code: def __init__(self, in_features, out_features, bias=True):
      super().__init__()
      self.linear_c = nn.Linear(
          in_features // 2, out_features // 2, bias
      )
      self.linear_p = nn.Linear(
          in_features // 2, out_features // 2, bias
      )
  
imports: import copy
  import math
  import torch
  import torch.nn
  import torch.nn.functional
  from stanza.models.constituency.positional_encoding import ConcatSinusoidalEncoding
label_desc: Use image node_id 1 to create a new PartitionedLinear object from inherited base classes: nn with example: obj = PartitionedLinear(in_features, out_features, bias)