code: def test_pos_single_concat_pos_neg(data_shape, out_type):
      class ConvDataConcat(nn.HybridBlock):
          def __init__(self, dim, **kwargs):
              super(ConvDataConcat, self).__init__(**kwargs)
              self.conv0 = nn.Conv2D(
                  channels=4,
                  kernel_size=(1, 1),
                  strides=1,
                  use_bias=False,
              )
              self.act = nn.Activation(activation="relu")
              self.concat_dim = dim
  
          def forward(self, x):
              relu_out = self.act(self.conv0(x))
              out = mx.np.concatenate(
                  [x, relu_out], axis=self.concat_dim
              )
              return out
  
      concat = ConvDataConcat(dim=1)
      check_quantize(
          concat, data_shape, out_type, name="", check_calibration=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 13 for calling a global function with example usage: test_pos_single_concat_pos_neg(data_shape, out_type) and returns: out