

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_					  =   logging.get_logger(__name__)

lowerCamelCase_					  =   {
    '''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 					__lowerCamelCase							(      __lowercase      ):
      lowerCamelCase_      : Dict  			=   'deberta'







      def __init__(	self				,    lowerCamelCase=50265				,    lowerCamelCase=768				,    lowerCamelCase=12				,    lowerCamelCase=12				,    lowerCamelCase=3072				,    lowerCamelCase="gelu"				,    lowerCamelCase=0.1				,    lowerCamelCase=0.1				,    lowerCamelCase=512				,    lowerCamelCase=0				,    lowerCamelCase=0.02				,    lowerCamelCase=1e-7				,    lowerCamelCase=False				,    lowerCamelCase=-1				,    lowerCamelCase=0				,    lowerCamelCase=True				,    lowerCamelCase=None				,    lowerCamelCase=0				,    lowerCamelCase="gelu"				,    **lowerCamelCase				,    )		->			str:
        super().__init__(**__A  )

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

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

        snake_case_					= pos_att_type
        snake_case_					= vocab_size
        snake_case_					= layer_norm_eps

        snake_case_					= kwargs.get("""pooler_hidden_size"""				,    __A  )
        snake_case_					= pooler_dropout
        snake_case_					= pooler_hidden_act







class 					__lowerCamelCase							(      __lowercase      ):







      @property
      def       lowerCAmelCase_       (	self  )		->			Mapping[str, Mapping[int, str]]:
        if self.task == "multiple-choice":
          snake_case_					= {0: """batch""", 1: """choice""", 2: """sequence"""}
        else:
          snake_case_					= {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				,    lowerCamelCase				,    lowerCamelCase = -1				,    lowerCamelCase = -1				,    lowerCamelCase = -1				,    lowerCamelCase = False				,    lowerCamelCase = None				,    lowerCamelCase = 3				,    lowerCamelCase = 40				,    lowerCamelCase = 40				,    lowerCamelCase = None				,    )		->			Mapping[str, Any]:
        snake_case_					= super().generate_dummy_inputs(preprocessor=__A				,    framework=__A  )
        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'''

from itertools import compress, repeat
from math import ceil, sqrt



def 				UpperCamelCase__      (      a__   ):


						'''simple docstring'''






						if num <= 2:
												return []
						if num == 3:
												return [2]

						# Odd sieve for numbers in range [3, num - 1]
						_lowerCAmelCase					    =bytearray(B'\x01'   ) * ((num >> 1) - 1)

						for i in range(3      ,   int(sqrt(a__   )   ) + 1      ,   2   ):
												if sieve[(i >> 1) - 1]:
																		_lowerCAmelCase					    =i**2
																		_lowerCAmelCase					    =repeat(
																		    0      ,   ceil((num - i_squared) / (i << 1)   )   )

						return [2] + list(compress(range(3      ,   a__      ,   2   )      ,   a__   )   )


if __name__ == "__main__":
							import doctest

							doctest.testmod()





