

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


A_						:     str			  =				logging.get_logger(__name__)

A_						:     Any			  =				{
    'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/config.json',
    'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/config.json',
    'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/config.json',
    'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/config.json',
    'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/config.json',
    'microsoft/deberta-xlarge-mnli': 'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/config.json',
}
class    A_				( _a  ):


    '''simple docstring'''






    a__       							=    "deberta"


    def __init__(self       , lowercase__=50_265       , lowercase__=768       , lowercase__=12       , lowercase__=12       , lowercase__=3_072       , lowercase__="gelu"       , lowercase__=0.1       , lowercase__=0.1       , lowercase__=512       , lowercase__=0       , lowercase__=0.02       , lowercase__=1E-7       , lowercase__=False       , lowercase__=-1       , lowercase__=0       , lowercase__=True       , lowercase__=None       , lowercase__=0       , lowercase__="gelu"       , **lowercase__       , )       -> Any:
        super().__init__(**lowercase__					)

        __UpperCAmelCase			   =     hidden_size
        __UpperCAmelCase			   =     num_hidden_layers
        __UpperCAmelCase			   =     num_attention_heads
        __UpperCAmelCase			   =     intermediate_size
        __UpperCAmelCase			   =     hidden_act
        __UpperCAmelCase			   =     hidden_dropout_prob
        __UpperCAmelCase			   =     attention_probs_dropout_prob
        __UpperCAmelCase			   =     max_position_embeddings
        __UpperCAmelCase			   =     type_vocab_size
        __UpperCAmelCase			   =     initializer_range
        __UpperCAmelCase			   =     relative_attention
        __UpperCAmelCase			   =     max_relative_positions
        __UpperCAmelCase			   =     pad_token_id
        __UpperCAmelCase			   =     position_biased_input

        # Backwards compatibility
        if type(lowercase__					) == str:
            __UpperCAmelCase			   =     [x.strip() for x in pos_att_type.lower().split('''|'''					)]

        __UpperCAmelCase			   =     pos_att_type
        __UpperCAmelCase			   =     vocab_size
        __UpperCAmelCase			   =     layer_norm_eps

        __UpperCAmelCase			   =     kwargs.get('''pooler_hidden_size'''       , lowercase__					)
        __UpperCAmelCase			   =     pooler_dropout
        __UpperCAmelCase			   =     pooler_hidden_act






class    A_				( _a  ):


    '''simple docstring'''






    @property
    def        lowerCAmelCase_  (self					)       -> Mapping[str, Mapping[int, str]]:
        if self.task == "multiple-choice":
            __UpperCAmelCase			   =     {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
        else:
            __UpperCAmelCase			   =     {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        lowerCAmelCase_  (self					)       -> int:
        return 12






    def        lowerCAmelCase_  (self       , lowercase__       , lowercase__ = -1       , lowercase__ = -1       , lowercase__ = -1       , lowercase__ = False       , lowercase__ = None       , lowercase__ = 3       , lowercase__ = 40       , lowercase__ = 40       , lowercase__ = None       , )       -> Mapping[str, Any]:
        __UpperCAmelCase			   =     super().generate_dummy_inputs(preprocessor=lowercase__       , framework=lowercase__					)
        if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
            del dummy_inputs["token_type_ids"]
        return dummy_inputs








from __future__ import annotations


def  __a    (				SCREAMING_SNAKE_CASE ) ->       list[int]:






    '''simple docstring'''
    if not list_of_ints:
        return []

    if min(SCREAMING_SNAKE_CASE ) < 0:
        raise ValueError('''All numbers must be positive''' )

    __UpperCAmelCase			   =     max(len(bin(SCREAMING_SNAKE_CASE )[2:] ) for x in list_of_ints )
    return _msd_radix_sort(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE )


def  __a    (				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE ) ->       list[int]:






    '''simple docstring'''
    if bit_position == 0 or len(SCREAMING_SNAKE_CASE ) in [0, 1]:
        return list_of_ints

    __UpperCAmelCase			   =     []
    __UpperCAmelCase			   =     []
    # Split numbers based on bit at bit_position from the right
    for number in list_of_ints:
        if (number >> (bit_position - 1)) & 1:
            # number has a one at bit bit_position
            ones.append(SCREAMING_SNAKE_CASE )
        else:
            # number has a zero at bit bit_position
            zeros.append(SCREAMING_SNAKE_CASE )

    # recursively split both lists further
    __UpperCAmelCase			   =     _msd_radix_sort(SCREAMING_SNAKE_CASE    ,				bit_position - 1 )
    __UpperCAmelCase			   =     _msd_radix_sort(SCREAMING_SNAKE_CASE    ,				bit_position - 1 )

    # recombine lists
    __UpperCAmelCase			   =     zeros
    res.extend(SCREAMING_SNAKE_CASE )

    return res


def  __a    (				SCREAMING_SNAKE_CASE ) ->       Optional[int]:






    '''simple docstring'''
    __UpperCAmelCase			   =     len(SCREAMING_SNAKE_CASE )
    if not list_of_ints or length == 1:
        return

    if min(SCREAMING_SNAKE_CASE ) < 0:
        raise ValueError('''All numbers must be positive''' )

    __UpperCAmelCase			   =     max(len(bin(SCREAMING_SNAKE_CASE )[2:] ) for x in list_of_ints )
    _msd_radix_sort_inplace(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				0    ,				SCREAMING_SNAKE_CASE )


def  __a    (				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE ) ->       int:






    '''simple docstring'''
    if bit_position == 0 or end_index - begin_index <= 1:
        return

    bit_position -= 1

    __UpperCAmelCase			   =     begin_index
    __UpperCAmelCase			   =     end_index - 1
    while i <= j:
        __UpperCAmelCase			   =     False
        if not (list_of_ints[i] >> bit_position) & 1:
            # found zero at the beginning
            i += 1
            __UpperCAmelCase			   =     True
        if (list_of_ints[j] >> bit_position) & 1:
            # found one at the end
            j -= 1
            __UpperCAmelCase			   =     True

        if changed:
            continue

        __UpperCAmelCase   ,       __UpperCAmelCase			   =     list_of_ints[j], list_of_ints[i]
        j -= 1
        if j != i:
            i += 1

    _msd_radix_sort_inplace(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE )
    _msd_radix_sort_inplace(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE )


if __name__ == "__main__":
       import doctest

       doctest.testmod()




