snake_case								=			[self.eos_token_id, self.cur_lang_code]
          else:
                snake_case								=			[self.cur_lang_code]
                snake_case								=			[self.eos_token_id]

    def 		snake_case (				self		,    lowerCAmelCase    ):






          """simple docstring"""

          snake_case								=			self.lang_code_to_id[lang]
          if self.legacy_behaviour:
                snake_case								=			[]
                snake_case								=			[self.eos_token_id, self.cur_lang_code]
          else:
                snake_case								=			[self.cur_lang_code]
                snake_case								=			[self.eos_token_id]



"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__      						=  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__      						=  {
    "weiweishi/roc-bert-base-zh": "https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json",
}



class   lowerCAmelCase_    (			lowerCAmelCase					):



				"""simple docstring"""
				_lowerCAmelCase     :    Dict			  =						"""roc_bert"""

				def __init__(				self		,    lowerCAmelCase=3_05_22		,    lowerCAmelCase=7_68		,    lowerCAmelCase=12		,    lowerCAmelCase=12		,    lowerCAmelCase=30_72		,    lowerCAmelCase="gelu"		,    lowerCAmelCase=0.1		,    lowerCAmelCase=0.1		,    lowerCAmelCase=5_12		,    lowerCAmelCase=2		,    lowerCAmelCase=0.02		,    lowerCAmelCase=1E-12		,    lowerCAmelCase=True		,    lowerCAmelCase=0		,    lowerCAmelCase="absolute"		,    lowerCAmelCase=None		,    lowerCAmelCase=True		,    lowerCAmelCase=True		,    lowerCAmelCase=7_68		,    lowerCAmelCase=9_10		,    lowerCAmelCase=5_12		,    lowerCAmelCase=2_48_58		,    lowerCAmelCase=True		,    **lowerCAmelCase		,    ):






										"""simple docstring"""

										snake_case								=			vocab_size
										snake_case								=			max_position_embeddings
										snake_case								=			hidden_size
										snake_case								=			num_hidden_layers
										snake_case								=			num_attention_heads
										snake_case								=			intermediate_size
										snake_case								=			hidden_act
										snake_case								=			hidden_dropout_prob
										snake_case								=			attention_probs_dropout_prob
										snake_case								=			initializer_range
										snake_case								=			type_vocab_size
										snake_case								=			layer_norm_eps
										snake_case								=			use_cache
										snake_case								=			enable_pronunciation
										snake_case								=			enable_shape
										snake_case								=			pronunciation_embed_dim
										snake_case								=			pronunciation_vocab_size
										snake_case								=			shape_embed_dim
										snake_case								=			shape_vocab_size
										snake_case								=			concat_input
										snake_case								=			position_embedding_type
										snake_case								=			classifier_dropout
										super().__init__(pad_token_id=lowerCAmelCase		,    **lowerCAmelCase    )


