code: def forward(self, net: torch.Tensor) -> torch.Tensor:
      if len(net.shape) > 2:
          net = net.contiguous().view(len(net), -1)
      net = self.planes_activation(self.to_planes(net))
      net = self.routes_activation(self.to_routes(net))
      net = self.to_leaves(net)
      return net
  
imports: import torch
  import numpy
  import torch.nn.functional
  from typing import Dict
  from typing import List
  from typing import Iterator
  from typing import Optional
  from cftool.array import to_numpy
  from cftool.array import to_torch
  from .base import MLModel
  from ...schema import MLEncoderSettings
  from ...schema import MLGlobalEncoderSettings
  from ...modules.blocks import Linear
  from ...modules.blocks import Activation
label_desc: Use image node_id 8 for calling the NDT obj's underlying member method code with example usage: obj.forward(net) and returns: net