



'''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:
				UpperCAmelCase     		=   None


UpperCAmelCase     		=   logging.get_logger(__name__)


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

UpperCAmelCase     		=   {
    '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',
    },
}

UpperCAmelCase     		=   {
    'facebook/mbart-large-en-ro': 1024,
    'facebook/mbart-large-cc25': 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']

class __snake_case(				_lowerCAmelCase ):


						'''simple docstring'''



						UpperCAmelCase							:   List[Any]									=		VOCAB_FILES_NAMES
						UpperCAmelCase							:   Any									=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCAmelCase							:   str									=		PRETRAINED_VOCAB_FILES_MAP
						UpperCAmelCase							:   List[Any]									=		["input_ids", "attention_mask"]
						UpperCAmelCase							:   int									=		MBartTokenizer

						UpperCAmelCase							:   List[int]									=		[]
						UpperCAmelCase							:   List[int]									=		[]


						def __init__( self     ,	A_=None     ,	A_=None     ,	A_="<s>"     ,	A_="</s>"     ,	A_="</s>"     ,	A_="<s>"     ,	A_="<unk>"     ,	A_="<pad>"     ,	A_="<mask>"     ,	A_=None     ,	A_=None     ,	A_=None     ,	**A_     ,	)     ->     str:
							# Mask token behave like a normal word, i.e. include the space before it
							lowerCAmelCase   =     AddedToken(A_     ,	lstrip=A_     ,	rstrip=A_				) if isinstance(A_     ,	A_				) else mask_token

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

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

							lowerCAmelCase   =     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   =     {
							    lang_code: self.convert_tokens_to_ids(A_				) for lang_code in FAIRSEQ_LANGUAGE_CODES
							}

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


						@property
						def     __snake_case   ( self				)     ->     str:
							return self._src_lang


						@src_lang.setter
						def     __snake_case   ( self     ,	A_				)     ->     None:
							lowerCAmelCase   =     new_src_lang
							self.set_src_lang_special_tokens(self._src_lang				)


						def     __snake_case   ( self     ,	A_     ,	A_ = None				)     ->     List[int]:
							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     ,	A_     ,	A_ = None				)     ->     List[int]:
							lowerCAmelCase   =     [self.sep_token_id]
							lowerCAmelCase   =     [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     ,	A_     ,	A_     ,	A_     ,	A_     ,	**A_				)     ->     Dict:
							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   =     src_lang
							lowerCAmelCase   =     self(A_     ,	add_special_tokens=A_     ,	return_tensors=A_     ,	**A_				)
							lowerCAmelCase   =     self.convert_tokens_to_ids(A_				)
							lowerCAmelCase   =     tgt_lang_id
							return inputs


						def     __snake_case   ( self     ,	A_     ,	A_ = "en_XX"     ,	A_ = None     ,	A_ = "ro_RO"     ,	**A_     ,	)     ->     BatchEncoding:
							lowerCAmelCase   =     src_lang
							lowerCAmelCase   =     tgt_lang
							return super().prepare_seqaseq_batch(A_     ,	A_     ,	**A_				)


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


						def     __snake_case   ( self				)     ->     Optional[Any]:
							return self.set_tgt_lang_special_tokens(self.tgt_lang				)


						def     __snake_case   ( self     ,	A_				)     ->     None:
							lowerCAmelCase   =     self.convert_tokens_to_ids(A_				)
							lowerCAmelCase   =     []
							lowerCAmelCase   =     [self.eos_token_id, self.cur_lang_code]

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

							lowerCAmelCase   =     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     __snake_case   ( self     ,	A_				)     ->     None:
							lowerCAmelCase   =     self.convert_tokens_to_ids(A_				)
							lowerCAmelCase   =     []
							lowerCAmelCase   =     [self.eos_token_id, self.cur_lang_code]

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

							lowerCAmelCase   =     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     __snake_case   ( self     ,	A_     ,	A_ = None				)     ->     Tuple[str]:
							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
							lowerCAmelCase   =     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,)




'''simple docstring'''

class __snake_case(				_lowerCAmelCase ):


						'''simple docstring'''



						pass







class __snake_case(				_lowerCAmelCase ):


						'''simple docstring'''



						pass







class __snake_case:


						'''simple docstring'''



						def __init__( self				)     ->     int:
							lowerCAmelCase   =     [
							    [],
							    [],
							    [],
							]


						def     __snake_case   ( self     ,	A_     ,	A_				)     ->     None:
							try:
								if len(self.queues[priority]				) >= 100:
									raise OverflowError("""Maximum queue size is 100"""				)
								self.queues[priority].append(A_				)
							except IndexError:
								raise ValueError("""Valid priorities are 0, 1, and 2"""				)


						def     __snake_case   ( self				)     ->     int:
							for queue in self.queues:
								if queue:
									return queue.pop(0				)
							raise UnderFlowError("""All queues are empty"""				)




						def __str__( self				)     ->     str:
							return "\n".join(f'Priority {i}: {q}' for i, q in enumerate(self.queues				)				)







class __snake_case:


						'''simple docstring'''



						def __init__( self				)     ->     Dict:
							lowerCAmelCase   =     []


						def     __snake_case   ( self     ,	A_				)     ->     None:
							if len(self.queue				) == 100:
								raise OverFlowError("""Maximum queue size is 100"""				)
							self.queue.append(A_				)


						def     __snake_case   ( self				)     ->     int:
							if not self.queue:
								raise UnderFlowError("""The queue is empty"""				)
							else:
								lowerCAmelCase   =     min(self.queue				)
								self.queue.remove(A_				)
								return data




						def __str__( self				)     ->     str:
							return str(self.queue				)







def 		_snake_case		( )      ->						Tuple:







	"""simple docstring"""
	lowerCAmelCase   =     FixedPriorityQueue()
	fpq.enqueue(0							,		10							)
	fpq.enqueue(1							,		70							)
	fpq.enqueue(0							,		100							)
	fpq.enqueue(2							,		1							)
	fpq.enqueue(2							,		5							)
	fpq.enqueue(1							,		7							)
	fpq.enqueue(2							,		4							)
	fpq.enqueue(1							,		64							)
	fpq.enqueue(0							,		128							)
	print(_SCREAMING_SNAKE_CASE							)
	print(fpq.dequeue()							)
	print(fpq.dequeue()							)
	print(fpq.dequeue()							)
	print(fpq.dequeue()							)
	print(fpq.dequeue()							)
	print(_SCREAMING_SNAKE_CASE							)
	print(fpq.dequeue()							)
	print(fpq.dequeue()							)
	print(fpq.dequeue()							)
	print(fpq.dequeue()							)
	print(fpq.dequeue()							)






def 		_snake_case		( )      ->						Optional[Any]:







	"""simple docstring"""
	lowerCAmelCase   =     ElementPriorityQueue()
	epq.enqueue(10							)
	epq.enqueue(70							)
	epq.enqueue(100							)
	epq.enqueue(1							)
	epq.enqueue(5							)
	epq.enqueue(7							)
	epq.enqueue(4							)
	epq.enqueue(64							)
	epq.enqueue(128							)
	print(_SCREAMING_SNAKE_CASE							)
	print(epq.dequeue()							)
	print(epq.dequeue()							)
	print(epq.dequeue()							)
	print(epq.dequeue()							)
	print(epq.dequeue()							)
	print(_SCREAMING_SNAKE_CASE							)
	print(epq.dequeue()							)
	print(epq.dequeue()							)
	print(epq.dequeue()							)
	print(epq.dequeue()							)
	print(epq.dequeue()							)


if __name__ == "__main__":
				fixed_priority_queue()
				element_priority_queue()