code: def forward(self, x):
      B, C, N = x.shape
      x = x.permute(0, 2, 1).contiguous().view(-1, C)
      x = self.lin(x).view(B, N, -1).permute(0, 2, 1).contiguous()
      return x
  
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from basic import BiLinear
  from torch.autograd import Variable
label_desc: Use image node_id 2 for calling the Conv1d obj's underlying member method code with example usage: obj.forward(x) and returns: x