

"""simple docstring"""





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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


__UpperCamelCase    : str				 =						logging.get_logger(__name__)

__UpperCamelCase    : Optional[int]				 =						'''▁'''

__UpperCamelCase    : Dict				 =						{'''vocab_file''': '''sentencepiece.bpe.model'''}

__UpperCamelCase    : str				 =						{
    '''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'''
        ),
    }
}

__UpperCamelCase    : str				 =						{
    '''facebook/mbart-large-50-one-to-many-mmt''': 1_0_2_4,
}

# fmt: off
__UpperCamelCase    : Union[str, Any]				 =						['''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 							SCREAMING_SNAKE_CASE   (						a_			):






					"""simple docstring"""



					lowercase__												=			VOCAB_FILES_NAMES
					lowercase__												=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowercase__												=			PRETRAINED_VOCAB_FILES_MAP
					lowercase__												=			["input_ids", "attention_mask"]

					lowercase__												=			[]
					lowercase__												=			[]







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

						lowerCAmelCase__      :		Any    							=      {} if sp_model_kwargs is None else sp_model_kwargs

						lowerCAmelCase__      :		Dict    							=      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__(
						    src_lang=lowercase_  ,tgt_lang=lowercase_  ,eos_token=lowercase_  ,unk_token=lowercase_  ,sep_token=lowercase_  ,cls_token=lowercase_  ,pad_token=lowercase_  ,mask_token=lowercase_  ,sp_model_kwargs=self.sp_model_kwargs  ,**lowercase_  ,)

						lowerCAmelCase__      :		int    							=      spm.SentencePieceProcessor(**self.sp_model_kwargs						)
						self.sp_model.Load(str(lowercase_						)						)
						lowerCAmelCase__      :		List[str]    							=      vocab_file

						# Original fairseq vocab and spm vocab must be "aligned":
						# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
						# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
						# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
						# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

						# Mimic fairseq token-to-id alignment for the first 4 token
						lowerCAmelCase__      :		Union[str, Any]    							=      {'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

						# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
						lowerCAmelCase__      :		Optional[int]    							=      1

						lowerCAmelCase__      :		Optional[Any]    							=      len(self.sp_model						)
						lowerCAmelCase__      :		int    							=      {
						    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(lowercase_						)
						}
						lowerCAmelCase__      :		Union[str, Any]    							=      {v: k for k, v in self.lang_code_to_id.items()}
						lowerCAmelCase__      :		Optional[int]    							=      len(self.sp_model						) + len(self.lang_code_to_id						) + self.fairseq_offset

						self.fairseq_tokens_to_ids.update(self.lang_code_to_id						)
						lowerCAmelCase__      :		Optional[Any]    							=      {v: k for k, v in self.fairseq_tokens_to_ids.items()}

						lowerCAmelCase__      :		str    							=      src_lang if src_lang is not None else '''en_XX'''
						lowerCAmelCase__      :		Dict    							=      self.lang_code_to_id[self._src_lang]
						lowerCAmelCase__      :		List[str]    							=      tgt_lang
						self.set_src_lang_special_tokens(self._src_lang						)







					@property
					def 			__lowerCAmelCase					(			self     :							Optional[int]						):
						return len(self.sp_model						) + len(self.lang_code_to_id						) + self.fairseq_offset + 1  # Plus 1 for the mask token







					@property
					def 			__lowerCAmelCase					(			self     :							Tuple						):
						return self._src_lang







					@src_lang.setter
					def 			__lowerCAmelCase					(			self     :							List[str]  ,lowercase_     :							str						):
						lowerCAmelCase__      :		Tuple    							=      new_src_lang
						self.set_src_lang_special_tokens(self._src_lang						)







					def __getstate__(			self     :							Optional[Any]						):
						lowerCAmelCase__      :		List[str]    							=      self.__dict__.copy()
						lowerCAmelCase__      :		Dict    							=      None
						return state







					def __setstate__(			self     :							str  ,lowercase_     :							Dict						):
						lowerCAmelCase__      :		Any    							=      d

						# for backward compatibility
						if not hasattr(self  ,'''sp_model_kwargs'''						):
							lowerCAmelCase__      :		List[Any]    							=      {}

						lowerCAmelCase__      :		Union[str, Any]    							=      spm.SentencePieceProcessor(**self.sp_model_kwargs						)
						self.sp_model.Load(self.vocab_file						)







					def 			__lowerCAmelCase					(			self     :							Any						):
						lowerCAmelCase__      :		List[Any]    							=      {self.convert_ids_to_tokens(lowercase_						): i for i in range(self.vocab_size						)}
						vocab.update(self.added_tokens_encoder						)
						return vocab







					def 			__lowerCAmelCase					(			self     :							List[Any]  ,lowercase_     :							str						):
						return self.sp_model.encode(lowercase_  ,out_type=lowercase_						)







					def 			__lowerCAmelCase					(			self     :							Union[str, Any]  ,lowercase_     :							str						):
						if token in self.fairseq_tokens_to_ids:
							return self.fairseq_tokens_to_ids[token]
						lowerCAmelCase__      :		List[Any]    							=      self.sp_model.PieceToId(lowercase_						)

