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Is this repository deprecated? #163
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Hi Eric,
Thank you for the question. While the principles of the AdaNet algorithm
still stand, the implementation of the AdaNet library is deeply tied to
tf.Estimator. With the transition to TF2 and keras.Models, "outer-loop"
libraries (such as AutoKeras) have made "outer-loop" algorithms (such as
AdaNet) easier to implement, and there is less of a need for a dedicated
"one-stop" library for searching, training, and ensembling DNNs. As such,
we have decided not to port AdaNet over to Keras.
However, we do have an alternative solution for architecture search +
distributed training in the cloud that is more future-proof (i.e., supports
Keras):
https://github.com/google/model_search
…On Thu, Sep 29, 2022 at 2:31 PM Eric Hulburd ***@***.***> wrote:
Has this work been subsumed by other projects? It seems that AutoKeras is
actively maintained and I'm curious why AdaNet was never supported there:
keras-team/autokeras#415
<keras-team/autokeras#415>. Another alternative
AutoDL library that seems well maintained is Auto-PyTorch
<https://github.com/automl/Auto-PyTorch>.
Perhaps AdaNet evolved into proprietary algorithms and software that are
only available through Google Cloud AutoML?
For reference, I'm interested in AdaNet more from the client side (ie I'm
evaluating AutoDL options either through a proprietary vendor or open
source software) rather than a researcher looking to push the field forward.
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I would like to know more about the current state of Adanet as an alternative to AutoKeras, since they may have issues on certain computing platforms (windows). Deep_AutoViML is also on the radar so @erichulburd hope you are still there. |
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Has this work been subsumed by other projects? It seems that AutoKeras is actively maintained and I'm curious why AdaNet was never supported there: keras-team/autokeras#415. Other alternative AutoDL libraries that seem well maintained are Auto-PyTorch and AutoGluon
Perhaps AdaNet evolved into proprietary algorithms and software that are only available through Google Cloud AutoML?
For reference, I'm interested in AdaNet more from the client side (ie I'm evaluating AutoDL options either through a proprietary vendor or open source software) rather than a researcher looking to push this particular field forward.
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