code: def test_pos_concat_scale_align(data_shape, out_type):
      # concat scale alignment case
      class ConcatScaleAlign(nn.HybridBlock):
          def __init__(self, **kwargs):
              super(ConcatScaleAlign, self).__init__(**kwargs)
              self.shared_weight = mx.gluon.Parameter(
                  "shared_weight",
                  shape=(64, data_shape[1], 3, 3),
                  init=mx.init.Xavier(magnitude=2.24),
                  dtype="float32",
                  allow_deferred_init=True,
              )
  
          def forward(self, x):
              conv1 = mx.npx.convolution(
                  x,
                  kernel=(3, 3),
                  num_filter=64,
                  weight=self.shared_weight.data(x.device),
                  no_bias=True,
              )
              conv2 = mx.npx.convolution(
                  x,
                  kernel=(3, 3),
                  num_filter=64,
                  weight=self.shared_weight.data(x.device) * 2,
                  no_bias=True,
              )
              conv3 = mx.npx.convolution(
                  x,
                  kernel=(3, 3),
                  num_filter=64,
                  weight=self.shared_weight.data(x.device) * 3,
                  no_bias=True,
              )
              conv4 = mx.npx.convolution(
                  x,
                  kernel=(3, 3),
                  num_filter=64,
                  weight=self.shared_weight.data(x.device) * 4,
                  no_bias=True,
              )
              return mx.np.concatenate(
                  [conv1, conv2, conv3, conv4], axis=1
              )
  
          def infer_shape(self, x, *args):
              self.shared_weight.weight = (64, data_shape[1], 3, 3)
  
      concat = ConcatScaleAlign()
      check_quantize(
          concat,
          data_shape,
          out_type,
          check_calibration=True,
          check_scale_align=True,
      )
  
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 14 for calling a global function with example usage: test_pos_concat_scale_align(data_shape, out_type) and returns: mx