code: def Conv(
      data,
      num_filter=1,
      kernel=(1, 1),
      stride=(1, 1),
      pad=(0, 0),
      num_group=1,
      name="",
      suffix="",
  ):
      conv = mx.sym.Convolution(
          data=data,
          num_filter=num_filter,
          kernel=kernel,
          num_group=num_group,
          stride=stride,
          pad=pad,
          no_bias=True,
          name="%s%s_conv2d" % (name, suffix),
      )
      bn = mx.sym.BatchNorm(
          data=conv,
          name="%s%s_batchnorm" % (name, suffix),
          fix_gamma=True,
      )
      act = mx.sym.Activation(
          data=bn, act_type="relu", name="%s%s_relu" % (name, suffix)
      )
      return act
  
imports: import mxnet
label_desc: Use image node_id 1 for calling a global function with example usage: Conv(data, num_filter, kernel, stride, pad, num_group, name, suffix) and returns: act