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


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

__SCREAMING_SNAKE_CASE     :				Any             =       {
    # pcqm4mv1 now deprecated
    'graphormer-base': 'https://huggingface.co/clefourrier/graphormer-base-pcqm4mv2/resolve/main/config.json',
    # See all Graphormer models at https://huggingface.co/models?filter=graphormer
}


class 						__magic_name__				(  lowerCAmelCase__      ):
		_lowerCAmelCase						=		'''graphormer'''
		_lowerCAmelCase						=		['''past_key_values''']





		def __init__(							self      :		List[str]  ,					lowerCamelCase__      :		Optional[Any] = 1  ,					lowerCamelCase__      :		Union[str, Any] = 5_1_2 * 9  ,					lowerCamelCase__      :		List[str] = 5_1_2 * 3  ,					lowerCamelCase__      :		List[str] = 5_1_2  ,					lowerCamelCase__      :		Tuple = 5_1_2  ,					lowerCamelCase__      :		Any = 5_1_2  ,					lowerCamelCase__      :		Optional[int] = 1_2_8  ,					lowerCamelCase__      :		int = 5  ,					lowerCamelCase__      :		Optional[int] = 1_0_2_4  ,					lowerCamelCase__      :		Any = "multi_hop"  ,					lowerCamelCase__      :		str = 5_1_2  ,					lowerCamelCase__      :		List[Any] = False  ,					lowerCamelCase__      :		Tuple = 1_2  ,					lowerCamelCase__      :		Union[str, Any] = 7_6_8  ,					lowerCamelCase__      :		int = 7_6_8  ,					lowerCamelCase__      :		List[Any] = 3_2  ,					lowerCamelCase__      :		Any = 0.1  ,					lowerCamelCase__      :		List[Any] = 0.1  ,					lowerCamelCase__      :		Any = 0.0  ,					lowerCamelCase__      :		Union[str, Any] = False  ,					lowerCamelCase__      :		List[Any] = False  ,					lowerCamelCase__      :		List[Any] = False  ,					lowerCamelCase__      :		int = "gelu"  ,					lowerCamelCase__      :		Union[str, Any] = None  ,					lowerCamelCase__      :		Union[str, Any] = False  ,					lowerCamelCase__      :		int = 0  ,					lowerCamelCase__      :		Optional[Any] = False  ,					lowerCamelCase__      :		Union[str, Any] = 0.0  ,					lowerCamelCase__      :		Any = 8  ,					lowerCamelCase__      :		List[Any] = None  ,					lowerCamelCase__      :		Dict = None  ,					lowerCamelCase__      :		str = True  ,					lowerCamelCase__      :		Dict = True  ,					lowerCamelCase__      :		str=0  ,					lowerCamelCase__      :		Tuple=1  ,					lowerCamelCase__      :		Optional[Any]=2  ,					**lowerCamelCase__      :		str  ,					):
							lowerCAmelCase						:   Optional[int]							=       num_classes
							lowerCAmelCase						:   Optional[int]							=       num_atoms
							lowerCAmelCase						:   Dict							=       num_in_degree
							lowerCAmelCase						:   List[str]							=       num_out_degree
							lowerCAmelCase						:   List[Any]							=       num_edges
							lowerCAmelCase						:   List[str]							=       num_spatial
							lowerCAmelCase						:   Union[str, Any]							=       num_edge_dis
							lowerCAmelCase						:   str							=       edge_type
							lowerCAmelCase						:   Optional[int]							=       multi_hop_max_dist
							lowerCAmelCase						:   List[str]							=       spatial_pos_max
							lowerCAmelCase						:   Tuple							=       max_nodes
							lowerCAmelCase						:   Any							=       num_hidden_layers
							lowerCAmelCase						:   str							=       embedding_dim
							lowerCAmelCase						:   str							=       embedding_dim
							lowerCAmelCase						:   Tuple							=       ffn_embedding_dim
							lowerCAmelCase						:   List[Any]							=       num_attention_heads
							lowerCAmelCase						:   Tuple							=       dropout
							lowerCAmelCase						:   Any							=       attention_dropout
							lowerCAmelCase						:   List[Any]							=       layerdrop
							lowerCAmelCase						:   Union[str, Any]							=       encoder_normalize_before
							lowerCAmelCase						:   Tuple							=       pre_layernorm
							lowerCAmelCase						:   List[str]							=       apply_graphormer_init
							lowerCAmelCase						:   List[Any]							=       activation_fn
							lowerCAmelCase						:   Union[str, Any]							=       embed_scale
							lowerCAmelCase						:   Optional[Any]							=       freeze_embeddings
							lowerCAmelCase						:   Dict							=       num_trans_layers_to_freeze
							lowerCAmelCase						:   Dict							=       share_input_output_embed
							lowerCAmelCase						:   Optional[Any]							=       traceable
							lowerCAmelCase						:   Union[str, Any]							=       q_noise
							lowerCAmelCase						:   List[Any]							=       qn_block_size

							# These parameters are here for future extensions
							# atm, the model only supports self attention
							lowerCAmelCase						:   Dict							=       kdim
							lowerCAmelCase						:   Tuple							=       vdim
							lowerCAmelCase						:   int							=       self_attention
							lowerCAmelCase						:   Optional[Any]							=       bias

							super().__init__(
							    pad_token_id=__lowerCAmelCase  ,					bos_token_id=__lowerCAmelCase  ,					eos_token_id=__lowerCAmelCase  ,					**__lowerCAmelCase  ,					)


from math import floor, sqrt
def       UpperCAmelCase__							(    __magic_name__  :       int					):


					'''simple docstring'''

					lowerCAmelCase						:   int							=       0.0
					lowerCAmelCase						:   int							=       1.0
					lowerCAmelCase						:   Any							=       int(sqrt(__magic_name__					)					)
					lowerCAmelCase						:   Optional[int]							=       root
					lowerCAmelCase						:   Dict							=       0
					while integer_part != 2 * root:
										lowerCAmelCase						:   str							=       denominator * integer_part - numerator
										lowerCAmelCase						:   Dict							=       (n - numerator**2) / denominator
										lowerCAmelCase						:   str							=       int((root + numerator) / denominator					)
										period += 1
					return period
def       UpperCAmelCase__							(    __magic_name__  :       int = 1_00_00					):


					'''simple docstring'''

					lowerCAmelCase						:   List[str]							=       0
					for i in range(2							,					n + 1					):
										lowerCAmelCase						:   Any							=       sqrt(__magic_name__					)
										if sr - floor(__magic_name__					) != 0 and continuous_fraction_period(__magic_name__					) % 2 == 1:
															count_odd_periods += 1
					return count_odd_periods


if __name__ == "__main__":
		print(f"""{solution(int(input().strip()))}""")
