
"""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


lowerCAmelCase__							=				logging.get_logger(__name__)

lowerCAmelCase__							=				'▁'

lowerCAmelCase__							=				{'vocab_file': 'sentencepiece.bpe.model'}

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

lowerCAmelCase__							=				{
    'facebook/nllb-200-distilled-600M': 1024,
}

# fmt: off
lowerCAmelCase__							=				['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     (							__lowercase   ):
							UpperCAmelCase__						     =      VOCAB_FILES_NAMES
							UpperCAmelCase__						     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							UpperCAmelCase__						     =      PRETRAINED_VOCAB_FILES_MAP
							UpperCAmelCase__						     =      ['''input_ids''', '''attention_mask''']

							UpperCAmelCase__						     =      []
							UpperCAmelCase__						     =      []

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

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = AddedToken(SCREAMING_SNAKE_CASE_       ,       lstrip=SCREAMING_SNAKE_CASE_       ,       rstrip=SCREAMING_SNAKE_CASE_    ) if isinstance(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ) else mask_token

									SCREAMING_SNAKE_CASE_						 = {} if sp_model_kwargs is None else sp_model_kwargs
									SCREAMING_SNAKE_CASE_						 = legacy_behaviour

									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_       ,       tokenizer_file=SCREAMING_SNAKE_CASE_       ,       src_lang=SCREAMING_SNAKE_CASE_       ,       tgt_lang=SCREAMING_SNAKE_CASE_       ,       additional_special_tokens=SCREAMING_SNAKE_CASE_       ,       sp_model_kwargs=self.sp_model_kwargs       ,       legacy_behaviour=SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_       ,       )

									SCREAMING_SNAKE_CASE_						 = spm.SentencePieceProcessor(**self.sp_model_kwargs    )
									self.sp_model.Load(str(SCREAMING_SNAKE_CASE_    )    )
									SCREAMING_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
									SCREAMING_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
									SCREAMING_SNAKE_CASE_						 = 1

									SCREAMING_SNAKE_CASE_						 = len(self.sp_model    )
									SCREAMING_SNAKE_CASE_						 = {
									    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(SCREAMING_SNAKE_CASE_    )
									}
									SCREAMING_SNAKE_CASE_						 = {v: k for k, v in self.lang_code_to_id.items()}
									SCREAMING_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    )
									SCREAMING_SNAKE_CASE_						 = {v: k for k, v in self.fairseq_tokens_to_ids.items()}
									SCREAMING_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]    )

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

							def __getstate__(self    ):

									"""simple docstring"""







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

							def __setstate__(self       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = d

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

									SCREAMING_SNAKE_CASE_						 = spm.SentencePieceProcessor(**self.sp_model_kwargs    )
									self.sp_model.LoadFromSerializedProto(self.sp_model_proto    )

							@property
							def _lowercase					(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 _lowercase					(self    ):

									"""simple docstring"""







									return self._src_lang

							@src_lang.setter
							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = new_src_lang
									self.set_src_lang_special_tokens(self._src_lang    )

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = False    ):

									"""simple docstring"""







									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_    )

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

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_ = 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 _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_ = None    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = [self.sep_token_id]
									SCREAMING_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 _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_    ):

									"""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'''    )
									SCREAMING_SNAKE_CASE_						 = src_lang
									SCREAMING_SNAKE_CASE_						 = self(SCREAMING_SNAKE_CASE_       ,       add_special_tokens=SCREAMING_SNAKE_CASE_       ,       return_tensors=SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = tgt_lang_id
									return inputs

							def _lowercase					(self    ):

									"""simple docstring"""







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

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







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

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







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

									# 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       ,       SCREAMING_SNAKE_CASE_    ):

									"""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       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = ''''''.join(SCREAMING_SNAKE_CASE_    ).replace(SCREAMING_SNAKE_CASE_       ,       ''' '''    ).strip()
									return out_string

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_ = None    ):

									"""simple docstring"""







									if not os.path.isdir(SCREAMING_SNAKE_CASE_    ):
											logger.error(f'Vocabulary path ({save_directory}) should be a directory'    )
											return
									SCREAMING_SNAKE_CASE_						 = os.path.join(
									    SCREAMING_SNAKE_CASE_       ,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']    )

