
'''simple docstring'''






from ...configuration_utils import PretrainedConfig


UpperCAmelCase_       :   Tuple   =       {
    'google/tapas-base-finetuned-sqa': (
        'https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'
    ),
    'google/tapas-base-finetuned-wtq': (
        'https://huggingface.co/google/tapas-base-finetuned-wtq/resolve/main/config.json'
    ),
    'google/tapas-base-finetuned-wikisql-supervised': (
        'https://huggingface.co/google/tapas-base-finetuned-wikisql-supervised/resolve/main/config.json'
    ),
    'google/tapas-base-finetuned-tabfact': (
        'https://huggingface.co/google/tapas-base-finetuned-tabfact/resolve/main/config.json'
    ),
}

class  UpperCAmelCase__						(       A ):
    lowerCAmelCase_				    =		'tapas'



    def __init__(	self      :       str,__A      :       Tuple=3_0_5_2_2,__A      :       Any=7_6_8,__A      :       Dict=1_2,__A      :       Optional[int]=1_2,__A      :       List[Any]=3_0_7_2,__A      :       Any="gelu",__A      :       List[str]=0.1,__A      :       List[str]=0.1,__A      :       Union[str, Any]=1_0_2_4,__A      :       List[Any]=[3, 2_5_6, 2_5_6, 2, 2_5_6, 2_5_6, 1_0],__A      :       str=0.02,__A      :       Dict=1e-12,__A      :       Dict=0,__A      :       str=10.0,__A      :       Dict=0,__A      :       Optional[Any]=1.0,__A      :       List[str]=None,__A      :       Optional[int]=1.0,__A      :       Optional[Any]=False,__A      :       Any=None,__A      :       List[str]=1.0,__A      :       Dict=1.0,__A      :       List[str]=False,__A      :       int=False,__A      :       List[Any]="ratio",__A      :       Optional[int]=None,__A      :       List[str]=None,__A      :       Union[str, Any]=6_4,__A      :       str=3_2,__A      :       List[str]=False,__A      :       int=True,__A      :       Dict=False,__A      :       str=False,__A      :       Optional[Any]=True,__A      :       str=False,__A      :       str=None,__A      :       Optional[Any]=None,**__A      :       Any,):
          super().__init__(pad_token_id=__A,**__A     )

          # BERT hyperparameters (with updated max_position_embeddings and type_vocab_sizes)
          _lowerCamelCase				:   List[Any]								=   vocab_size
          _lowerCamelCase				:   Optional[int]								=   hidden_size
          _lowerCamelCase				:   str								=   num_hidden_layers
          _lowerCamelCase				:   List[Any]								=   num_attention_heads
          _lowerCamelCase				:   Optional[Any]								=   hidden_act
          _lowerCamelCase				:   Any								=   intermediate_size
          _lowerCamelCase				:   List[str]								=   hidden_dropout_prob
          _lowerCamelCase				:   Optional[int]								=   attention_probs_dropout_prob
          _lowerCamelCase				:   Tuple								=   max_position_embeddings
          _lowerCamelCase				:   Optional[int]								=   type_vocab_sizes
          _lowerCamelCase				:   Dict								=   initializer_range
          _lowerCamelCase				:   Tuple								=   layer_norm_eps

          # Fine-tuning task hyperparameters
          _lowerCamelCase				:   Optional[int]								=   positive_label_weight
          _lowerCamelCase				:   Dict								=   num_aggregation_labels
          _lowerCamelCase				:   str								=   aggregation_loss_weight
          _lowerCamelCase				:   List[str]								=   use_answer_as_supervision
          _lowerCamelCase				:   Optional[int]								=   answer_loss_importance
          _lowerCamelCase				:   Union[str, Any]								=   use_normalized_answer_loss
          _lowerCamelCase				:   str								=   huber_loss_delta
          _lowerCamelCase				:   int								=   temperature
          _lowerCamelCase				:   str								=   aggregation_temperature
          _lowerCamelCase				:   Optional[int]								=   use_gumbel_for_cells
          _lowerCamelCase				:   Dict								=   use_gumbel_for_aggregation
          _lowerCamelCase				:   int								=   average_approximation_function
          _lowerCamelCase				:   str								=   cell_selection_preference
          _lowerCamelCase				:   Tuple								=   answer_loss_cutoff
          _lowerCamelCase				:   Tuple								=   max_num_rows
          _lowerCamelCase				:   Any								=   max_num_columns
          _lowerCamelCase				:   Optional[Any]								=   average_logits_per_cell
          _lowerCamelCase				:   Union[str, Any]								=   select_one_column
          _lowerCamelCase				:   List[Any]								=   allow_empty_column_selection
          _lowerCamelCase				:   Optional[int]								=   init_cell_selection_weights_to_zero
          _lowerCamelCase				:   Dict								=   reset_position_index_per_cell
          _lowerCamelCase				:   Union[str, Any]								=   disable_per_token_loss

          # Aggregation hyperparameters
          _lowerCamelCase				:   str								=   aggregation_labels
          _lowerCamelCase				:   Optional[Any]								=   no_aggregation_label_index

          if isinstance(self.aggregation_labels,__A     ):
                _lowerCamelCase				:   Tuple								=   {int(__A     ): v for k, v in aggregation_labels.items()}

'''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


UpperCAmelCase_       :   Union[str, Any]   =       logging.get_logger(__name__)

UpperCAmelCase_       :   Optional[int]   =       {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

UpperCAmelCase_       :   Union[str, Any]   =       {
    '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'
        )
    },
}

UpperCAmelCase_       :   Union[str, Any]   =       {
    'facebook/blenderbot_small-90M': 512,
}

class  UpperCAmelCase__						(       A ):
    lowerCAmelCase_				    =		VOCAB_FILES_NAMES
    lowerCAmelCase_				    =		PRETRAINED_VOCAB_FILES_MAP
    lowerCAmelCase_				    =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCAmelCase_				    =		BlenderbotSmallTokenizer



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



    def   lowerCamelCase_  (	self      :       Any,__A      :       Optional[Any],__A      :       Optional[int]=None     ):
          _lowerCamelCase				:   Any								=   [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   lowerCamelCase_  (	self      :       List[Any],__A      :       List[int],__A      :       Optional[List[int]] = None     ):
          _lowerCamelCase				:   Any								=   [self.sep_token_id]
          _lowerCamelCase				:   Union[str, Any]								=   [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]