Miles Olson

Unfortunately no, but you're right that it should be very straightforward to implement. Something like the following should do the trick. ``` def foo(client: AxClient, arm_name: str) -> int: for...

Hi @kurt-essential -- thanks for raising this with us; it is indeed a confusing user experience. As you discovered, under the hood the call to "predict" relies on using the...

Hi @Ianmendonca thanks for bringing this to our attention. I'll see to it that this gets resolved and included in the next patch version of Ax, and will update this...

Thanks for stepping in @CompRhys -- that's right, @Ianmendonca can use `object_to_json` as a workaround, and their current solution of calling `_to_json_snapshot` will work as well. For my understanding as...

Hi @jultou-raa thanks for raising this with us -- we are working on a comprehensive revamp of our plotting code and hope to get something out soon. In the meantime...

Hi @HOLL95 -- sorry to get back to you later than I intended. Ax does not normalize the objective values, but this shouldn't matter and you will be completely fine...

Hi @arnaudlahouati -- I'm glad to hear Ax is working well for your mat sci use case. Admittedly, Ax does not do a fantastic job of surfacing this information. Assuming...

Hi @omrisch I was not able to reproduce this behavior on my machine, but hopefully I can offer some advice. This is the code I ran, based largely off the...

Code sample with the adjustment: ``` from ax.api.client import Client from ax.api.configs import RangeParameterConfig # 1. Initialize the Client. client = Client() # 2. Configure where Ax will search. client.configure_experiment(...

You can follow this tutorial for how to use different acquisition functions from Botorch within Ax https://ax.dev/docs/tutorials/modular_botorch/