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

									return (out_vocab_file,)

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_ = "eng_Latn"       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = "fra_Latn"       ,       **SCREAMING_SNAKE_CASE_       ,       ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = src_lang
									SCREAMING_SNAKE_CASE_						 = tgt_lang
									return super().prepare_seqaseq_batch(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_    )

							def _lowercase					(self    ):

									"""simple docstring"""







									return self.set_src_lang_special_tokens(self.src_lang    )

							def _lowercase					(self    ):

									"""simple docstring"""







									return self.set_tgt_lang_special_tokens(self.tgt_lang    )

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







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







							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







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

"""simple docstring"""




import os
import socket
from contextlib import contextmanager

import torch

from ..commands.config.default import write_basic_config  # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import convert_model
from .versions import is_torch_version


if is_deepspeed_available():
						from deepspeed import DeepSpeedEngine

if is_tpu_available(check_device=False):
						import torch_xla.core.xla_model as xm



def        _lowerCamelCase ( __a    ):
		if is_torch_version('''<''',							'''2.0.0'''    ) or not hasattr(__a,							'''_dynamo'''    ):
				return False
		return isinstance(__a,							torch._dynamo.eval_frame.OptimizedModule    )



def        _lowerCamelCase ( __a,							__a = True    ):
		SCREAMING_SNAKE_CASE_						 = (torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

		SCREAMING_SNAKE_CASE_						 = is_compiled_module(__a    )
		if is_compiled:
				SCREAMING_SNAKE_CASE_						 = model
				SCREAMING_SNAKE_CASE_						 = model._orig_mod

		if is_deepspeed_available():
				options += (DeepSpeedEngine,)

		while isinstance(__a,							__a    ):
				SCREAMING_SNAKE_CASE_						 = model.module

		if not keep_fpaa_wrapper:
				SCREAMING_SNAKE_CASE_						 = getattr(__a,							'''forward'''    )
				SCREAMING_SNAKE_CASE_						 = model.__dict__.pop('''_original_forward''',							__a    )
				if original_forward is not None:
						while hasattr(__a,							'''__wrapped__'''    ):
								SCREAMING_SNAKE_CASE_						 = forward.__wrapped__
								if forward == original_forward:
										break
						SCREAMING_SNAKE_CASE_						 = forward
				if getattr(__a,							'''_converted_to_transformer_engine''',							__a    ):
						convert_model(__a,							to_transformer_engine=__a    )

		if is_compiled:
				SCREAMING_SNAKE_CASE_						 = model
				SCREAMING_SNAKE_CASE_						 = compiled_model

		return model



def        _lowerCamelCase ( ):
		PartialState().wait_for_everyone()



def        _lowerCamelCase ( __a,							__a    ):
		if PartialState().distributed_type == DistributedType.TPU:
				xm.save(__a,							__a    )
		elif PartialState().local_process_index == 0:
				torch.save(__a,							__a    )



@contextmanager
def        _lowerCamelCase ( **__a    ):
		for key, value in kwargs.items():
				SCREAMING_SNAKE_CASE_						 = str(__a    )

		yield

		for key in kwargs:
				if key.upper() in os.environ:
						del os.environ[key.upper()]



def        _lowerCamelCase ( __a    ):
		if not hasattr(__a,							'''__qualname__'''    ) and not hasattr(__a,							'''__name__'''    ):
				SCREAMING_SNAKE_CASE_						 = getattr(__a,							'''__class__''',							__a    )
		if hasattr(__a,							'''__qualname__'''    ):
				return obj.__qualname__
		if hasattr(__a,							'''__name__'''    ):
				return obj.__name__
		return str(__a    )



def        _lowerCamelCase ( __a,							__a    ):
		for key, value in source.items():
				if isinstance(__a,							__a    ):
						SCREAMING_SNAKE_CASE_						 = destination.setdefault(__a,							{}    )
						merge_dicts(__a,							__a    )
				else:
						SCREAMING_SNAKE_CASE_						 = value

		return destination



def        _lowerCamelCase ( __a = None    ):
		if port is None:
				SCREAMING_SNAKE_CASE_						 = 29_500
		with socket.socket(socket.AF_INET,							socket.SOCK_STREAM    ) as s:
				return s.connect_ex(('''localhost''', port)    ) == 0