


"""simple docstring"""


from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


_snake_case          =							logging.get_logger(__name__)

_snake_case          =							{
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

_snake_case          =							{
    "vocab_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"
    },
    "merges_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"
    },
    "tokenizer_config_file": {
        "facebook/blenderbot_small-90M": (
            "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"
        )
    },
}

_snake_case          =							{
    "facebook/blenderbot_small-90M": 512,
}



class   _a      (      SCREAMING_SNAKE_CASE_ ):
    a_    :				Union[str, Any]             =    VOCAB_FILES_NAMES
    a_    :				str             =    PRETRAINED_VOCAB_FILES_MAP
    a_    :				Union[str, Any]             =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a_    :				Union[str, Any]             =    BlenderbotSmallTokenizer
    def __init__( self							:					Optional[Any]							,					SCREAMING_SNAKE_CASE__							:					int=None							,					SCREAMING_SNAKE_CASE__							:					Dict=None							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]="<|endoftext|>"							,					SCREAMING_SNAKE_CASE__							:					int="<|endoftext|>"							,					SCREAMING_SNAKE_CASE__							:					List[Any]="<|endoftext|>"							,					SCREAMING_SNAKE_CASE__							:					Dict=False							,					SCREAMING_SNAKE_CASE__							:					Tuple=True							,					**SCREAMING_SNAKE_CASE__							:					Optional[int]							,					):
          super().__init__(
              ByteLevelBPETokenizer(
                  vocab=SCREAMING_SNAKE_CASE__							,					merges=SCREAMING_SNAKE_CASE__							,					add_prefix_space=SCREAMING_SNAKE_CASE__							,					trim_offsets=SCREAMING_SNAKE_CASE__							,					)							,					bos_token=SCREAMING_SNAKE_CASE__							,					eos_token=SCREAMING_SNAKE_CASE__							,					unk_token=SCREAMING_SNAKE_CASE__							,					**SCREAMING_SNAKE_CASE__							,					)
          lowerCamelCase__           =		add_prefix_space
    def      _UpperCamelCase       ( self							:					str							,					SCREAMING_SNAKE_CASE__							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					Any=None				):
          lowerCamelCase__           =		[self.bos_token_id] + token_ids_a + [self.eos_token_id]
          if token_ids_a is None:
                return output

          return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]


    def      _UpperCamelCase       ( self							:					int							,					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]







"""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."
)



