1.2 KiB
1.2 KiB
id, title, challengeType, videoId
id | title | challengeType | videoId |
---|---|---|---|
5e8f2f13c4cdbe86b5c72da1 | Natural Language Processing With RNNs: Building the Model | 11 | 32WBFS7lfsw |
Description
Tests
question:
text: |
Fill in the blanks below to complete the `build_model` function:
```py
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`
solution: 3