






'''simple docstring'''







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


UpperCamelCase    :      Union[str, Any]  			=		logging.get_logger(__name__)

UpperCamelCase    :      str  			=		{
    'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json',
    # See all CANINE models at https://huggingface.co/models?filter=canine
}




class 		UpperCamelCase__    (a			):




		'''simple docstring'''





		_UpperCamelCase				  =					'canine'






		def __init__(      self   ,_lowerCAmelCase=7_68   ,_lowerCAmelCase=12   ,_lowerCAmelCase=12   ,_lowerCAmelCase=30_72   ,_lowerCAmelCase="gelu"   ,_lowerCAmelCase=0.1   ,_lowerCAmelCase=0.1   ,_lowerCAmelCase=1_63_84   ,_lowerCAmelCase=16   ,_lowerCAmelCase=0.02   ,_lowerCAmelCase=1E-12   ,_lowerCAmelCase=0   ,_lowerCAmelCase=0xe0_00   ,_lowerCAmelCase=0xe0_01   ,_lowerCAmelCase=4   ,_lowerCAmelCase=4   ,_lowerCAmelCase=8   ,_lowerCAmelCase=1_63_84   ,_lowerCAmelCase=1_28   ,**_lowerCAmelCase   ,):
								super().__init__(pad_token_id=_lowerCAmelCase   ,bos_token_id=_lowerCAmelCase   ,eos_token_id=_lowerCAmelCase   ,**_lowerCAmelCase       )

								lowerCamelCase__         =  max_position_embeddings
								lowerCamelCase__         =  hidden_size
								lowerCamelCase__         =  num_hidden_layers
								lowerCamelCase__         =  num_attention_heads
								lowerCamelCase__         =  intermediate_size
								lowerCamelCase__         =  hidden_act
								lowerCamelCase__         =  hidden_dropout_prob
								lowerCamelCase__         =  attention_probs_dropout_prob
								lowerCamelCase__         =  initializer_range
								lowerCamelCase__         =  type_vocab_size
								lowerCamelCase__         =  layer_norm_eps

								# Character config:
								lowerCamelCase__         =  downsampling_rate
								lowerCamelCase__         =  upsampling_kernel_size
								lowerCamelCase__         =  num_hash_functions
								lowerCamelCase__         =  num_hash_buckets
								lowerCamelCase__         =  local_transformer_stride









'''simple docstring'''







from __future__ import annotations

import math
def 						A__			(				__lowerCAmelCase		:			int						):

						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(__lowerCAmelCase						) + 1						)   ,    6						):
												if number % i == 0 or number % (i + 2) == 0:
																		return False
						return True


UpperCamelCase    :      str  			=		[num for num in range(3, 10_00_01, 2) if not is_prime(num)]
def 						A__			(				__lowerCAmelCase		:			int						):
						if not isinstance(__lowerCAmelCase   ,    __lowerCAmelCase						):
												raise ValueError("""n must be an integer"""						)
						if n <= 0:
												raise ValueError("""n must be >= 0"""						)

						lowerCamelCase__         =  []
						for num in range(len(__lowerCAmelCase						)						):
												lowerCamelCase__         =  0
												while 2 * i * i <= odd_composites[num]:
																		lowerCamelCase__         =  odd_composites[num] - 2 * i * i
																		if is_prime(__lowerCAmelCase						):
																								break
																		i += 1
												else:
																		list_nums.append(odd_composites[num]						)
																		if len(__lowerCAmelCase						) == n:
																								return list_nums

						return []
def 						A__			(				):
						return compute_nums(1						)[0]


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

