code: def test_bf16_flatten_slice_after_conv():
      data_fp32 = mx.symbol.Variable("data")
      data_bf16 = mx.symbol.Variable("data", dtype="bfloat16")
  
      conv_fp32 = mx.symbol.Convolution(
          data=data_fp32,
          name="conv",
          num_filter=64,
          kernel=(3, 3),
          stride=(1, 1),
      )
      flatten_fp32 = mx.symbol.flatten(data=conv_fp32)
      slice_fp32 = mx.symbol.slice(data=flatten_fp32, begin=0, end=1)
  
      conv_bf16 = mx.symbol.Convolution(
          data=data_bf16,
          name="conv",
          num_filter=64,
          kernel=(3, 3),
          stride=(1, 1),
      )
      flatten_bf16 = mx.symbol.flatten(data=conv_bf16)
      slice_bf16 = mx.symbol.slice(data=flatten_bf16, begin=0, end=1)
  
      shape = (2, 16, 16, 16)
      check_operator_accuracy(
          slice_fp32, slice_bf16, shape, bf16_use_fp32_params=False
      )
  
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 14 for calling a global function with example usage: test_bf16_flatten_slice_after_conv() without return types