
'''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 				UpperCAmelCase_			(		snake_case__   ):
 UpperCAmelCase_						      =  """graphormer"""
 UpperCAmelCase_						      =  ["""past_key_values"""]





 def __init__(      self	,    lowercase_ = 1	,    lowercase_ = 5_12 * 9	,    lowercase_ = 5_12 * 3	,    lowercase_ = 5_12	,    lowercase_ = 5_12	,    lowercase_ = 5_12	,    lowercase_ = 1_28	,    lowercase_ = 5	,    lowercase_ = 10_24	,    lowercase_ = "multi_hop"	,    lowercase_ = 5_12	,    lowercase_ = False	,    lowercase_ = 12	,    lowercase_ = 7_68	,    lowercase_ = 7_68	,    lowercase_ = 32	,    lowercase_ = 0.1	,    lowercase_ = 0.1	,    lowercase_ = 0.0	,    lowercase_ = False	,    lowercase_ = False	,    lowercase_ = False	,    lowercase_ = "gelu"	,    lowercase_ = None	,    lowercase_ = False	,    lowercase_ = 0	,    lowercase_ = False	,    lowercase_ = 0.0	,    lowercase_ = 8	,    lowercase_ = None	,    lowercase_ = None	,    lowercase_ = True	,    lowercase_ = True	,    lowercase_=0	,    lowercase_=1	,    lowercase_=2	,    **lowercase_	,    ):
     snake_case_	:      Dict            =  num_classes
     snake_case_	:      int            =  num_atoms
     snake_case_	:      str            =  num_in_degree
     snake_case_	:      List[Any]            =  num_out_degree
     snake_case_	:      List[str]            =  num_edges
     snake_case_	:      Tuple            =  num_spatial
     snake_case_	:      List[Any]            =  num_edge_dis
     snake_case_	:      Dict            =  edge_type
     snake_case_	:      Union[str, Any]            =  multi_hop_max_dist
     snake_case_	:      Optional[int]            =  spatial_pos_max
     snake_case_	:      Tuple            =  max_nodes
     snake_case_	:      Union[str, Any]            =  num_hidden_layers
     snake_case_	:      Optional[int]            =  embedding_dim
     snake_case_	:      str            =  embedding_dim
     snake_case_	:      int            =  ffn_embedding_dim
     snake_case_	:      Optional[int]            =  num_attention_heads
     snake_case_	:      List[str]            =  dropout
     snake_case_	:      Optional[int]            =  attention_dropout
     snake_case_	:      Any            =  layerdrop
     snake_case_	:      Union[str, Any]            =  encoder_normalize_before
     snake_case_	:      Optional[Any]            =  pre_layernorm
     snake_case_	:      Any            =  apply_graphormer_init
     snake_case_	:      Union[str, Any]            =  activation_fn
     snake_case_	:      Union[str, Any]            =  embed_scale
     snake_case_	:      List[Any]            =  freeze_embeddings
     snake_case_	:      List[str]            =  num_trans_layers_to_freeze
     snake_case_	:      Optional[Any]            =  share_input_output_embed
     snake_case_	:      Optional[int]            =  traceable
     snake_case_	:      Optional[Any]            =  q_noise
     snake_case_	:      Any            =  qn_block_size

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

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






'''simple docstring'''
from math import exp

def   UpperCamelCase_       (		__SCREAMING_SNAKE_CASE    ):
    """simple docstring"""






    return 8 * x - 2 * exp(-x    )

def   UpperCamelCase_       (		__SCREAMING_SNAKE_CASE,						__SCREAMING_SNAKE_CASE,						__SCREAMING_SNAKE_CASE    ):
    """simple docstring"""






    snake_case_	:      Optional[Any]            =  lower_bound
    snake_case_	:      int            =  upper_bound
    for _ in range(0,						__SCREAMING_SNAKE_CASE    ):
        snake_case_     ,	snake_case_	:      List[str]            =  xa, xa - (f(__SCREAMING_SNAKE_CASE    ) * (xa - xa)) / (f(__SCREAMING_SNAKE_CASE    ) - f(__SCREAMING_SNAKE_CASE    ))
    return xa


if __name__ == "__main__":
  print(f"""Example: {secant_method(1, 3, 2)}""")




