



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


A__  :  Optional[int]								=					logging.get_logger(__name__)

A__  :  Tuple								=					{
    "vinvino02/glpn-kitti": "https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json",
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}



class 				__snake_case						(     __lowerCamelCase						):
							_a			      = '''glpn'''




							def __init__(       self     :       List[str]				,				A_     :       Optional[Any]=3				,				A_     :       Optional[int]=4				,				A_     :       Any=[2, 2, 2, 2]				,				A_     :       str=[8, 4, 2, 1]				,				A_     :       int=[3_2, 6_4, 1_6_0, 2_5_6]				,				A_     :       int=[7, 3, 3, 3]				,				A_     :       Optional[int]=[4, 2, 2, 2]				,				A_     :       int=[1, 2, 5, 8]				,				A_     :       int=[4, 4, 4, 4]				,				A_     :       Any="gelu"				,				A_     :       Dict=0.0				,				A_     :       str=0.0				,				A_     :       Optional[int]=0.02				,				A_     :       Optional[int]=0.1				,				A_     :       str=1e-6				,				A_     :       int=6_4				,				A_     :       str=1_0				,				A_     :       Optional[Any]=-1				,				**A_     :       List[str]				,				):
									super().__init__(**A_)

									lowerCAmelCase_			:     str									= num_channels
									lowerCAmelCase_			:     Any									= num_encoder_blocks
									lowerCAmelCase_			:     Optional[Any]									= depths
									lowerCAmelCase_			:     int									= sr_ratios
									lowerCAmelCase_			:     Dict									= hidden_sizes
									lowerCAmelCase_			:     Any									= patch_sizes
									lowerCAmelCase_			:     List[Any]									= strides
									lowerCAmelCase_			:     int									= mlp_ratios
									lowerCAmelCase_			:     Dict									= num_attention_heads
									lowerCAmelCase_			:     List[str]									= hidden_act
									lowerCAmelCase_			:     Optional[Any]									= hidden_dropout_prob
									lowerCAmelCase_			:     Dict									= attention_probs_dropout_prob
									lowerCAmelCase_			:     List[Any]									= initializer_range
									lowerCAmelCase_			:     int									= drop_path_rate
									lowerCAmelCase_			:     int									= layer_norm_eps
									lowerCAmelCase_			:     List[str]									= decoder_hidden_size
									lowerCAmelCase_			:     Dict									= max_depth
									lowerCAmelCase_			:     Optional[int]									= head_in_index












import math







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    bool:

  if 1 < number < 4:
    # 2 and 3 are primes
    return True
  elif number < 2 or number % 2 == 0 or number % 3 == 0:
    # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
    return False

  # All primes number are in format of 6k +/- 1
  for i in range(5					,					int(math.sqrt(SCREAMING_SNAKE_CASE__) + 1)					,					6):
    if number % i == 0 or number % (i + 2) == 0:
      return False
  return True







def 			A__							(    SCREAMING_SNAKE_CASE__ = 1_0001)   ->    int:

  try:
    __snake_case:						List[str]   =						int(SCREAMING_SNAKE_CASE__)
  except (TypeError, ValueError):
    raise TypeError("""Parameter nth must be int or castable to int.""") from None
  if nth <= 0:
    raise ValueError("""Parameter nth must be greater than or equal to one.""")
  __snake_case:						list[int]   =						[]
  __snake_case:						List[str]   =						2
  while len(SCREAMING_SNAKE_CASE__) < nth:
    if is_prime(SCREAMING_SNAKE_CASE__):
      primes.append(SCREAMING_SNAKE_CASE__)
      num += 1
    else:
      num += 1
  return primes[len(SCREAMING_SNAKE_CASE__) - 1]


if __name__ == "__main__":
      print(f'{solution() = }')






