



"""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_mbart import MBartTokenizer
else:
					__A   :							Any										=   None


__A   :							Union[str, Any]										=   logging.get_logger(__name__)


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

__A   :							int										=   {
    'vocab_file': {
        'facebook/mbart-large-en-ro': (
            'https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model'
        ),
        'facebook/mbart-large-cc25': (
            'https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model'
        ),
    },
    'tokenizer_file': {
        'facebook/mbart-large-en-ro': 'https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json',
        'facebook/mbart-large-cc25': 'https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json',
    },
}

__A   :							List[Any]										=   {
    'facebook/mbart-large-en-ro': 1024,
    'facebook/mbart-large-cc25': 1024,
}

# fmt: off
__A   :							Dict										=   ['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']
class 			_a (					lowerCAmelCase):
			"""simple docstring"""
			UpperCamelCase__			      =	VOCAB_FILES_NAMES
			UpperCamelCase__			      =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			UpperCamelCase__			      =	PRETRAINED_VOCAB_FILES_MAP
			UpperCamelCase__			      =	['input_ids', 'attention_mask']
			UpperCamelCase__			      =	MBartTokenizer

			UpperCamelCase__			      =	[]
			UpperCamelCase__			      =	[]



			def __init__(		self     :    Any				,   __UpperCamelCase     :    str=None				,   __UpperCamelCase     :    Any=None				,   __UpperCamelCase     :    Union[str, Any]="<s>"				,   __UpperCamelCase     :    str="</s>"				,   __UpperCamelCase     :    int="</s>"				,   __UpperCamelCase     :    Any="<s>"				,   __UpperCamelCase     :    str="<unk>"				,   __UpperCamelCase     :    str="<pad>"				,   __UpperCamelCase     :    str="<mask>"				,   __UpperCamelCase     :    Dict=None				,   __UpperCamelCase     :    Tuple=None				,   __UpperCamelCase     :    List[str]=None				,   **__UpperCamelCase     :    str				,   )->Tuple:
							_UpperCAmelCase					=    AddedToken(UpperCAmelCase__				,   lstrip=UpperCAmelCase__				,   rstrip=UpperCAmelCase__   ) if isinstance(UpperCAmelCase__				,   UpperCAmelCase__   ) else mask_token

							super().__init__(
							    vocab_file=UpperCAmelCase__				,   tokenizer_file=UpperCAmelCase__				,   bos_token=UpperCAmelCase__				,   eos_token=UpperCAmelCase__				,   sep_token=UpperCAmelCase__				,   cls_token=UpperCAmelCase__				,   unk_token=UpperCAmelCase__				,   pad_token=UpperCAmelCase__				,   mask_token=UpperCAmelCase__				,   src_lang=UpperCAmelCase__				,   tgt_lang=UpperCAmelCase__				,   additional_special_tokens=UpperCAmelCase__				,   **UpperCAmelCase__				,   )

							_UpperCAmelCase					=    vocab_file
							_UpperCAmelCase					=    False if not self.vocab_file else True

							_UpperCAmelCase					=    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}   )
							_UpperCAmelCase					=    {
							    lang_code: self.convert_tokens_to_ids(UpperCAmelCase__   ) for lang_code in FAIRSEQ_LANGUAGE_CODES
							}

							_UpperCAmelCase					=    src_lang if src_lang is not None else '''en_XX'''
							_UpperCAmelCase					=    self.convert_tokens_to_ids(self._src_lang   )
							_UpperCAmelCase					=    tgt_lang
							self.set_src_lang_special_tokens(self._src_lang   )



			@property
			def  lowercase__						(		self     :    Union[str, Any]   )->Optional[Any]:
							return self._src_lang



			@src_lang.setter
			def  lowercase__						(		self     :    Optional[Any]				,   __UpperCamelCase     :    str   )->int:
							_UpperCAmelCase					=    new_src_lang
							self.set_src_lang_special_tokens(self._src_lang   )



			def  lowercase__						(		self     :    Optional[int]				,   __UpperCamelCase     :    List[int]				,   __UpperCamelCase     :    Optional[List[int]] = None   )->Dict:
							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     :    Tuple				,   __UpperCamelCase     :    List[int]				,   __UpperCamelCase     :    Optional[List[int]] = None   )->int:
							_UpperCAmelCase					=    [self.sep_token_id]
							_UpperCAmelCase					=    [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     :    Optional[int]				,   __UpperCamelCase     :    List[Any]				,   __UpperCamelCase     :    str				,   __UpperCamelCase     :    Optional[str]				,   __UpperCamelCase     :    Optional[str]				,   **__UpperCamelCase     :    List[Any]   )->str:
							if src_lang is None or tgt_lang is None:
											raise ValueError('''Translation requires a `src_lang` and a `tgt_lang` for this model'''   )
							_UpperCAmelCase					=    src_lang
							_UpperCAmelCase					=    self(UpperCAmelCase__				,   add_special_tokens=UpperCAmelCase__				,   return_tensors=UpperCAmelCase__				,   **UpperCAmelCase__   )
							_UpperCAmelCase					=    self.convert_tokens_to_ids(UpperCAmelCase__   )
							_UpperCAmelCase					=    tgt_lang_id
							return inputs



