code: def deconv2d(data, ishape, oshape, kshape, name, stride=(2, 2)):
      """a deconv layer that enlarges the feature map"""
      target_shape = (oshape[-2], oshape[-1])
      pad_y = (kshape[0] - 1) // 2
      pad_x = (kshape[1] - 1) // 2
      adj_y = (target_shape[0] + 2 * pad_y - kshape[0]) % stride[0]
      adj_x = (target_shape[1] + 2 * pad_x - kshape[1]) % stride[1]
  
      net = mx.sym.Deconvolution(
          data,
          kernel=kshape,
          stride=stride,
          pad=(pad_y, pad_x),
          adj=(adj_y, adj_x),
          num_filter=oshape[0],
          no_bias=True,
          name=name,
      )
      return net
  
imports: import mxnet
label_desc: Use image node_id 1 for calling a global function with example usage: deconv2d(data, ishape, oshape, kshape, name, stride) and returns: net