code: def BF16Model(model, custom_objects=None):
      original_policies = []
      policy_bf16 = mixed_precision.Policy("mixed_bfloat16")
      for layer in model.layers:
          original_policies.append(layer._dtype_policy)
          layer._set_dtype_policy(policy_bf16)
      try:
          # save or load operation may fail
          with TemporaryDirectory() as temp_dir:
              model.save(temp_dir)
              bf16_model = tf.keras.models.load_model(
                  temp_dir, custom_objects=custom_objects
              )
      except Exception as _e:
          # if a functional model failed to save or load, try `from_config`
          if hasattr(model, "input_shape"):
              config = model.get_config()
              bf16_model = tf.keras.Model.from_config(config)
              with TemporaryDirectory() as temp_dir:
                  model.save_weights(temp_dir)
                  bf16_model.load_weights(temp_dir)
              patch_compiled(bf16_model, model)
          else:
              invalidInputError(
                  False, "Failed to convert model to bfloat16 dtype."
              )
      finally:
          for policy, layer in zip(original_policies, model.layers):
              layer._set_dtype_policy(policy)
      return bf16_model
  
imports: from tempfile import TemporaryDirectory
  import tensorflow
  from tensorflow.keras import mixed_precision
  from bigdl.nano.utils.common import invalidInputError
  from bigdl.nano.utils.tf import patch_compiled
label_desc: Use image node_id 1 for calling a global function with example usage: BF16Model(model, custom_objects) and returns: bf16_model