


'''simple docstring'''




# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__snake_case    						={
    """configuration_efficientnet""": [
        """EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """EfficientNetConfig""",
        """EfficientNetOnnxConfig""",
    ]
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __snake_case    						=["""EfficientNetImageProcessor"""]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __snake_case    						=[
           """EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """EfficientNetForImageClassification""",
           """EfficientNetModel""",
           """EfficientNetPreTrainedModel""",
       ]

if TYPE_CHECKING:
       from .configuration_efficientnet import (
           EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP,
           EfficientNetConfig,
           EfficientNetOnnxConfig,
       )

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .image_processing_efficientnet import EfficientNetImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_efficientnet import (
                  EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                  EfficientNetForImageClassification,
                  EfficientNetModel,
                  EfficientNetPreTrainedModel,
              )

else:
       import sys

       __snake_case    						=_LazyModule(__name__, globals()["""__file__"""], _import_structure)









'''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 		UpperCAmelCase_      (  __lowercase		):
     lowerCamelCase				:	Tuple		=     VOCAB_FILES_NAMES
     lowerCamelCase				:	Optional[int]		=     PRETRAINED_VOCAB_FILES_MAP
     lowerCamelCase				:	Union[str, Any]		=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCamelCase				:	Optional[Any]		=     BlenderbotSmallTokenizer





     def __init__( self       :      Any    ,      UpperCAmelCase__       :      Union[str, Any]=None    ,      UpperCAmelCase__       :      Dict=None    ,      UpperCAmelCase__       :      int="<|endoftext|>"    ,      UpperCAmelCase__       :      Dict="<|endoftext|>"    ,      UpperCAmelCase__       :      str="<|endoftext|>"    ,      UpperCAmelCase__       :      str=False    ,      UpperCAmelCase__       :      Tuple=True    ,      **UpperCAmelCase__       :      Optional[Any]    ,      )				->  Any:
        super().__init__(
            ByteLevelBPETokenizer(
                vocab=UpperCAmelCase__    ,      merges=UpperCAmelCase__    ,      add_prefix_space=UpperCAmelCase__    ,      trim_offsets=UpperCAmelCase__    ,      )    ,      bos_token=UpperCAmelCase__    ,      eos_token=UpperCAmelCase__    ,      unk_token=UpperCAmelCase__    ,      **UpperCAmelCase__    ,      )
        lowerCAmelCase     =			add_prefix_space





     def 							__UpperCAmelCase      ( self       :      List[Any]    ,      UpperCAmelCase__       :      Union[str, Any]    ,      UpperCAmelCase__       :      Dict=None    )				->  Any:
        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       :      Any    ,      UpperCAmelCase__       :      List[int]    ,      UpperCAmelCase__       :      Optional[List[int]] = None    )				->  List[int]:
        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]





