






"""simple docstring"""



from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


if TYPE_CHECKING:
 from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


_lowerCAmelCase	:	List[str]				=      logging.get_logger(__name__)

_lowerCAmelCase	:	Any				=      {
    """microsoft/deberta-v2-xlarge""": """https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/config.json""",
    """microsoft/deberta-v2-xxlarge""": """https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/config.json""",
    """microsoft/deberta-v2-xlarge-mnli""": (
        """https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/config.json"""
    ),
    """microsoft/deberta-v2-xxlarge-mnli""": (
        """https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/config.json"""
    ),
}




class 			lowerCAmelCase__			(    __magic_name__   ):
   SCREAMING_SNAKE_CASE_    ='''deberta-v2'''
   def __init__(		self      :	Union[str, Any]							,			snake_case__      :	Tuple=1_2_8_1_0_0							,			snake_case__      :	int=1_5_3_6							,			snake_case__      :	int=2_4							,			snake_case__      :	Any=2_4							,			snake_case__      :	Any=6_1_4_4							,			snake_case__      :	List[str]="gelu"							,			snake_case__      :	str=0.1							,			snake_case__      :	Union[str, Any]=0.1							,			snake_case__      :	int=5_1_2							,			snake_case__      :	List[Any]=0							,			snake_case__      :	List[Any]=0.02							,			snake_case__      :	Tuple=1e-7							,			snake_case__      :	List[Any]=False							,			snake_case__      :	Dict=-1							,			snake_case__      :	Optional[int]=0							,			snake_case__      :	List[Any]=True							,			snake_case__      :	Tuple=None							,			snake_case__      :	Optional[int]=0							,			snake_case__      :	Union[str, Any]="gelu"							,			**snake_case__      :	List[Any]							,			):


        '''simple docstring'''
        super().__init__(**snake_case__							)

        UpperCAmelCase__						:    Union[str, Any]							=							hidden_size
        UpperCAmelCase__						:    Optional[Any]							=							num_hidden_layers
        UpperCAmelCase__						:    Dict							=							num_attention_heads
        UpperCAmelCase__						:    Optional[int]							=							intermediate_size
        UpperCAmelCase__						:    List[str]							=							hidden_act
        UpperCAmelCase__						:    Any							=							hidden_dropout_prob
        UpperCAmelCase__						:    Optional[Any]							=							attention_probs_dropout_prob
        UpperCAmelCase__						:    Optional[int]							=							max_position_embeddings
        UpperCAmelCase__						:    Any							=							type_vocab_size
        UpperCAmelCase__						:    List[str]							=							initializer_range
        UpperCAmelCase__						:    Union[str, Any]							=							relative_attention
        UpperCAmelCase__						:    Dict							=							max_relative_positions
        UpperCAmelCase__						:    int							=							pad_token_id
        UpperCAmelCase__						:    str							=							position_biased_input

        # Backwards compatibility
        if type(snake_case__							) == str:
             UpperCAmelCase__						:    Tuple							=							[x.strip() for x in pos_att_type.lower().split("|"							)]

        UpperCAmelCase__						:    str							=							pos_att_type
        UpperCAmelCase__						:    Dict							=							vocab_size
        UpperCAmelCase__						:    Tuple							=							layer_norm_eps

        UpperCAmelCase__						:    List[str]							=							kwargs.get("pooler_hidden_size"							,			snake_case__							)
        UpperCAmelCase__						:    Any							=							pooler_dropout
        UpperCAmelCase__						:    Union[str, Any]							=							pooler_hidden_act




class 			lowerCAmelCase__			(    __magic_name__   ):
   @property
   def       __a							(		self      :	int							):


        '''simple docstring'''
        if self.task == "multiple-choice":
             UpperCAmelCase__						:    Any							=							{0: "batch", 1: "choice", 2: "sequence"}
        else:
             UpperCAmelCase__						:    Dict							=							{0: "batch", 1: "sequence"}
        if self._config.type_vocab_size > 0:
             return OrderedDict(
                 [("input_ids", dynamic_axis), ("attention_mask", dynamic_axis), ("token_type_ids", dynamic_axis)]							)
        else:
             return OrderedDict([("input_ids", dynamic_axis), ("attention_mask", dynamic_axis)]							)
   @property
   def       __a							(		self      :	Tuple							):


        '''simple docstring'''
        return 1_2




   def       __a							(		self      :	str							,			snake_case__      :	Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]							,			snake_case__      :	int = -1							,			snake_case__      :	int = -1							,			snake_case__      :	int = -1							,			snake_case__      :	bool = False							,			snake_case__      :	Optional["TensorType"] = None							,			snake_case__      :	int = 3							,			snake_case__      :	int = 4_0							,			snake_case__      :	int = 4_0							,			snake_case__      :	"PreTrainedTokenizerBase" = None							,			):


        '''simple docstring'''
        UpperCAmelCase__						:    Union[str, Any]							=							super().generate_dummy_inputs(preprocessor=snake_case__							,			framework=snake_case__							)
        if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
             del dummy_inputs["token_type_ids"]
        return dummy_inputs










"""simple docstring"""



def 	SCREAMING_SNAKE_CASE__       (  snake_case       : list				)->		list:






     '''simple docstring'''



     UpperCAmelCase__						:    List[str]							=							False
     while is_sorted is False:  # Until all the indices are traversed keep looping
          UpperCAmelCase__						:    List[Any]							=							True
          for i in range(0			,					len(snake_case				) - 1			,					2				):  # iterating over all even indices
               if input_list[i] > input_list[i + 1]:
                    UpperCAmelCase__							,				UpperCAmelCase__						:    Optional[int]							=							input_list[i + 1], input_list[i]
                    # swapping if elements not in order
                    UpperCAmelCase__						:    int							=							False

          for i in range(1			,					len(snake_case				) - 1			,					2				):  # iterating over all odd indices
               if input_list[i] > input_list[i + 1]:
                    UpperCAmelCase__							,				UpperCAmelCase__						:    Optional[int]							=							input_list[i + 1], input_list[i]
                    # swapping if elements not in order
                    UpperCAmelCase__						:    str							=							False
     return input_list


if __name__ == "__main__":
 print("""Enter list to be sorted""")
 _lowerCAmelCase	:	List[str]				=      [int(x) for x in input().split()]
 # inputing elements of the list in one line
 _lowerCAmelCase	:	Optional[int]				=      odd_even_sort(input_list)
 print("""The sorted list is""")
 print(sorted_list)


