
"""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:
			__A					=			None


__A					=			logging.get_logger(__name__)

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

__A					=			{
    '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'
        ),
    },
}

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

# fmt: off
__A					=			['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 						lowerCamelCase__   (   __magic_name__							):





			'''simple docstring'''
			lowerCamelCase       =						VOCAB_FILES_NAMES
			lowerCamelCase       =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase       =						PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase       =						['''input_ids''', '''attention_mask''']
			lowerCamelCase       =						MBartaaTokenizer

			lowerCamelCase       =						[]
			lowerCamelCase       =						[]



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

				_lowerCAmelCase								=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__(
				    __UpperCAmelCase	,	src_lang=__UpperCAmelCase	,	tgt_lang=__UpperCAmelCase	,	tokenizer_file=__UpperCAmelCase	,	eos_token=__UpperCAmelCase	,	sep_token=__UpperCAmelCase	,	cls_token=__UpperCAmelCase	,	unk_token=__UpperCAmelCase	,	pad_token=__UpperCAmelCase	,	mask_token=__UpperCAmelCase	,	**__UpperCAmelCase	,	)

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

				_lowerCAmelCase								={
				    lang_code: self.convert_tokens_to_ids(__UpperCAmelCase    ) for lang_code in FAIRSEQ_LANGUAGE_CODES
				}

				_lowerCAmelCase								=src_lang if src_lang is not None else """en_XX"""
				_lowerCAmelCase								=tgt_lang
				_lowerCAmelCase								=self.lang_code_to_id[self._src_lang]
				self.set_src_lang_special_tokens(self._src_lang    )



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



			@src_lang.setter
			def    _lowerCAmelCase						(				self	,	__UpperCAmelCase    )					->	None:
				_lowerCAmelCase								=new_src_lang
				self.set_src_lang_special_tokens(self._src_lang    )



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



			def    _lowerCAmelCase						(				self    )					->	int:
				return self.set_src_lang_special_tokens(self.src_lang    )



			def    _lowerCAmelCase						(				self    )					->	List[str]:
				return self.set_tgt_lang_special_tokens(self.tgt_lang    )



			def    _lowerCAmelCase						(				self	,	__UpperCAmelCase    )					->	None:
				_lowerCAmelCase								=self.convert_tokens_to_ids(__UpperCAmelCase    )
				_lowerCAmelCase								=[self.cur_lang_code_id]
				_lowerCAmelCase								=[self.eos_token_id]

				_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    _lowerCAmelCase						(				self	,	__UpperCAmelCase    )					->	None:
				_lowerCAmelCase								=self.convert_tokens_to_ids(__UpperCAmelCase    )
				_lowerCAmelCase								=[self.cur_lang_code_id]
				_lowerCAmelCase								=[self.eos_token_id]

				_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    _lowerCAmelCase						(				self	,	__UpperCAmelCase	,	__UpperCAmelCase	,	__UpperCAmelCase	,	__UpperCAmelCase	,	**__UpperCAmelCase    )					->	int:
				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(__UpperCAmelCase	,	add_special_tokens=__UpperCAmelCase	,	return_tensors=__UpperCAmelCase	,	**__UpperCAmelCase    )
				_lowerCAmelCase								=self.convert_tokens_to_ids(__UpperCAmelCase    )
				_lowerCAmelCase								=tgt_lang_id
				return inputs



			def    _lowerCAmelCase						(				self	,	__UpperCAmelCase	,	__UpperCAmelCase = 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(__UpperCAmelCase    ):
					logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''    )
					return
				_lowerCAmelCase								=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


__A					=			logging.get_logger(__name__)

__A					=			{
    'uw-madison/nystromformer-512': 'https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json',
    # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
}







class 						lowerCamelCase__   (   __magic_name__							):





			'''simple docstring'''
			lowerCamelCase       =						'''nystromformer'''



			def __init__(				self	,	__UpperCAmelCase=3_00_00	,	__UpperCAmelCase=7_68	,	__UpperCAmelCase=12	,	__UpperCAmelCase=12	,	__UpperCAmelCase=30_72	,	__UpperCAmelCase="gelu_new"	,	__UpperCAmelCase=0.1	,	__UpperCAmelCase=0.1	,	__UpperCAmelCase=5_10	,	__UpperCAmelCase=2	,	__UpperCAmelCase=64	,	__UpperCAmelCase=64	,	__UpperCAmelCase=65	,	__UpperCAmelCase=False	,	__UpperCAmelCase=0.0_2	,	__UpperCAmelCase=1e-5	,	__UpperCAmelCase=1	,	__UpperCAmelCase=0	,	__UpperCAmelCase=2	,	**__UpperCAmelCase	,	)					->	Union[str, Any]:
				_lowerCAmelCase								=vocab_size
				_lowerCAmelCase								=max_position_embeddings
				_lowerCAmelCase								=hidden_size
				_lowerCAmelCase								=num_hidden_layers
				_lowerCAmelCase								=num_attention_heads
				_lowerCAmelCase								=intermediate_size
				_lowerCAmelCase								=hidden_act
				_lowerCAmelCase								=hidden_dropout_prob
				_lowerCAmelCase								=attention_probs_dropout_prob
				_lowerCAmelCase								=initializer_range
				_lowerCAmelCase								=type_vocab_size
				_lowerCAmelCase								=segment_means_seq_len
				_lowerCAmelCase								=num_landmarks
				_lowerCAmelCase								=conv_kernel_size
				_lowerCAmelCase								=inv_coeff_init_option
				_lowerCAmelCase								=layer_norm_eps
				super().__init__(pad_token_id=__UpperCAmelCase	,	bos_token_id=__UpperCAmelCase	,	eos_token_id=__UpperCAmelCase	,	**__UpperCAmelCase    )



