code: def testBfloat16(self):
      a = np.random.uniform(-100, 100, 100).astype(np.float32)
      with self.cached_session(use_gpu=False):
          b = math_ops.cast(
              math_ops.cast(a, dtypes.bfloat16), dtypes.float32
          )
          self.assertAllClose(a, self.evaluate(b), rtol=1 / 128.0)
      with self.cached_session():
          b = math_ops.cast(
              math_ops.cast(a, dtypes.bfloat16), dtypes.float32
          )
          self.assertAllClose(a, self.evaluate(b), rtol=1 / 128.0)
  
imports: import numpy
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_state_ops
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 8 for calling the CastOpTest obj's underlying member method code with example usage: obj.testBfloat16() without return types