code: def test_pos_conv_add4(no_bias, data_shape, out_type):
      # conv + add fusion case 4
      class ConvAdd(nn.HybridBlock):
          def __init__(self, use_bias, **kwargs):
              super(ConvAdd, self).__init__(**kwargs)
              self.conv0 = nn.Conv2D(
                  channels=data_shape[1],
                  kernel_size=(1, 1),
                  strides=1,
                  use_bias=use_bias,
              )
              self.conv1 = nn.Conv2D(
                  channels=64,
                  kernel_size=(3, 3),
                  strides=1,
                  use_bias=use_bias,
              )
  
          def forward(self, x):
              out = self.conv1(x + self.conv0(x))
              return out
  
      net = ConvAdd(use_bias=True)
      check_quantize(net, data_shape, out_type)
  
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 8 for calling a global function with example usage: test_pos_conv_add4(no_bias, data_shape, out_type) and returns: out