ee1e8abd87
* feat(tools): add seed/solution restore script * chore(curriculum): remove empty sections' markers * chore(curriculum): add seed + solution to Chinese * chore: remove old formatter * fix: update getChallenges parse translated challenges separately, without reference to the source * chore(curriculum): add dashedName to English * chore(curriculum): add dashedName to Chinese * refactor: remove unused challenge property 'name' * fix: relax dashedName requirement * fix: stray tag Remove stray `pre` tag from challenge file. Signed-off-by: nhcarrigan <nhcarrigan@gmail.com> Co-authored-by: nhcarrigan <nhcarrigan@gmail.com>
55 lines
908 B
Markdown
55 lines
908 B
Markdown
---
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id: 5e8f2f13c4cdbe86b5c72da2
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title: 'Natural Language Processing With RNNs: Training the Model'
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challengeType: 11
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videoId: hEUiK7j9UI8
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dashedName: natural-language-processing-with-rnns-training-the-model
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---
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# --question--
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## --text--
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Fill in the blanks below to save your model's checkpoints in the `./checkpoints` directory and call the latest checkpoint for training:
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```py
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checkpoint_dir = __A__
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checkpoint_prefix = os.path.join(checkpoint_dir, 'ckpt_{epoch}')
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checkpoint_callback = tf.keras.callbacks.__B__(
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filepath=checkpoint_prefix,
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save_weights_only=True
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)
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history = model.fit(data, epochs=2, callbacks=[__C__])
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```
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## --answers--
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A: `'./training_checkpoints'`
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B: `ModelCheckpoint`
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C: `checkpoint_prefix`
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---
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A: `'./checkpoints'`
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B: `ModelCheckpoint`
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C: `checkpoint_callback`
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---
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A: `'./checkpoints'`
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B: `BaseLogger`
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C: `checkpoint_callback`
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## --video-solution--
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2
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