code: def test(self, use_cpu_only, backend, dims, batch_size, input_length):
      # input shape: 2D tensor (batch_size, input_length)
      # output shape: 3D tensor (batch_size, input_length, output_dim)
      shape = (batch_size, input_length)
      model = tf.keras.Sequential(
          [
              tf.keras.layers.Embedding(
                  batch_input_shape=shape,
                  input_dim=dims[0],
                  output_dim=dims[1],
                  input_length=input_length,
              )
          ]
      )
      run_compare_tf_keras(
          model,
          [random_gen(shape, rand_min=0, rand_max=dims[0])],
          use_cpu_only=use_cpu_only,
          backend=backend,
          atol=1e-3,
          rtol=1e-4,
      )
  
imports: import random
  from coremltools.converters.mil import testing_reqs
  from coremltools.converters.mil.frontend.tensorflow2.test.testing_utils import run_compare_tf_keras
  from coremltools.converters.mil.testing_reqs import *
label_desc: Use image node_id 1 for calling the TestEmbedding obj's underlying member method code with example usage: obj.test(use_cpu_only, backend, dims, batch_size, input_length) without return types