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id, title, challengeType, videoId, dashedName
| id | title | challengeType | videoId | dashedName | 
|---|---|---|---|---|
| 5e8f2f13c4cdbe86b5c72da1 | Natural Language Processing With RNNs: Building the Model | 11 | 32WBFS7lfsw | natural-language-processing-with-rnns-building-the-model | 
--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