code: def network_structure_1():
      data1 = mx.sym.var("data1", shape=(2, 3, 10, 10))
      data2 = mx.sym.var("data2")
      conv1 = mx.sym.Convolution(
          data=data1,
          weight=data2,
          no_bias=True,
          kernel=(2, 2),
          num_filter=1,
      )
      conv2 = mx.sym.Convolution(
          data=data2, no_bias=True, kernel=(1, 1), num_filter=1
      )
      out = mx.sym.Group([conv1, conv2])
      return (out, ["data1"], [(2, 3, 10, 10)])
  
imports: import os
  import sys
  import ctypes
  import mxnet
  from mxnet.base import SymbolHandle, check_call, _LIB, mx_uint, c_str_array, c_str, mx_real_t
  from mxnet.symbol import Symbol
  import numpy
  from mxnet.test_utils import assert_almost_equal, environment
  from mxnet import gluon
  from mxnet.gluon import nn
  from mxnet import nd, npx
  import pytest
  import tempfile
label_desc: Use image node_id 1 for calling a global function with example usage: network_structure_1() and returns: out,  list,  list