docs: various fixes for tf.keras docs. #1119
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stoksc
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Aug 19, 2020
| @@ -9,8 +9,7 @@ hyperparameters: | |||
| dropout1: 0.25 | |||
| dropout2: 0.5 | |||
| resources: | |||
| # Use 16 GPUs to train the model. | |||
| slots_per_trial: 16 | |||
| slots_per_trial: 8 | |||
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What's the reason for this change? Just curious, seems reasonable because this is what the parallel tests run anyways (test_pytorch_parallel).
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The quick start tutorial references this file but claims that slots_per_trial is 8. Seems like a reasonable default value anyway...
| @@ -713,9 +732,12 @@ def keras_callbacks(self) -> List[tf.keras.callbacks.Callback]: | |||
| Determined training behavior. | |||
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| .. note:: | |||
| If a callback is supplied that has implemented `keras.callbacks.Callback.on_epoch_end | |||
| If you specify a Keras callback that uses the `on_epoch_begin | |||
| <https://www.tensorflow.org/api_docs/python/tf/keras/callbacks/Callback#on_epoch_begin>`__ | |||
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ah, good catch adding on_epoch_begin, too.
* Clarify docs on epoch boundaries * Fix epoch size in Fashion MNIST example * Make wrapper requirements more clear * Better linking to API reference.
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