






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


UpperCamelCase__	=     logging.get_logger(__name__)

UpperCamelCase__	=     {
    'facebook/regnet-y-040': 'https://huggingface.co/facebook/regnet-y-040/blob/main/config.json',
}


class     _UpperCAmelCase  (						snake_case     ):
    __lowerCamelCase:				str						    =      'regnet'
    __lowerCamelCase:				Optional[int]						    =      ['x', 'y']




    def __init__(     self					:    List[str]					,       a					:    Tuple=3					,       a					:    Optional[int]=3_2					,       a					:    str=[1_2_8, 1_9_2, 5_1_2, 1_0_8_8]					,       a					:    int=[2, 6, 1_2, 2]					,       a					:    Any=6_4					,       a					:    Any="y"					,       a					:    Tuple="relu"					,       **a					:    Tuple					,       ):






       '''simple docstring'''






       super().__init__(**a     )
       if layer_type not in self.layer_types:
          raise ValueError(f"""layer_type={layer_type} is not one of {",".join(self.layer_types     )}"""     )
       lowercase_		:      Optional[int]          =       num_channels
       lowercase_		:      Union[str, Any]          =       embedding_size
       lowercase_		:      str          =       hidden_sizes
       lowercase_		:      Optional[int]          =       depths
       lowercase_		:      Union[str, Any]          =       groups_width
       lowercase_		:      Optional[int]          =       layer_type
       lowercase_		:      Union[str, Any]          =       hidden_act
       # always downsample in the first stage
       lowercase_		:      List[Any]          =       True












'''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_mbartaa import MBartaaTokenizer
else:
 UpperCamelCase__	=     None


UpperCamelCase__	=     logging.get_logger(__name__)

UpperCamelCase__	=     {'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

UpperCamelCase__	=     {
    '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'
        ),
    },
    'tokenizer_file': {
        'facebook/mbart-large-50-one-to-many-mmt': (
            'https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/tokenizer.json'
        ),
    },
}

UpperCamelCase__	=     {
    'facebook/mbart-large-50-one-to-many-mmt': 1024,
}

# fmt: off
UpperCamelCase__	=     ['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     _UpperCAmelCase  (						snake_case     ):
    __lowerCamelCase:				List[str]						    =      VOCAB_FILES_NAMES
    __lowerCamelCase:				int						    =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __lowerCamelCase:				List[str]						    =      PRETRAINED_VOCAB_FILES_MAP
    __lowerCamelCase:				List[str]						    =      ['input_ids', 'attention_mask']
    __lowerCamelCase:				str						    =      MBartaaTokenizer

    __lowerCamelCase:				List[int]						    =      []
    __lowerCamelCase:				List[int]						    =      []




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






       '''simple docstring'''






       lowercase_		:      int          =       AddedToken(a					,       lstrip=a					,       rstrip=a     ) if isinstance(a					,       a     ) else mask_token

       lowercase_		:      List[Any]          =       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__(
           a					,       src_lang=a					,       tgt_lang=a					,       tokenizer_file=a					,       eos_token=a					,       sep_token=a					,       cls_token=a					,       unk_token=a					,       pad_token=a					,       mask_token=a					,       **a					,       )

       lowercase_		:      Any          =       vocab_file
       lowercase_		:      int          =       False if not self.vocab_file else True

       lowercase_		:      Optional[Any]          =       {
           lang_code: self.convert_tokens_to_ids(a     ) for lang_code in FAIRSEQ_LANGUAGE_CODES
       }

       lowercase_		:      int          =       src_lang if src_lang is not None else "en_XX"
       lowercase_		:      Tuple          =       tgt_lang
       lowercase_		:      List[Any]          =       self.lang_code_to_id[self._src_lang]
       self.set_src_lang_special_tokens(self._src_lang     )




    @property
    def 			lowerCAmelCase__			(     self					:    List[Any]     ):






       '''simple docstring'''






       return self._src_lang




    @src_lang.setter
    def 			lowerCAmelCase__			(     self					:    Union[str, Any]					,       a					:    str     ):






       '''simple docstring'''






       lowercase_		:      Optional[Any]          =       new_src_lang
       self.set_src_lang_special_tokens(self._src_lang     )




    def 			lowerCAmelCase__			(     self					:    int					,       a					:    List[int]					,       a					:    Optional[List[int]] = 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 			lowerCAmelCase__			(     self					:    Any					,       a					:    List[str]					,       a					:    str = "en_XX"					,       a					:    Optional[List[str]] = None					,       a					:    str = "ro_RO"					,       **a					:    Union[str, Any]					,       ):






       '''simple docstring'''






       lowercase_		:      Dict          =       src_lang
       lowercase_		:      Dict          =       tgt_lang
       return super().prepare_seqaseq_batch(a					,       a					,       **a     )




    def 			lowerCAmelCase__			(     self					:    Dict     ):






       '''simple docstring'''






       return self.set_src_lang_special_tokens(self.src_lang     )




    def 			lowerCAmelCase__			(     self					:    int     ):






       '''simple docstring'''






       return self.set_tgt_lang_special_tokens(self.tgt_lang     )




    def 			lowerCAmelCase__			(     self					:    str					,       a					:    str     ):






       '''simple docstring'''






       lowercase_		:      Optional[int]          =       self.convert_tokens_to_ids(a     )
       lowercase_		:      Optional[int]          =       [self.cur_lang_code_id]
       lowercase_		:      List[Any]          =       [self.eos_token_id]

       lowercase_		:      Optional[Any]          =       self.convert_ids_to_tokens(self.prefix_tokens     )
       lowercase_		:      Union[str, Any]          =       self.convert_ids_to_tokens(self.suffix_tokens     )

       lowercase_		:      Optional[Any]          =       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 			lowerCAmelCase__			(     self					:    Tuple					,       a					:    str     ):






       '''simple docstring'''






       lowercase_		:      Optional[Any]          =       self.convert_tokens_to_ids(a     )
       lowercase_		:      str          =       [self.cur_lang_code_id]
       lowercase_		:      List[str]          =       [self.eos_token_id]

       lowercase_		:      Dict          =       self.convert_ids_to_tokens(self.prefix_tokens     )
       lowercase_		:      Dict          =       self.convert_ids_to_tokens(self.suffix_tokens     )

       lowercase_		:      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 			lowerCAmelCase__			(     self					:    Any					,       a					:    int					,       a					:    str					,       a					:    Optional[str]					,       a					:    Optional[str]					,       **a					:    str     ):






       '''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"     )
       lowercase_		:      Any          =       src_lang
       lowercase_		:      int          =       self(a					,       add_special_tokens=a					,       return_tensors=a					,       **a     )
       lowercase_		:      Any          =       self.convert_tokens_to_ids(a     )
       lowercase_		:      Optional[Any]          =       tgt_lang_id
       return inputs





    def 			lowerCAmelCase__			(     self					:    Any					,       a					:    str					,       a					:    Optional[str] = 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(a     ):
          logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""     )
          return
       lowercase_		:      Any          =       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     ):
          copyfile(self.vocab_file					,       a     )

       return (out_vocab_file,)




