code: def test_bf16_binary_broadcast_elemwise_mixed_input(function, dtype):
      ndim = np.random.randint(1, 6)
      dshape_0 = rand_shape_nd(ndim)
      dshape_1 = tuple()
      for i in range(ndim):
          if randint(0, 1):
              dshape_1 += (dshape_0[i],)
          else:
              dshape_1 += (1,)
  
      a = mx.np.random.uniform(-1, 1, dshape_0, dtype=np.float32)
      a_fp32 = mx.np.array(a, dtype=dtype)
      a_bf16 = a.astype("bfloat16")
  
      b = mx.np.random.uniform(-1, 1, dshape_1, dtype=np.float32)
      b_fp32 = mx.np.array(b, dtype=dtype)
      b_bf16 = b.astype("bfloat16")
  
      rtol = 1e-1
      atol = 5e-1
      etol = 0
  
      out_bf_16_1 = function(a_bf16, b_fp32)
      out_fp_32 = function(a_fp32, b_fp32)
      assert_almost_equal_with_err(
          out_bf_16_1, out_fp_32, rtol=rtol, atol=atol, etol=etol
      )
  
      out_bf_16_2 = function(a_fp32, b_bf16)
      assert_almost_equal_with_err(
          out_bf_16_2, out_fp_32, rtol=rtol, atol=atol, etol=etol
      )
  
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 9 for calling a global function with example usage: test_bf16_binary_broadcast_elemwise_mixed_input(function, dtype) without return types