code: def forward(self, x):
      if isinstance(x, tuple):
          x_c, x_p = x
      else:
          x_c, x_p = torch.chunk(x, 2, dim=-1)
  
      out_c = self.linear_c(x_c)
      out_p = self.linear_p(x_p)
      return out_c, out_p
  
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 2 for calling the PartitionedLinear obj's underlying member method code with example usage: obj.forward(x) and returns: out_c,  out_p