code: def test_dispatch_precision_keras(self):
      import tensorflow as tf
      import numpy as np
      from bigdl.nano.tf import patch_tensorflow, unpatch_tensorflow
      from bigdl.nano.tf.keras import Sequential
      from bigdl.nano.tf.keras.layers import Embedding
  
      patch_tensorflow(precision="mixed_bfloat16")
      model = Sequential()
      model.add(
          Embedding(
              1000,
              64,
              input_length=10,
              embeddings_regularizer=tf.keras.regularizers.L2(),
              name="Layer",
          )
      )
      model.compile("rmsprop", "mse")
      output = model.get_layer("Layer").output
      assert output.dtype.name == "bfloat16"
      input_array = np.random.randint(1000, size=(32, 10))
      pred = model(input_array)
      assert output.dtype.name == "bfloat16"
  
      unpatch_tensorflow()
      model = Sequential()
      model.add(
          Embedding(
              1000,
              64,
              input_length=10,
              embeddings_regularizer=tf.keras.regularizers.L2(),
              name="Layer",
          )
      )
      model.compile("rmsprop", "mse")
  
      output = model.get_layer("Layer").output
      assert output.dtype.name == "float32"
      input_array = np.random.randint(1000, size=(32, 10))
      pred = model(input_array)
      assert output.dtype.name == "float32"
  
imports: from unittest import TestCase
label_desc: Use image node_id 2 for calling the TestDispatcherKeras obj's underlying member method code with example usage: obj.test_dispatch_precision_keras() without return types