						# Need to return unknown token if the SP model returned 0
						return spm_id + self.fairseq_offset if spm_id else self.unk_token_id







					def 			__lowerCAmelCase					(			self     :							str  ,lowercase_     :							int						):
						if index in self.fairseq_ids_to_tokens:
							return self.fairseq_ids_to_tokens[index]
						return self.sp_model.IdToPiece(index - self.fairseq_offset						)







					def 			__lowerCAmelCase					(			self     :							Optional[int]  ,lowercase_     :							int						):
						lowerCAmelCase__      :		Dict    							=      []
						lowerCAmelCase__      :		Any    							=      ''''''
						lowerCAmelCase__      :		Tuple    							=      False
						for token in tokens:
							# make sure that special tokens are not decoded using sentencepiece model
							if token in self.all_special_tokens:
								if not prev_is_special:
									out_string += " "
								out_string += self.sp_model.decode(lowercase_						) + token
								lowerCAmelCase__      :		Optional[int]    							=      True
								lowerCAmelCase__      :		str    							=      []
							else:
								current_sub_tokens.append(lowercase_						)
								lowerCAmelCase__      :		Optional[Any]    							=      False
						out_string += self.sp_model.decode(lowercase_						)
						return out_string.strip()







					def 			__lowerCAmelCase					(			self     :							List[Any]  ,lowercase_     :							str  ,lowercase_     :							Optional[str] = None						):
						if not os.path.isdir(lowercase_						):
							logger.error(F'Vocabulary path ({save_directory}) should be a directory'						)
							return
						lowerCAmelCase__      :		Tuple    							=      os.path.join(
						    lowercase_  ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']						)

						if os.path.abspath(self.vocab_file						) != os.path.abspath(lowercase_						) and os.path.isfile(self.vocab_file						):
							copyfile(self.vocab_file  ,lowercase_						)
						elif not os.path.isfile(self.vocab_file						):
							with open(lowercase_  ,'''wb'''						) as fi:
								lowerCAmelCase__      :		Any    							=      self.sp_model.serialized_model_proto()
								fi.write(lowercase_						)

						return (out_vocab_file,)







					def 			__lowerCAmelCase					(			self     :							Tuple  ,lowercase_     :							List[int]  ,lowercase_     :							Optional[List[int]] = None  ,lowercase_     :							bool = False						):

						if already_has_special_tokens:
							return super().get_special_tokens_mask(
							    token_ids_a=lowercase_  ,token_ids_a=lowercase_  ,already_has_special_tokens=lowercase_						)

						lowerCAmelCase__      :		List[str]    							=      [1] * len(self.prefix_tokens						)
						lowerCAmelCase__      :		int    							=      [1] * len(self.suffix_tokens						)
						if token_ids_a is None:
							return prefix_ones + ([0] * len(lowercase_						)) + suffix_ones
						return prefix_ones + ([0] * len(lowercase_						)) + ([0] * len(lowercase_						)) + suffix_ones







					def 			__lowerCAmelCase					(			self     :							Tuple  ,lowercase_     :							List[int]  ,lowercase_     :							Optional[List[int]] = None						):
						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     :							str  ,lowercase_     :							str  ,lowercase_     :							str  ,lowercase_     :							Optional[str]  ,lowercase_     :							Optional[str]  ,**lowercase_     :							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__      :		Optional[int]    							=      src_lang
						lowerCAmelCase__      :		Union[str, Any]    							=      self(lowercase_  ,add_special_tokens=lowercase_  ,return_tensors=lowercase_  ,**lowercase_						)
						lowerCAmelCase__      :		List[str]    							=      self.convert_tokens_to_ids(lowercase_						)
						lowerCAmelCase__      :		Union[str, Any]    							=      tgt_lang_id
						return inputs







					def 			__lowerCAmelCase					(			self     :							str  ,lowercase_     :							List[str]  ,lowercase_     :							str = "en_XX"  ,lowercase_     :							Optional[List[str]] = None  ,lowercase_     :							str = "ro_RO"  ,**lowercase_     :							List[Any]  ,):
						lowerCAmelCase__      :		Any    							=      src_lang
						lowerCAmelCase__      :		Dict    							=      tgt_lang
						return super().prepare_seqaseq_batch(lowercase_  ,lowercase_  ,**lowercase_						)







					def 			__lowerCAmelCase					(			self     :							int						):
						return self.set_src_lang_special_tokens(self.src_lang						)







					def 			__lowerCAmelCase					(			self     :							int						):
						return self.set_tgt_lang_special_tokens(self.tgt_lang						)







					def 			__lowerCAmelCase					(			self     :							Tuple  ,lowercase_     :							str						):
						lowerCAmelCase__      :		int    							=      self.lang_code_to_id[src_lang]
						lowerCAmelCase__      :		Optional[int]    							=      [self.cur_lang_code_id]
						lowerCAmelCase__      :		Dict    							=      [self.eos_token_id]







					def 			__lowerCAmelCase					(			self     :							List[str]  ,lowercase_     :							str						):
						lowerCAmelCase__      :		str    							=      self.lang_code_to_id[tgt_lang]
						lowerCAmelCase__      :		Union[str, Any]    							=      [self.cur_lang_code_id]
						lowerCAmelCase__      :		str    							=      [self.eos_token_id]







"""simple docstring"""





import warnings

from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor


__UpperCamelCase    : List[str]				 =						logging.get_logger(__name__)







class 							SCREAMING_SNAKE_CASE   (						a_			):






					"""simple docstring"""



					def __init__(			self     :							Any  ,*lowercase_     :							Dict  ,**lowercase_     :							List[str]						):
						warnings.warn(
						    '''The class ImageGPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
						    ''' Please use ImageGPTImageProcessor instead.'''  ,lowercase_  ,)
						super().__init__(*lowercase_  ,**lowercase_						)




