code: def forward(self, x):
      if self.num_branches == 1:
          return [self.layers[0](x[0])]
      if self.module_type == "LITE":
          out = self.layers(x)
      elif self.module_type == "NAIVE":
          for i in range(self.num_branches):
              x[i] = self.layers[i](x[i])
          out = x
      if self.with_fuse:
          out_fuse = []
          for i in range(len(self.fuse_layers)):
              y = out[0] if i == 0 else self.fuse_layers[i][0](out[0])
              for j in range(self.num_branches):
                  if j == 0:
                      y += y
                  elif i == j:
                      y += out[j]
                  else:
                      y += self.fuse_layers[i][j](out[j])
                  if i == 0:
                      out[i] = y
              out_fuse.append(self.relu(y))
          out = out_fuse
      elif not self.multiscale_output:
          out = [out[0]]
      return out
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from numbers import Integral
  from paddle import ParamAttr
  from paddle.regularizer import L2Decay
  from paddle.nn.initializer import Normal, Constant
  from ppdet.core.workspace import register
  from ppdet.modeling.shape_spec import ShapeSpec
  from ppdet.modeling.ops import channel_shuffle
  from ..None import layers
label_desc: Use image node_id 5 for calling the LiteHRNetModule obj's underlying member method code with example usage: obj.forward(x) and returns: out, list