code: def test_pos_conv_add2(no_bias, data_shape):
      # conv + add fusion case 2
      class ConvAdd(nn.HybridBlock):
          def __init__(self, use_bias, **kwargs):
              super(ConvAdd, self).__init__(**kwargs)
              self.conv0 = nn.Conv2D(
                  channels=64,
                  kernel_size=(3, 3),
                  strides=1,
                  use_bias=use_bias,
              )
              self.conv1 = nn.Conv2D(
                  channels=64, kernel_size=(3, 3), strides=1
              )
              self.pool = nn.AvgPool2D(pool_size=(1, 1))
  
          def forward(self, x):
              out = self.pool(self.conv1(x)) + self.conv0(x)
              return out
  
      attr = {"conv": {"with_sum": "true"}}
      net = ConvAdd(use_bias=True)
      check_fusion(net, data_shape, attr, check_quantization=False)
  
imports: import copy
  import mxnet
  import pytest
  from subgraph_common import check_fusion, check_neg_fusion, check_quantize
  from subgraph_common import CustomNormalInit, DATA_SHAPE, RELU6, TailNegBlock
  from subgraph_common import DATA_SHAPE, SG_PASS_NAME, QUANTIZE_SG_PASS_NAME
  from mxnet.contrib import quantization
  from mxnet.gluon import nn
  from mxnet.test_utils import assert_almost_equal, assert_almost_equal_with_err
label_desc: Use image node_id 6 for calling a global function with example usage: test_pos_conv_add2(no_bias, data_shape) and returns: out