



from collections import OrderedDict
from typing import Mapping

from packaging import version

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


UpperCAmelCase_		 =					logging.get_logger(__name__)

UpperCAmelCase_		 =					{
    """sail/poolformer_s12""": """https://huggingface.co/sail/poolformer_s12/resolve/main/config.json""",
    # See all PoolFormer models at https://huggingface.co/models?filter=poolformer
}


class 	lowerCamelCase__	(       _A):



 """simple docstring"""

 a__					: Any =  'poolformer'

 def __init__(    self					:					Optional[Any]			,						__lowerCAmelCase					:					Union[str, Any]=3			,						__lowerCAmelCase					:					List[str]=16			,						__lowerCAmelCase					:					Any=16			,						__lowerCAmelCase					:					List[str]=3			,						__lowerCAmelCase					:					str=4.0			,						__lowerCAmelCase					:					Dict=[2, 2, 6, 2]			,						__lowerCAmelCase					:					str=[64, 1_28, 3_20, 5_12]			,						__lowerCAmelCase					:					Any=[7, 3, 3, 3]			,						__lowerCAmelCase					:					Any=[4, 2, 2, 2]			,						__lowerCAmelCase					:					List[Any]=[2, 1, 1, 1]			,						__lowerCAmelCase					:					Union[str, Any]=4			,						__lowerCAmelCase					:					List[str]=0.0			,						__lowerCAmelCase					:					str="gelu"			,						__lowerCAmelCase					:					int=True			,						__lowerCAmelCase					:					str=1E-5			,						__lowerCAmelCase					:					int=0.02			,						**__lowerCAmelCase					:					List[str]			,						)   ->	Dict:
    _A      =       num_channels
    _A      =       patch_size
    _A      =       stride
    _A      =       padding
    _A      =       pool_size
    _A      =       hidden_sizes
    _A      =       mlp_ratio
    _A      =       depths
    _A      =       patch_sizes
    _A      =       strides
    _A      =       num_encoder_blocks
    _A      =       drop_path_rate
    _A      =       hidden_act
    _A      =       use_layer_scale
    _A      =       layer_scale_init_value
    _A      =       initializer_range
    super().__init__(**__lowerCAmelCase      )


class 	lowerCamelCase__	(       _A):



 """simple docstring"""

 a__					: Union[str, Any] =  version.parse("1.11")

 @property
 def     snake_case_      (    self					:					Dict      )   ->	List[Any]:
    return OrderedDict(
        [
            ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
        ]      )

 @property
 def     snake_case_      (    self					:					int      )   ->	Optional[Any]:
    return 2E-3






"""simple docstring"""

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

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
    from .tokenization_nllb import NllbTokenizer
else:
    _UpperCamelCase		     =    None


_UpperCamelCase		     =    logging.get_logger(__name__)


_UpperCamelCase		     =    {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

_UpperCamelCase		     =    {
    """vocab_file""": {
        """facebook/nllb-200-distilled-600M""": (
            """https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/sentencepiece.bpe.model"""
        ),
    },
    """tokenizer_file""": {
        """facebook/nllb-200-distilled-600M""": (
            """https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/tokenizer.json"""
        ),
    },
}

_UpperCamelCase		     =    {
    """facebook/nllb-large-en-ro""": 1_0_2_4,
    """facebook/nllb-200-distilled-600M""": 1_0_2_4,
}

# fmt: off
_UpperCamelCase		     =    ["""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 			__a					(						__magic_name__       ):





       """simple docstring"""


       __UpperCamelCase					:      List[Any]    =						VOCAB_FILES_NAMES
       __UpperCamelCase					:      Dict    =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __UpperCamelCase					:      Dict    =						PRETRAINED_VOCAB_FILES_MAP
       __UpperCamelCase					:      int    =						['input_ids', 'attention_mask']
       __UpperCamelCase					:      Union[str, Any]    =						NllbTokenizer

       __UpperCamelCase					:      List[int]    =						[]
       __UpperCamelCase					:      List[int]    =						[]






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





        """simple docstring"""

        lowerCAmelCase__   :				List[Any] 			=				AddedToken(snake_case			,					lstrip=snake_case			,					rstrip=snake_case   ) if isinstance(snake_case			,					snake_case   ) else mask_token
        lowerCAmelCase__   :				Tuple 			=				legacy_behaviour
        super().__init__(
            vocab_file=snake_case			,					tokenizer_file=snake_case			,					bos_token=snake_case			,					eos_token=snake_case			,					sep_token=snake_case			,					cls_token=snake_case			,					unk_token=snake_case			,					pad_token=snake_case			,					mask_token=snake_case			,					src_lang=snake_case			,					tgt_lang=snake_case			,					additional_special_tokens=snake_case			,					legacy_behaviour=snake_case			,					**snake_case			,					)

        lowerCAmelCase__   :				Optional[int] 			=				vocab_file
        lowerCAmelCase__   :				int 			=				False if not self.vocab_file else True

        lowerCAmelCase__   :				Union[str, Any] 			=				FAIRSEQ_LANGUAGE_CODES.copy()

