code: 
  
  """simple docstring"""
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  _A						=     logging.get_logger(__name__)
  
  _A						=     {
      # 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 			lowerCamelCase  (					lowerCAmelCase__      ):
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    SCREAMING_SNAKE_CASE							=     'graphormer'
    SCREAMING_SNAKE_CASE							=     ['past_key_values']
  
  
  
    def __init__(self       ,					_lowerCamelCase = 1       ,					_lowerCamelCase = 512 * 9       ,					_lowerCamelCase = 512 * 3       ,					_lowerCamelCase = 512       ,					_lowerCamelCase = 512       ,					_lowerCamelCase = 512       ,					_lowerCamelCase = 128       ,					_lowerCamelCase = 5       ,					_lowerCamelCase = 1024       ,					_lowerCamelCase = "multi_hop"       ,					_lowerCamelCase = 512       ,					_lowerCamelCase = False       ,					_lowerCamelCase = 12       ,					_lowerCamelCase = 768       ,					_lowerCamelCase = 768       ,					_lowerCamelCase = 32       ,					_lowerCamelCase = 0.1       ,					_lowerCamelCase = 0.1       ,					_lowerCamelCase = 0.0       ,					_lowerCamelCase = False       ,					_lowerCamelCase = False       ,					_lowerCamelCase = False       ,					_lowerCamelCase = "gelu"       ,					_lowerCamelCase = None       ,					_lowerCamelCase = False       ,					_lowerCamelCase = 0       ,					_lowerCamelCase = False       ,					_lowerCamelCase = 0.0       ,					_lowerCamelCase = 8       ,					_lowerCamelCase = None       ,					_lowerCamelCase = None       ,					_lowerCamelCase = True       ,					_lowerCamelCase = True       ,					_lowerCamelCase=0       ,					_lowerCamelCase=1       ,					_lowerCamelCase=2       ,					**_lowerCamelCase       ,					):
  
  
          """simple docstring"""
  
          UpperCAmelCase__ :       Any						=						num_classes
          UpperCAmelCase__ :       Union[str, Any]						=						num_atoms
          UpperCAmelCase__ :       Tuple						=						num_in_degree
          UpperCAmelCase__ :       List[Any]						=						num_out_degree
          UpperCAmelCase__ :       Any						=						num_edges
          UpperCAmelCase__ :       List[Any]						=						num_spatial
          UpperCAmelCase__ :       str						=						num_edge_dis
          UpperCAmelCase__ :       Any						=						edge_type
          UpperCAmelCase__ :       int						=						multi_hop_max_dist
          UpperCAmelCase__ :       Union[str, Any]						=						spatial_pos_max
          UpperCAmelCase__ :       Dict						=						max_nodes
          UpperCAmelCase__ :       Optional[int]						=						num_hidden_layers
          UpperCAmelCase__ :       Tuple						=						embedding_dim
          UpperCAmelCase__ :       int						=						embedding_dim
          UpperCAmelCase__ :       Optional[int]						=						ffn_embedding_dim
          UpperCAmelCase__ :       List[str]						=						num_attention_heads
          UpperCAmelCase__ :       Union[str, Any]						=						dropout
          UpperCAmelCase__ :       str						=						attention_dropout
          UpperCAmelCase__ :       str						=						layerdrop
          UpperCAmelCase__ :       Tuple						=						encoder_normalize_before
          UpperCAmelCase__ :       Optional[int]						=						pre_layernorm
          UpperCAmelCase__ :       Dict						=						apply_graphormer_init
          UpperCAmelCase__ :       Optional[int]						=						activation_fn
          UpperCAmelCase__ :       str						=						embed_scale
          UpperCAmelCase__ :       List[Any]						=						freeze_embeddings
          UpperCAmelCase__ :       List[str]						=						num_trans_layers_to_freeze
          UpperCAmelCase__ :       List[Any]						=						share_input_output_embed
          UpperCAmelCase__ :       Optional[Any]						=						traceable
          UpperCAmelCase__ :       Dict						=						q_noise
          UpperCAmelCase__ :       str						=						qn_block_size
  
          # These parameters are here for future extensions
          # atm, the model only supports self attention
          UpperCAmelCase__ :       Any						=						kdim
          UpperCAmelCase__ :       int						=						vdim
          UpperCAmelCase__ :       Tuple						=						self_attention
          UpperCAmelCase__ :       int						=						bias
  
          super().__init__(
              pad_token_id=_lowerCamelCase       ,					bos_token_id=_lowerCamelCase       ,					eos_token_id=_lowerCamelCase       ,					**_lowerCamelCase       ,					)
  
  
style_context: 
  
  """simple docstring"""
  from __future__ import annotations
  
  
  
  
  def 				a__	(	lowerCAmelCase						)  ->   set[int]:
        UpperCAmelCase__ :       List[Any]						=						{1}
        UpperCAmelCase__ :       Optional[int]						=						[1]
        for _ in range(2 ,  depth + 1						):
              UpperCAmelCase__ :       Tuple						=						[*previous_coefficients, 0]
              UpperCAmelCase__ :       List[str]						=						[0, *previous_coefficients]
              UpperCAmelCase__ :       Dict						=						[]
              for x, y in zip(lowerCAmelCase ,  lowerCAmelCase						):
                    coefficients.add(x + y						)
                    previous_coefficients.append(x + y						)
        return coefficients
  
  
  
  
  def 				a__	(	lowerCAmelCase						)  ->   set[int]:
        UpperCAmelCase__ :       List[str]						=						set()
        for number in unique_coefficients:
              UpperCAmelCase__ :       int						=						2
              UpperCAmelCase__ :       List[Any]						=						number
              while divisor**2 <= copy_number:
                    UpperCAmelCase__ :       Tuple						=						0
                    while copy_number % divisor == 0:
                          copy_number //= divisor
                          multiplicity += 1
                    if multiplicity >= 2:
                          non_squarefrees.add(lowerCAmelCase						)
                          break
                    divisor += 1
  
        return unique_coefficients.difference(lowerCAmelCase						)
  
  
  
  
  def 				a__	(	lowerCAmelCase = 51						)  ->   int:
        UpperCAmelCase__ :       Any						=						get_pascal_triangle_unique_coefficients(lowerCAmelCase						)
        UpperCAmelCase__ :       Dict						=						get_squarefrees(lowerCAmelCase						)
        return sum(lowerCAmelCase						)
  
  
  if __name__ == "__main__":
      print(f'''{solution() = }''')
  
  