Charles Weill

@ShettyHarapanahalli: This should be fixed now with #12 .

@Mistobaan : Are you still encountering the original error?

Could you try installing v0.2.0 from PyPi with pip? Let me know if that works for you.

> If I use `adanet.AutoEnsembleEstimator` to combine weak-learners, do those weak-learners combine side by side on the same layer with weights or one after another on multiple layers? AutoEnsembleEstimator use...

Can you please give an example of what you would prefer the API to look like? Perhaps the new [`adanet.AutoEnsembleEstimator` ](https://github.com/tensorflow/adanet/blob/master/adanet/autoensemble/estimator.py#L114)may be a better API for your needs? I'm considering...

My understanding is `tf.Estimator` will continue to be the recommended way to train and serve models in TF 2.0.

@tianxh1212 : With the following code and settings you should be able to get the same results: https://github.com/tensorflow/adanet/blob/master/adanet/examples/nasnet.py#L181 * We used the N=6, F=32 in the config. A single subnetwork...

@SmallyolkLiu: Have a look at [our research code that uses NASNet in AdaNet](https://github.com/tensorflow/adanet/tree/master/research/improve_nas). It shows you how you can get it working on Google Cloud MLE.

@tl-yang: Please see the details in our recent paper: https://arxiv.org/abs/1903.06236

@mmuratarat: We've successfully train all kinds of RNNs with different cells like `lstm`, `cudnn_lstm`, and `gru`. Like @dataforcast mentions, you will need to create a custom `adanet.subnetwork.Generator` and `adanet.subnetwork.Builder` subclasses...