from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
UpperCAmelCase					      =							Lock()






def        SCREAMING_SNAKE_CASE_      (		lowerCAmelCase_:			Optional[Any]			,						lowerCAmelCase_:			Optional[Any]			,						lowerCAmelCase_:			List[str]			,						lowerCAmelCase_:			List[Any]			,						lowerCAmelCase_:			List[Any]			,						lowerCAmelCase_:			str			,						lowerCAmelCase_:			Tuple  ):
      global process_lock

      # we perform n swaps since after n swaps we know we are sorted
      # we *could* stop early if we are sorted already, but it takes as long to
      # find out we are sorted as it does to sort the list with this algorithm
      for i in range(0			,						1_0  ):
            if (i + position) % 2 == 0 and r_send is not None:
                  # send your value to your right neighbor
                  process_lock.acquire()
                  r_send[1].send(snake_case__  )
                  process_lock.release()

                  # receive your right neighbor's value
                  process_lock.acquire()
                  snake_case_  :      List[str]  	=							rr_cv[0].recv()
                  process_lock.release()

                  # take the lower value since you are on the left
                  snake_case_  :      List[Any]  	=							min(snake_case__			,						snake_case__  )
            elif (i + position) % 2 != 0 and l_send is not None:
                  # send your value to your left neighbor
                  process_lock.acquire()
                  l_send[1].send(snake_case__  )
                  process_lock.release()

                  # receive your left neighbor's value
                  process_lock.acquire()
                  snake_case_  :      List[Any]  	=							lr_cv[0].recv()
                  process_lock.release()

                  # take the higher value since you are on the right
                  snake_case_  :      Optional[int]  	=							max(snake_case__			,						snake_case__  )
    # after all swaps are performed, send the values back to main
      result_pipe[1].send(snake_case__  )






def        SCREAMING_SNAKE_CASE_      (		lowerCAmelCase_:			Optional[Any]  ):
      snake_case_  :      Optional[Any]  	=							[]
      snake_case_  :      Tuple  	=							[]
      # initialize the list of pipes where the values will be retrieved
      for _ in arr:
            result_pipe.append(Pipe()  )
      # creates the processes
      # the first and last process only have one neighbor so they are made outside
      # of the loop
      snake_case_  :      Tuple  	=							Pipe()
      snake_case_  :      Optional[Any]  	=							Pipe()
      process_array_.append(
          Process(
              target=snake_case__			,						args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])			,						)  )
      snake_case_  :      int  	=							temp_rs
      snake_case_  :      List[Any]  	=							temp_rr

      for i in range(1			,						len(snake_case__  ) - 1  ):
            snake_case_  :      List[str]  	=							Pipe()
            snake_case_  :      Tuple  	=							Pipe()
            process_array_.append(
                Process(
                    target=snake_case__			,						args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i])			,						)  )
            snake_case_  :      Dict  	=							temp_rs
            snake_case_  :      Any  	=							temp_rr

      process_array_.append(
          Process(
              target=snake_case__			,						args=(
                  len(snake_case__  ) - 1,
                  arr[len(snake_case__  ) - 1],
                  temp_ls,
                  None,
                  temp_lr,
                  None,
                  result_pipe[len(snake_case__  ) - 1],
              )			,						)  )

      # start the processes
      for p in process_array_:
            p.start()

      # wait for the processes to end and write their values to the list
      for p in range(0			,						len(snake_case__  )  ):
            snake_case_  :      Union[str, Any]  	=							result_pipe[p][0].recv()
            process_array_[p].join()
      return arr






def        SCREAMING_SNAKE_CASE_      (		):
      snake_case_  :      List[Any]  	=							list(range(1_0			,						0			,						-1  )  )
      print("Initial List"  )
      print(*snake_case__  )
      snake_case_  :      Any  	=							odd_even_transposition(snake_case__  )
      print("Sorted List\n"  )
      print(*snake_case__  )


if __name__ == "__main__":
     main()











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       snake_case__ (				lowercase_):

       '''simple docstring'''
       lowerCamelCase				:					Tuple								=			"tapas"



       def __init__(				self      ,    a__=3_05_22      ,    a__=7_68      ,    a__=12      ,    a__=12      ,    a__=30_72      ,    a__="gelu"      ,    a__=0.1      ,    a__=0.1      ,    a__=10_24      ,    a__=[3, 2_56, 2_56, 2, 2_56, 2_56, 10]      ,    a__=0.02      ,    a__=1e-12      ,    a__=0      ,    a__=10.0      ,    a__=0      ,    a__=1.0      ,    a__=None      ,    a__=1.0      ,    a__=False      ,    a__=None      ,    a__=1.0      ,    a__=1.0      ,    a__=False      ,    a__=False      ,    a__="ratio"      ,    a__=None      ,    a__=None      ,    a__=64      ,    a__=32      ,    a__=False      ,    a__=True      ,    a__=False      ,    a__=False      ,    a__=True      ,    a__=False      ,    a__=None      ,    a__=None      ,    **a__      ,    )			->   Any:






            '''simple docstring'''





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

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

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

            # Aggregation hyperparameters
            __snake_case      :List[str] 							=    aggregation_labels
            __snake_case      :int 							=    no_aggregation_label_index

            if isinstance(self.aggregation_labels      ,    a__     ):
                 __snake_case      :Any 							=    {int(a__     ): v for k, v in aggregation_labels.items()}


