


'''simple docstring'''






from ...configuration_utils import PretrainedConfig


__A					:  int											=      {
    "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    __snake_case       (   _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    lowercase    =					'tapas'

    def __init__(   self    :  int    ,						lowerCamelCase    :  str=3_05_22    ,						lowerCamelCase    :  Optional[Any]=7_68    ,						lowerCamelCase    :  Tuple=12    ,						lowerCamelCase    :  Dict=12    ,						lowerCamelCase    :  str=30_72    ,						lowerCamelCase    :  List[str]="gelu"    ,						lowerCamelCase    :  int=0.1    ,						lowerCamelCase    :  Any=0.1    ,						lowerCamelCase    :  Union[str, Any]=10_24    ,						lowerCamelCase    :  Union[str, Any]=[3, 2_56, 2_56, 2, 2_56, 2_56, 10]    ,						lowerCamelCase    :  Union[str, Any]=0.02    ,						lowerCamelCase    :  Any=1E-12    ,						lowerCamelCase    :  Optional[int]=0    ,						lowerCamelCase    :  str=10.0    ,						lowerCamelCase    :  Any=0    ,						lowerCamelCase    :  Optional[int]=1.0    ,						lowerCamelCase    :  int=None    ,						lowerCamelCase    :  Tuple=1.0    ,						lowerCamelCase    :  Optional[Any]=False    ,						lowerCamelCase    :  List[str]=None    ,						lowerCamelCase    :  int=1.0    ,						lowerCamelCase    :  str=1.0    ,						lowerCamelCase    :  List[str]=False    ,						lowerCamelCase    :  str=False    ,						lowerCamelCase    :  Optional[int]="ratio"    ,						lowerCamelCase    :  Optional[int]=None    ,						lowerCamelCase    :  Any=None    ,						lowerCamelCase    :  int=64    ,						lowerCamelCase    :  Any=32    ,						lowerCamelCase    :  Optional[int]=False    ,						lowerCamelCase    :  str=True    ,						lowerCamelCase    :  Dict=False    ,						lowerCamelCase    :  Tuple=False    ,						lowerCamelCase    :  List[str]=True    ,						lowerCamelCase    :  Union[str, Any]=False    ,						lowerCamelCase    :  Any=None    ,						lowerCamelCase    :  List[Any]=None    ,						**lowerCamelCase    :  str    ,						)   ->  Any:
      super().__init__(pad_token_id=lowerCamelCase    ,						**lowerCamelCase		)

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

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

      # Aggregation hyperparameters
      lowerCAmelCase_			:      Any			=   aggregation_labels
      lowerCAmelCase_			:      Optional[Any]			=   no_aggregation_label_index

      if isinstance(self.aggregation_labels    ,						lowerCamelCase		):
        lowerCAmelCase_			:      Optional[int]			=   {int(lowerCamelCase		): v for k, v in aggregation_labels.items()}







'''simple docstring'''






# Copyright 2023 The HuggingFace Inc. 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 ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool






class    __snake_case       (   _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    lowercase    =					'philschmid/bart-large-cnn-samsum'
    lowercase    =					(
        'This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, '
        'and returns a summary of the text.'
    )
    lowercase    =					'summarizer'
    lowercase    =					AutoTokenizer
    lowercase    =					AutoModelForSeqaSeqLM

    lowercase    =					['text']
    lowercase    =					['text']

    def __lowercase   (   self    :  Dict    ,						lowerCamelCase    :  Dict		)   ->  Any:
      return self.pre_processor(lowerCamelCase    ,						return_tensors="""pt"""    ,						truncation=lowerCamelCase		)

    def __lowercase   (   self    :  Optional[Any]    ,						lowerCamelCase    :  Tuple		)   ->  List[str]:
      return self.model.generate(**lowerCamelCase		)[0]





    def __lowercase   (   self    :  str    ,						lowerCamelCase    :  Dict		)   ->  List[Any]:
      return self.pre_processor.decode(lowerCamelCase    ,						skip_special_tokens=lowerCamelCase    ,						clean_up_tokenization_spaces=lowerCamelCase		)



