
"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

from packaging import version

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


_a		       =							logging.get_logger(__name__)

_a		       =							{
    'hustvl/yolos-small': 'https://huggingface.co/hustvl/yolos-small/resolve/main/config.json',
    # See all YOLOS models at https://huggingface.co/models?filter=yolos
}


class A_	(lowercase__      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						Optional[Any]       =		"""yolos"""







  def __init__(		self				,   lowercase_=768				,   lowercase_=12				,   lowercase_=12				,   lowercase_=3072				,   lowercase_="gelu"				,   lowercase_=0.0				,   lowercase_=0.0				,   lowercase_=0.02				,   lowercase_=1E-1_2				,   lowercase_=[512, 864]				,   lowercase_=16				,   lowercase_=3				,   lowercase_=True				,   lowercase_=100				,   lowercase_=True				,   lowercase_=False				,   lowercase_=1				,   lowercase_=5				,   lowercase_=2				,   lowercase_=5				,   lowercase_=2				,   lowercase_=0.1				,   **lowercase_				,   ):

     """simple docstring"""
     super().__init__(**lowercase_  )

     UpperCAmelCase_					:					List[Any]			     =    hidden_size
     UpperCAmelCase_					:					int			     =    num_hidden_layers
     UpperCAmelCase_					:					Union[str, Any]			     =    num_attention_heads
     UpperCAmelCase_					:					List[str]			     =    intermediate_size
     UpperCAmelCase_					:					List[str]			     =    hidden_act
     UpperCAmelCase_					:					Any			     =    hidden_dropout_prob
     UpperCAmelCase_					:					Union[str, Any]			     =    attention_probs_dropout_prob
     UpperCAmelCase_					:					Union[str, Any]			     =    initializer_range
     UpperCAmelCase_					:					List[str]			     =    layer_norm_eps
     UpperCAmelCase_					:					Tuple			     =    image_size
     UpperCAmelCase_					:					List[str]			     =    patch_size
     UpperCAmelCase_					:					List[str]			     =    num_channels
     UpperCAmelCase_					:					str			     =    qkv_bias
     UpperCAmelCase_					:					Any			     =    num_detection_tokens
     UpperCAmelCase_					:					Optional[int]			     =    use_mid_position_embeddings
     UpperCAmelCase_					:					Union[str, Any]			     =    auxiliary_loss
     # Hungarian matcher
     UpperCAmelCase_					:					int			     =    class_cost
     UpperCAmelCase_					:					Dict			     =    bbox_cost
     UpperCAmelCase_					:					int			     =    giou_cost
     # Loss coefficients
     UpperCAmelCase_					:					Dict			     =    bbox_loss_coefficient
     UpperCAmelCase_					:					List[str]			     =    giou_loss_coefficient
     UpperCAmelCase_					:					int			     =    eos_coefficient




class A_	(lowercase__      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						Union[str, Any]       =		version.parse("""1.11"""      )







  @property
  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return OrderedDict(
         [
             ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
         ]  )







  @property
  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return 1E-4







  @property
  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return 12




"""simple docstring"""





def 	__a     (		__lowerCamelCase  ):
   UpperCAmelCase_					:					List[str]			     =    int(__lowerCamelCase  )
   if n_element < 1:
      UpperCAmelCase_					:					List[Any]			     =    ValueError("a should be a positive number"  )
      raise my_error

   UpperCAmelCase_					:					List[Any]			     =    [1]
   UpperCAmelCase_     ,   UpperCAmelCase_     ,   UpperCAmelCase_					:					Optional[int]			     =    (0, 0, 0)
   UpperCAmelCase_					:					Dict			     =    1
   while index < n_element:
      while hamming_list[i] * 2 <= hamming_list[-1]:
         i += 1
      while hamming_list[j] * 3 <= hamming_list[-1]:
         j += 1
      while hamming_list[k] * 5 <= hamming_list[-1]:
         k += 1
      hamming_list.append(
          min(hamming_list[i] * 2,		hamming_list[j] * 3,		hamming_list[k] * 5  )  )
      index += 1
   return hamming_list


if __name__ == "__main__":
    _a		       =							input('Enter the last number (nth term) of the Hamming Number Series: ')
    print('Formula of Hamming Number Series => 2^i * 3^j * 5^k')
    _a		       =							hamming(int(n))
    print('-----------------------------------------------------')
    print(f"""The list with nth numbers is: {hamming_numbers}""")
    print('-----------------------------------------------------')


