code: def get_symbol(oshape=(3, 64, 64), ngf=128, code=None):
      """get symbol of dcgan generator"""
      assert oshape[-1] == 64, "Only support 64x64 image"
      assert oshape[-2] == 64, "Only support 64x64 image"
  
      code = mx.sym.Variable("data") if code is None else code
      net = mx.sym.FullyConnected(
          code,
          name="g1",
          num_hidden=ngf * 8 * 4 * 4,
          no_bias=True,
          flatten=False,
      )
      net = mx.sym.Activation(net, act_type="relu")
      # 4 x 4
      net = mx.sym.reshape(net, shape=(-1, ngf * 8, 4, 4))
      # 8 x 8
      net = deconv2d_bn_relu(
          net,
          ishape=(ngf * 8, 4, 4),
          oshape=(ngf * 4, 8, 8),
          kshape=(4, 4),
          prefix="g2",
      )
      # 16x16
      net = deconv2d_bn_relu(
          net,
          ishape=(ngf * 4, 8, 8),
          oshape=(ngf * 2, 16, 16),
          kshape=(4, 4),
          prefix="g3",
      )
      # 32x32
      net = deconv2d_bn_relu(
          net,
          ishape=(ngf * 2, 16, 16),
          oshape=(ngf, 32, 32),
          kshape=(4, 4),
          prefix="g4",
      )
      # 64x64
      net = deconv2d(
          net,
          ishape=(ngf, 32, 32),
          oshape=oshape[-3:],
          kshape=(4, 4),
          name="g5_deconv",
      )
      net = mx.sym.Activation(net, act_type="tanh")
      return net
  
imports: import mxnet
label_desc: Use image node_id 3 for calling a global function with example usage: get_symbol(oshape, ngf, code) and returns: net