DOC: LazyAdamOptimizer example #66
Conversation
|
cc @karmel . Do you mind giving this a once over? I'd like to have a small example in the first release branch. Going forward we'll strive for colab notebooks as well, and more interesting examples. |
|
@qlzh727 -- any chance you can take a look? I am unlikely to have time before the Dev Summit. |
|
Ack, I will take a quick look. |
|
Ah, sorry I forgot today is probably quite hectic. Probably doesn't need more than a glance its just MNIST with the LazyAdamOptimizer. I tested it and it converges fine |
| :return: Keras `Model` | ||
| """ | ||
| inputs = tf.keras.Input(shape=(784,), name='digits') | ||
| net = tf.keras.layers.Dense(64, activation='relu', name='dense_1')(inputs) |
There was a problem hiding this comment.
Since this is just a sequential model, you can probably use keras.models.Sequential to get rid of "net". That said, this is purely optional, and depends on whether you want to show case the functional or sequential model.
There was a problem hiding this comment.
Yeah, I have no real preference, but feel that the functional form is more familiar to other frameworks.
| validation_data=(data['x_val'], data['y_val'])) | ||
|
|
||
| # Evaluate the network | ||
| print('\n# Evaluate on test data') |
There was a problem hiding this comment.
Just curious why it need the leading '\n'. Alternatively you can use tf.logging, which will print with same format as other TF logs generated during training.
There was a problem hiding this comment.
All of the small implementation details were mostly copied from this:
https://github.com/tensorflow/docs/blob/master/site/en/r2/guide/keras/training_and_evaluation.ipynb
|
@qlzh727 thanks for the review! |
* DOC: optimizer example
Simple example using LazyAdamOptimizer tested after installing the dev pip package. After we publish a 0.1 release we can install it in colab and have interactive examples.