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

        self.add_special_tokens({"additional_special_tokens": _additional_special_tokens}   )
        lowerCAmelCase__   :				Tuple 			=				{
            lang_code: self.convert_tokens_to_ids(snake_case   ) for lang_code in FAIRSEQ_LANGUAGE_CODES
        }

        lowerCAmelCase__   :				Union[str, Any] 			=				src_lang if src_lang is not None else "eng_Latn"
        lowerCAmelCase__   :				List[str] 			=				self.convert_tokens_to_ids(self._src_lang   )
        lowerCAmelCase__   :				Any 			=				tgt_lang
        self.set_src_lang_special_tokens(self._src_lang   )






       @property
       def 			SCREAMING_SNAKE_CASE_	(   self   ):





        """simple docstring"""

        return self._src_lang






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





        """simple docstring"""

        lowerCAmelCase__   :				Union[str, Any] 			=				new_src_lang
        self.set_src_lang_special_tokens(self._src_lang   )






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





        """simple docstring"""

        lowerCAmelCase__   :				Tuple 			=				[self.sep_token_id]
        lowerCAmelCase__   :				Dict 			=				[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 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case			,					snake_case			,					snake_case			,					snake_case			,					**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"   )
        lowerCAmelCase__   :				Any 			=				src_lang
        lowerCAmelCase__   :				Optional[Any] 			=				self(snake_case			,					add_special_tokens=snake_case			,					return_tensors=snake_case			,					**snake_case   )
        lowerCAmelCase__   :				str 			=				self.convert_tokens_to_ids(snake_case   )
        lowerCAmelCase__   :				Any 			=				tgt_lang_id
        return inputs






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





        """simple docstring"""

        lowerCAmelCase__   :				int 			=				src_lang
        lowerCAmelCase__   :				str 			=				tgt_lang
        return super().prepare_seqaseq_batch(snake_case			,					snake_case			,					**snake_case   )






       def 			SCREAMING_SNAKE_CASE_	(   self   ):





        """simple docstring"""

        return self.set_src_lang_special_tokens(self.src_lang   )






       def 			SCREAMING_SNAKE_CASE_	(   self   ):





        """simple docstring"""

        return self.set_tgt_lang_special_tokens(self.tgt_lang   )






       def 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case   ):





        """simple docstring"""

        lowerCAmelCase__   :				Tuple 			=				self.convert_tokens_to_ids(snake_case   )

        if self.legacy_behaviour:
         lowerCAmelCase__   :				Optional[int] 			=				[]
         lowerCAmelCase__   :				Optional[int] 			=				[self.eos_token_id, self.cur_lang_code]
        else:
         lowerCAmelCase__   :				int 			=				[self.cur_lang_code]
         lowerCAmelCase__   :				List[str] 			=				[self.eos_token_id]

        lowerCAmelCase__   :				Any 			=				self.convert_ids_to_tokens(self.prefix_tokens   )
        lowerCAmelCase__   :				str 			=				self.convert_ids_to_tokens(self.suffix_tokens   )

        lowerCAmelCase__   :				Tuple 			=				processors.TemplateProcessing(
            single=prefix_tokens_str + ["$A"] + suffix_tokens_str			,					pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str			,					special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str			,					self.prefix_tokens + self.suffix_tokens   )   )			,					)






       def 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case   ):





        """simple docstring"""

        lowerCAmelCase__   :				List[Any] 			=				self.convert_tokens_to_ids(snake_case   )
        if self.legacy_behaviour:
         lowerCAmelCase__   :				Dict 			=				[]
         lowerCAmelCase__   :				Dict 			=				[self.eos_token_id, self.cur_lang_code]
        else:
         lowerCAmelCase__   :				str 			=				[self.cur_lang_code]
         lowerCAmelCase__   :				Tuple 			=				[self.eos_token_id]

        lowerCAmelCase__   :				Any 			=				self.convert_ids_to_tokens(self.prefix_tokens   )
        lowerCAmelCase__   :				List[Any] 			=				self.convert_ids_to_tokens(self.suffix_tokens   )

        lowerCAmelCase__   :				Optional[int] 			=				processors.TemplateProcessing(
            single=prefix_tokens_str + ["$A"] + suffix_tokens_str			,					pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str			,					special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str			,					self.prefix_tokens + self.suffix_tokens   )   )			,					)






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





        """simple docstring"""

        if not self.can_save_slow_tokenizer:
         raise ValueError(
             "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
             "tokenizer."   )

        if not os.path.isdir(snake_case   ):
         logger.error(F"""Vocabulary path ({save_directory}) should be a directory."""   )
         return
        lowerCAmelCase__   :				str 			=				os.path.join(
            snake_case			,					(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]   )

        if os.path.abspath(self.vocab_file   ) != os.path.abspath(snake_case   ):
         copyfile(self.vocab_file			,					snake_case   )

        return (out_vocab_file,)






