


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


A      = logging.get_logger(__name__)

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

A      = {
    "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"
        )
    },
}

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


class     lowercase__  (					__SCREAMING_SNAKE_CASE		):
  A__=  VOCAB_FILES_NAMES
  A__=  PRETRAINED_VOCAB_FILES_MAP
  A__=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  A__=  BlenderbotSmallTokenizer






  def __init__(					self      :					Union[str, Any]		,						_lowercase      :					Union[str, Any]=None		,						_lowercase      :					Tuple=None		,						_lowercase      :					int="<|endoftext|>"		,						_lowercase      :					Tuple="<|endoftext|>"		,						_lowercase      :					Dict="<|endoftext|>"		,						_lowercase      :					Any=False		,						_lowercase      :					Optional[Any]=True		,						**_lowercase      :					Any		,						):




         """simple docstring"""







         super().__init__(
             ByteLevelBPETokenizer(
                 vocab=_lowercase		,						merges=_lowercase		,						add_prefix_space=_lowercase		,						trim_offsets=_lowercase		,						)		,						bos_token=_lowercase		,						eos_token=_lowercase		,						unk_token=_lowercase		,						**_lowercase		,						)
         UpperCAmelCase__										=     add_prefix_space






  def 			_UpperCAmelCase  (					self      :					List[str]		,						_lowercase      :					Dict		,						_lowercase      :					Optional[int]=None ):




         """simple docstring"""







         UpperCAmelCase__										=     [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		,						_lowercase      :					List[int]		,						_lowercase      :					Optional[List[int]] = None ):




         """simple docstring"""







         UpperCAmelCase__										=     [self.sep_token_id]
         UpperCAmelCase__										=     [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]









from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A      = {"configuration_mmbt": ["MMBTConfig"]}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A      = ["MMBTForClassification", "MMBTModel", "ModalEmbeddings"]


if TYPE_CHECKING:
    from .configuration_mmbt import MMBTConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mmbt import MMBTForClassification, MMBTModel, ModalEmbeddings

else:
    import sys

    A      = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





