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--question--

--text--​

Fill in the blanks below to complete the build_model function:

def build_mode(vocab_size, embedding_dim, rnn_units, batch_size):
    model = tf.keras.Sequential([
        tf.keras.layers.Embedding(vocab_size,
                                  embedding_dim,
                                  batch_input_shape=[batch_size, None]),
        tf.keras.layers.__A__(rnn_units,
                              return_sequences=__B__,
                              recurrent_initializer='glorot_uniform),
        tf.keras.layers.Dense(__C__)
    ])
    __D__

--answers--​

A: ELU

B: True

C: vocab_size

D: return model

A: LSTM

B: False

C: batch_size

D: return model

A: LSTM

B: True

C: vocab_size

D: return model

--video-solution--​

3