





"""simple docstring"""
from ...configuration_utils import PretrainedConfig


lowerCamelCase_								=		{
    "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 					_SCREAMING_SNAKE_CASE(   _UpperCAmelCase  ):
       SCREAMING_SNAKE_CASE_   :      Dict							=  '''tapas'''




       def __init__(						self		,SCREAMING_SNAKE_CASE__=3_05_22		,SCREAMING_SNAKE_CASE__=7_68		,SCREAMING_SNAKE_CASE__=12		,SCREAMING_SNAKE_CASE__=12		,SCREAMING_SNAKE_CASE__=30_72		,SCREAMING_SNAKE_CASE__="gelu"		,SCREAMING_SNAKE_CASE__=0.1		,SCREAMING_SNAKE_CASE__=0.1		,SCREAMING_SNAKE_CASE__=10_24		,SCREAMING_SNAKE_CASE__=[3, 2_56, 2_56, 2, 2_56, 2_56, 10]		,SCREAMING_SNAKE_CASE__=0.0_2		,SCREAMING_SNAKE_CASE__=1E-12		,SCREAMING_SNAKE_CASE__=0		,SCREAMING_SNAKE_CASE__=1_0.0		,SCREAMING_SNAKE_CASE__=0		,SCREAMING_SNAKE_CASE__=1.0		,SCREAMING_SNAKE_CASE__=None		,SCREAMING_SNAKE_CASE__=1.0		,SCREAMING_SNAKE_CASE__=False		,SCREAMING_SNAKE_CASE__=None		,SCREAMING_SNAKE_CASE__=1.0		,SCREAMING_SNAKE_CASE__=1.0		,SCREAMING_SNAKE_CASE__=False		,SCREAMING_SNAKE_CASE__=False		,SCREAMING_SNAKE_CASE__="ratio"		,SCREAMING_SNAKE_CASE__=None		,SCREAMING_SNAKE_CASE__=None		,SCREAMING_SNAKE_CASE__=64		,SCREAMING_SNAKE_CASE__=32		,SCREAMING_SNAKE_CASE__=False		,SCREAMING_SNAKE_CASE__=True		,SCREAMING_SNAKE_CASE__=False		,SCREAMING_SNAKE_CASE__=False		,SCREAMING_SNAKE_CASE__=True		,SCREAMING_SNAKE_CASE__=False		,SCREAMING_SNAKE_CASE__=None		,SCREAMING_SNAKE_CASE__=None		,**SCREAMING_SNAKE_CASE__		,)			->      str:





             """simple docstring"""






             super().__init__(pad_token_id=lowercase_		,**lowercase_							)

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

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

             # Aggregation hyperparameters
             __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  aggregation_labels
             __SCREAMING_SNAKE_CASE   :List[str]						=  no_aggregation_label_index

             if isinstance(self.aggregation_labels		,lowercase_							):
                   __SCREAMING_SNAKE_CASE   :str						=  {int(lowercase_							): v for k, v in aggregation_labels.items()}


import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def 						_snake_case(    SCREAMING_SNAKE_CASE__			:	Union[str, Any]      )							->      Union[str, Any]:





    '''simple docstring'''






    return EnvironmentCommand()


class  A						(							_UpperCAmelCase ):







    """simple docstring"""





    @staticmethod
    def 						snake_case__     (      lowercase_ :       ArgumentParser		)->    Dict:





        '''simple docstring'''







        A__          =   parser.add_parser('env'		)
        download_parser.set_defaults(func=lowercase_		)


    def 						snake_case__     (      self :       List[Any]		)->    List[str]:





        '''simple docstring'''







        A__          =   huggingface_hub.__version__

        A__          =   'not installed'
        A__          =   'NA'
        if is_torch_available():
            import torch

            A__          =   torch.__version__
            A__          =   torch.cuda.is_available()

        A__          =   'not installed'
        if is_transformers_available():
            import transformers

            A__          =   transformers.__version__

        A__          =   'not installed'
        if is_accelerate_available():
            import accelerate

            A__          =   accelerate.__version__

        A__          =   'not installed'
        if is_xformers_available():
            import xformers

            A__          =   xformers.__version__

        A__          =   {
            '`diffusers` version': version,
            'Platform': platform.platform(),
            'Python version': platform.python_version(),
            'PyTorch version (GPU?)': F'{pt_version} ({pt_cuda_available})',
            'Huggingface_hub version': hub_version,
            'Transformers version': transformers_version,
            'Accelerate version': accelerate_version,
            'xFormers version': xformers_version,
            'Using GPU in script?': '<fill in>',
            'Using distributed or parallel set-up in script?': '<fill in>',
        }

        print('\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n'		)
        print(self.format_dict(lowercase_		)		)

        return info


    @staticmethod
    def 						snake_case__     (      lowercase_ :       int		)->    Optional[Any]:





        '''simple docstring'''







        return "\n".join([F'- {prop}: {val}' for prop, val in d.items()]		) + "\n"

