



"""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:
   _snake_case          =							None


_snake_case          =							logging.get_logger(__name__)


_snake_case          =							{"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

_snake_case          =							{
    "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",
    },
}

_snake_case          =							{
    "facebook/mbart-large-en-ro": 1024,
    "facebook/mbart-large-cc25": 1024,
}

# fmt: off
_snake_case          =							["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      (      UpperCAmelCase__ ):
    a_    :				List[str]             =    VOCAB_FILES_NAMES
    a_    :				Tuple             =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a_    :				str             =    PRETRAINED_VOCAB_FILES_MAP
    a_    :				Any             =    ["input_ids", "attention_mask"]
    a_    :				int             =    MBartTokenizer

    a_    :				List[int]             =    []
    a_    :				List[int]             =    []
    def __init__( self							:					int							,					SCREAMING_SNAKE_CASE__							:					Any=None							,					SCREAMING_SNAKE_CASE__							:					List[Any]=None							,					SCREAMING_SNAKE_CASE__							:					int="<s>"							,					SCREAMING_SNAKE_CASE__							:					str="</s>"							,					SCREAMING_SNAKE_CASE__							:					Tuple="</s>"							,					SCREAMING_SNAKE_CASE__							:					str="<s>"							,					SCREAMING_SNAKE_CASE__							:					List[Any]="<unk>"							,					SCREAMING_SNAKE_CASE__							:					Dict="<pad>"							,					SCREAMING_SNAKE_CASE__							:					List[str]="<mask>"							,					SCREAMING_SNAKE_CASE__							:					Optional[int]=None							,					SCREAMING_SNAKE_CASE__							:					int=None							,					SCREAMING_SNAKE_CASE__							:					List[str]=None							,					**SCREAMING_SNAKE_CASE__							:					str							,					):
          lowerCamelCase__           =		AddedToken(lowerCamelCase__							,					lstrip=lowerCamelCase__							,					rstrip=lowerCamelCase__				) if isinstance(lowerCamelCase__							,					lowerCamelCase__				) else mask_token

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

          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(lowerCamelCase__				) 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      _UpperCamelCase       ( self							:					str				):
          return self._src_lang
    @src_lang.setter
    def      _UpperCamelCase       ( self							:					Union[str, Any]							,					SCREAMING_SNAKE_CASE__							:					str				):
          lowerCamelCase__           =		new_src_lang
          self.set_src_lang_special_tokens(self._src_lang				)
    def      _UpperCamelCase       ( self							:					str							,					SCREAMING_SNAKE_CASE__							:					List[int]							,					SCREAMING_SNAKE_CASE__							:					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      _UpperCamelCase       ( self							:					Tuple							,					SCREAMING_SNAKE_CASE__							:					List[int]							,					SCREAMING_SNAKE_CASE__							:					Optional[List[int]] = None				):
          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      _UpperCamelCase       ( self							:					Any							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]							,					SCREAMING_SNAKE_CASE__							:					str							,					SCREAMING_SNAKE_CASE__							:					Optional[str]							,					SCREAMING_SNAKE_CASE__							:					Optional[str]							,					**SCREAMING_SNAKE_CASE__							:					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'				)
          lowerCamelCase__           =		src_lang
          lowerCamelCase__           =		self(lowerCamelCase__							,					add_special_tokens=lowerCamelCase__							,					return_tensors=lowerCamelCase__							,					**lowerCamelCase__				)
          lowerCamelCase__           =		self.convert_tokens_to_ids(lowerCamelCase__				)
          lowerCamelCase__           =		tgt_lang_id
          return inputs
    def      _UpperCamelCase       ( self							:					int							,					SCREAMING_SNAKE_CASE__							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					str = "en_XX"							,					SCREAMING_SNAKE_CASE__							:					Optional[List[str]] = None							,					SCREAMING_SNAKE_CASE__							:					str = "ro_RO"							,					**SCREAMING_SNAKE_CASE__							:					List[Any]							,					):
          lowerCamelCase__           =		src_lang
          lowerCamelCase__           =		tgt_lang
          return super().prepare_seqaseq_batch(lowerCamelCase__							,					lowerCamelCase__							,					**lowerCamelCase__				)
    def      _UpperCamelCase       ( self							:					Optional[Any]				):
          return self.set_src_lang_special_tokens(self.src_lang				)
    def      _UpperCamelCase       ( self							:					Union[str, Any]				):
          return self.set_tgt_lang_special_tokens(self.tgt_lang				)
    def      _UpperCamelCase       ( self							:					Dict							,					SCREAMING_SNAKE_CASE__							:					int				):
          lowerCamelCase__           =		self.convert_tokens_to_ids(lowerCamelCase__				)
          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      _UpperCamelCase       ( self							:					str							,					SCREAMING_SNAKE_CASE__							:					str				):
          lowerCamelCase__           =		self.convert_tokens_to_ids(lowerCamelCase__				)
          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      _UpperCamelCase       ( self							:					Union[str, Any]							,					SCREAMING_SNAKE_CASE__							:					str							,					SCREAMING_SNAKE_CASE__							:					Optional[str] = None				):







          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(lowerCamelCase__				):
                logger.error(F'Vocabulary path ({save_directory}) should be a directory.'				)
                return
          lowerCamelCase__           =		os.path.join(
              lowerCamelCase__							,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']				)

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

          return (out_vocab_file,)







"""simple docstring"""


import warnings

from diffusers import StableDiffusionImgaImgPipeline  # noqa F401


warnings.warn(
    "The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
    " StableDiffusionImg2ImgPipeline` instead."
)



