code: def __init__(self, in_channel, out_channel, kernel_size, padding=0):
      super().__init__()
  
      self.weight = self.params.get(
          "weight",
          shape=(in_channel, out_channel, kernel_size, kernel_size),
          grad_req="write",
          init=mx.init.Normal(sigma=1),
      )
      self.bias = self.params.get(
          "bias",
          shape=(out_channel),
          grad_req="write",
          init=mx.init.Zero(),
      )
      fan_in = in_channel * kernel_size * kernel_size
      self.multiplier = sqrt(2 / (fan_in + 1e-8))
      self.pad = (padding, padding)
  
imports: import numpy
  from math import sqrt
  import mxnet
  import mxnet.ndarray
  import mxnet.gluon.nn
  from numpy import prod
label_desc: Use image node_id 1 to create a new FusedDownsample object from inherited base classes: nn with example: obj = FusedDownsample(in_channel, out_channel, kernel_size, padding)