


"""simple docstring"""







from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowercase    					=      logging.get_logger(__name__)

__lowercase    					=      {
    """MIT/ast-finetuned-audioset-10-10-0.4593""": (
        """https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/config.json"""
    ),
}






class 						_A  (  _a  ):







    """simple docstring"""




    UpperCAmelCase       :							List[str]	=       """audio-spectrogram-transformer"""






    def __init__(					self				:    List[Any]				, __UpperCAmelCase				:    str=768				, __UpperCAmelCase				:    Dict=12				, __UpperCAmelCase				:    Optional[int]=12				, __UpperCAmelCase				:    Any=3072				, __UpperCAmelCase				:    List[Any]="gelu"				, __UpperCAmelCase				:    Tuple=0.0				, __UpperCAmelCase				:    Any=0.0				, __UpperCAmelCase				:    List[str]=0.02				, __UpperCAmelCase				:    int=1e-12				, __UpperCAmelCase				:    str=16				, __UpperCAmelCase				:    Optional[Any]=True				, __UpperCAmelCase				:    Any=10				, __UpperCAmelCase				:    List[Any]=10				, __UpperCAmelCase				:    List[str]=1024				, __UpperCAmelCase				:    str=128				, **__UpperCAmelCase				:    Dict				, ):
      super().__init__(**__UpperCAmelCase)

      a						:		Any      							=			hidden_size
      a						:		Tuple      							=			num_hidden_layers
      a						:		Any      							=			num_attention_heads
      a						:		Optional[Any]      							=			intermediate_size
      a						:		str      							=			hidden_act
      a						:		Tuple      							=			hidden_dropout_prob
      a						:		Optional[int]      							=			attention_probs_dropout_prob
      a						:		Optional[int]      							=			initializer_range
      a						:		Any      							=			layer_norm_eps
      a						:		Optional[int]      							=			patch_size
      a						:		Optional[Any]      							=			qkv_bias
      a						:		Optional[Any]      							=			frequency_stride
      a						:		Optional[Any]      							=			time_stride
      a						:		Tuple      							=			max_length
      a						:		Optional[Any]      							=			num_mel_bins









from __future__ import annotations

from collections.abc import Generator


def   __SCREAMING_SNAKE_CASE					():
						snake_case_   =	{}
						snake_case_   =	2
						while True:
												snake_case_   =	factor_map.pop(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       )
												if factor:
																		snake_case_   =	factor + prime
																		while x in factor_map:
																								x += factor
																		snake_case_   =	factor
												else:
																		snake_case_   =	prime
																		yield prime
												prime += 1


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__ = 1E10       ):
						snake_case_   =	sieve()

						snake_case_   =	1
						while True:
												snake_case_   =	next(SCREAMING_SNAKE_CASE__       )
												if (2 * prime * n) > limit:
																		return n
												# Ignore the next prime as the reminder will be 2.
												next(SCREAMING_SNAKE_CASE__       )
												n += 2


if __name__ == "__main__":
					print(solution())