code: def test_bf16_concat():
      dshape = rand_shape_nd(4)
      a_shape = tuple(dshape)
      b_shape = tuple(dshape)
  
      a_sym_fp32 = mx.sym.Variable("data")
      b_sym_fp32 = mx.sym.Variable("data_1")
  
      a_sym_bf16 = mx.sym.Variable("data", dtype="bfloat16")
      b_sym_bf16 = mx.sym.Variable("data_1", dtype="bfloat16")
      for axis in range(0, 4):
          concat_sym_fp32 = mx.sym.concat(
              a_sym_fp32, b_sym_fp32, dim=axis
          )
          concat_sym_bf16 = mx.sym.concat(
              a_sym_bf16, b_sym_bf16, dim=axis
          )
  
          dshapes = {"data": a_shape, "data_1": b_shape}
          check_operator_accuracy(
              concat_sym_fp32,
              concat_sym_bf16,
              dshapes,
              num_input_data=2,
              bf16_use_fp32_params=True,
          )
  
imports: import os
  import sys
  import mxnet
  import numpy
  from random import randint
  import itertools
  from mxnet.test_utils import assert_almost_equal_with_err, rand_shape_nd
  import pytest
label_desc: Use image node_id 10 for calling a global function with example usage: test_bf16_concat() without return types