





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


_lowercase		:  List[str]			       =logging.get_logger(__name__)

_lowercase		:  str			       ={
    """CarlCochet/trajectory-transformer-halfcheetah-medium-v2""": (
        """https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json"""
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}






class 						UpperCamelCase_  (  snake_case__							):
					_a      :						int						    =					'trajectory_transformer'
					_a      :						int						    =					['past_key_values']
					_a      :						Any						    =					{
					    'hidden_size': 'n_embd',
					    'num_attention_heads': 'n_head',
					    'num_hidden_layers': 'n_layer',
					}



					def __init__(		self     :     str       ,      lowerCamelCase     :     Optional[Any]=1_00       ,      lowerCamelCase     :     Tuple=5       ,      lowerCamelCase     :     Optional[Any]=1       ,      lowerCamelCase     :     Union[str, Any]=1       ,      lowerCamelCase     :     Optional[Any]=2_49       ,      lowerCamelCase     :     Tuple=6       ,      lowerCamelCase     :     List[str]=17       ,      lowerCamelCase     :     str=25       ,      lowerCamelCase     :     Any=4       ,      lowerCamelCase     :     Optional[Any]=4       ,      lowerCamelCase     :     Tuple=1_28       ,      lowerCamelCase     :     List[Any]=0.1       ,      lowerCamelCase     :     Optional[int]=0.1       ,      lowerCamelCase     :     Tuple=0.1       ,      lowerCamelCase     :     List[Any]=0.0_006       ,      lowerCamelCase     :     Any=5_12       ,      lowerCamelCase     :     str=0.02       ,      lowerCamelCase     :     Dict=1E-12       ,      lowerCamelCase     :     Tuple=1       ,      lowerCamelCase     :     List[Any]=True       ,      lowerCamelCase     :     str=1       ,      lowerCamelCase     :     Optional[Any]=5_02_56       ,      lowerCamelCase     :     Optional[Any]=5_02_56       ,      **lowerCamelCase     :     Union[str, Any]       ,      ):
							lowerCamelCase_	:     int 						=      vocab_size
							lowerCamelCase_	:     Optional[Any] 						=      action_weight
							lowerCamelCase_	:     Dict 						=      reward_weight
							lowerCamelCase_	:     Optional[int] 						=      value_weight
							lowerCamelCase_	:     Tuple 						=      max_position_embeddings
							lowerCamelCase_	:     int 						=      block_size
							lowerCamelCase_	:     Optional[int] 						=      action_dim
							lowerCamelCase_	:     List[str] 						=      observation_dim
							lowerCamelCase_	:     Optional[int] 						=      transition_dim
							lowerCamelCase_	:     int 						=      learning_rate
							lowerCamelCase_	:     Dict 						=      n_layer
							lowerCamelCase_	:     Any 						=      n_head
							lowerCamelCase_	:     Any 						=      n_embd
							lowerCamelCase_	:     Any 						=      embd_pdrop
							lowerCamelCase_	:     List[Any] 						=      attn_pdrop
							lowerCamelCase_	:     Union[str, Any] 						=      resid_pdrop
							lowerCamelCase_	:     List[Any] 						=      initializer_range
							lowerCamelCase_	:     Optional[Any] 						=      layer_norm_eps
							lowerCamelCase_	:     Optional[Any] 						=      kaiming_initializer_range
							lowerCamelCase_	:     Optional[Any] 						=      use_cache
							super().__init__(pad_token_id=lowerCamelCase       ,      bos_token_id=lowerCamelCase       ,      eos_token_id=lowerCamelCase       ,      **lowerCamelCase						)







from __future__ import annotations

import math


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):

		if num <= 0:
				lowerCamelCase_	:     Optional[int] 						=      F"{num}: Invalid input, please enter a positive integer."
				raise ValueError(lowerCAmelCase__						)

		lowerCamelCase_	:     str 						=      [True] * (num + 1)
		lowerCamelCase_	:     List[str] 						=      []
		lowerCamelCase_	:     Optional[int] 						=      2
		lowerCamelCase_	:     List[str] 						=      int(math.sqrt(lowerCAmelCase__						)						)

		while start <= end:
				# If start is a prime
				if sieve[start] is True:
						prime.append(lowerCAmelCase__						)

						# Set multiples of start be False
						for i in range(start * start							,num + 1							,lowerCAmelCase__						):
								if sieve[i] is True:
										lowerCamelCase_	:     Tuple 						=      False

				start += 1

		for j in range(end + 1							,num + 1						):
				if sieve[j] is True:
						prime.append(lowerCAmelCase__						)

		return prime


if __name__ == "__main__":
		print(prime_sieve(int(input("""Enter a positive integer: """).strip())))