			def  lowercase__						(		self     :    Any				,   __UpperCamelCase     :    List[str]				,   __UpperCamelCase     :    str = "en_XX"				,   __UpperCamelCase     :    Optional[List[str]] = None				,   __UpperCamelCase     :    str = "ro_RO"				,   **__UpperCamelCase     :    Any				,   )->int:
							_UpperCAmelCase					=    src_lang
							_UpperCAmelCase					=    tgt_lang
							return super().prepare_seqaseq_batch(UpperCAmelCase__				,   UpperCAmelCase__				,   **UpperCAmelCase__   )



			def  lowercase__						(		self     :    Dict   )->Dict:
							return self.set_src_lang_special_tokens(self.src_lang   )



			def  lowercase__						(		self     :    List[Any]   )->Dict:
							return self.set_tgt_lang_special_tokens(self.tgt_lang   )



			def  lowercase__						(		self     :    Optional[int]				,   __UpperCamelCase     :    Tuple   )->str:
							_UpperCAmelCase					=    self.convert_tokens_to_ids(UpperCAmelCase__   )
							_UpperCAmelCase					=    []
							_UpperCAmelCase					=    [self.eos_token_id, self.cur_lang_code]

							_UpperCAmelCase					=    self.convert_ids_to_tokens(self.prefix_tokens   )
							_UpperCAmelCase					=    self.convert_ids_to_tokens(self.suffix_tokens   )

							_UpperCAmelCase					=    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  lowercase__						(		self     :    Union[str, Any]				,   __UpperCamelCase     :    str   )->Optional[int]:
							_UpperCAmelCase					=    self.convert_tokens_to_ids(UpperCAmelCase__   )
							_UpperCAmelCase					=    []
							_UpperCAmelCase					=    [self.eos_token_id, self.cur_lang_code]

							_UpperCAmelCase					=    self.convert_ids_to_tokens(self.prefix_tokens   )
							_UpperCAmelCase					=    self.convert_ids_to_tokens(self.suffix_tokens   )

							_UpperCAmelCase					=    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  lowercase__						(		self     :    Union[str, Any]				,   __UpperCamelCase     :    str				,   __UpperCamelCase     :    Optional[str] = None   )->Optional[int]:
							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(UpperCAmelCase__   ):
											logger.error(F'Vocabulary path ({save_directory}) should be a directory.'   )
											return
							_UpperCAmelCase					=    os.path.join(
							    UpperCAmelCase__				,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']   )

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

							return (out_vocab_file,)









"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


__A   :							Optional[int]										=   logging.get_logger(__name__)

__A   :							Optional[Any]										=   {
    "google/bit-50": "https://huggingface.co/google/bit-50/resolve/main/config.json",
}
class 			_a (					lowerCAmelCase			,							lowerCAmelCase):
			"""simple docstring"""
			UpperCamelCase__			      =	"""bit"""
			UpperCamelCase__			      =	["""preactivation""", """bottleneck"""]
			UpperCamelCase__			      =	["""SAME""", """VALID"""]



			def __init__(		self     :    List[Any]				,   __UpperCamelCase     :    Optional[int]=3				,   __UpperCamelCase     :    Optional[int]=6_4				,   __UpperCamelCase     :    List[Any]=[2_5_6, 5_1_2, 1_0_2_4, 2_0_4_8]				,   __UpperCamelCase     :    Any=[3, 4, 6, 3]				,   __UpperCamelCase     :    str="preactivation"				,   __UpperCamelCase     :    Union[str, Any]="relu"				,   __UpperCamelCase     :    str=None				,   __UpperCamelCase     :    Dict=3_2				,   __UpperCamelCase     :    List[str]=0.0				,   __UpperCamelCase     :    Any=False				,   __UpperCamelCase     :    Union[str, Any]=3_2				,   __UpperCamelCase     :    List[str]=1				,   __UpperCamelCase     :    List[str]=None				,   __UpperCamelCase     :    Optional[Any]=None				,   **__UpperCamelCase     :    List[str]				,   )->List[Any]:
							super().__init__(**__UpperCamelCase   )
							if layer_type not in self.layer_types:
											raise ValueError(F'layer_type={layer_type} is not one of {",".join(self.layer_types   )}'   )
							if global_padding is not None:
											if global_padding.upper() in self.supported_padding:
															_UpperCAmelCase					=    global_padding.upper()
											else:
															raise ValueError(F'Padding strategy {global_padding} not supported'   )
							_UpperCAmelCase					=    num_channels
							_UpperCAmelCase					=    embedding_size
							_UpperCAmelCase					=    hidden_sizes
							_UpperCAmelCase					=    depths
							_UpperCAmelCase					=    layer_type
							_UpperCAmelCase					=    hidden_act
							_UpperCAmelCase					=    global_padding
							_UpperCAmelCase					=    num_groups
							_UpperCAmelCase					=    drop_path_rate
							_UpperCAmelCase					=    embedding_dynamic_padding
							_UpperCAmelCase					=    output_stride
							_UpperCAmelCase					=    width_factor

							_UpperCAmelCase					=    ['''stem'''] + [F'stage{idx}' for idx in range(1				,   len(__UpperCamelCase   ) + 1   )]
							_UpperCAmelCase		,						_UpperCAmelCase					=    get_aligned_output_features_output_indices(
							    out_features=__UpperCamelCase				,   out_indices=__UpperCamelCase				,   stage_names=self.stage_names   )



