class_docstr: Simple embedding model.
class_docstr_tok: ["Simple","embedding","model","."]
code: def __init__(self, *args, **kwargs):
      super().__init__(*args, **kwargs)
      self.embed_layer = tf.keras.layers.Embedding(
          name="embedding",
          input_dim=10,  # vocabulary size.
          output_dim=6,  # embedding size.
          embeddings_initializer="uniform",
          input_length=4,
      )  # sequence length.
      self.pool_layer = tf.keras.layers.Dense(
          name="pooler",
          units=6,
          activation="tanh",
          kernel_initializer="zeros",
          bias_initializer="zeros",
      )
      self.probs_layer = tf.keras.layers.Dense(
          units=1, activation="softmax", name="classification"
      )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow import estimator
  from tensorflow_privacy.privacy.optimizers import dp_optimizer_keras
  from tensorflow_privacy.privacy.optimizers import dp_optimizer_keras_vectorized
label_desc: Use image node_id 1 to create a new SimpleEmbeddingModel object from inherited base classes: tf.keras with example: obj = SimpleEmbeddingModel()