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I have set up the following workflow for MFBO, hoping that after loading existing data, the model will recommend a new experiment for me:
parameters.append(
RangeParameter(
name=fidelity_para_info["name"],
parameter_type=ParameterType.FLOAT,
lower=fidelity_para_info["low"],
upper=fidelity_para_info["high"],
is_fidelity=fidelity_para_info["is_fidelity"],
target_value=1
)
)
search_space = SearchSpace(parameters=parameters)
experiment = Experiment(name="my_experiment", search_space=search_space)
# (Omitting the part where old data (arms) and objective data are loaded)
botorch_kwargs = {
"experiment": experiment,
"data": experiment.fetch_data(),
}
model = Models.BOTORCH_MODULAR(**botorch_kwargs)
candidate = model.gen(gen_num)
However, this does not seem to work. Are there any relevant examples I can refer to?
Thanks in advance!
Please provide any relevant code snippet if applicable.
Code of Conduct
I agree to follow this Ax's Code of Conduct
The text was updated successfully, but these errors were encountered:
If I want to perform multi-objective MFBO, is it possible?
I'm not 100% sure, but I don't see why not. Would you please paste a minimal reproducible example so that I can recreate your setup locally and help debug?
Question
Hello everyone,
I have set up the following workflow for MFBO, hoping that after loading existing data, the model will recommend a new experiment for me:
However, this does not seem to work. Are there any relevant examples I can refer to?
Thanks in advance!
Please provide any relevant code snippet if applicable.
Code of Conduct
The text was updated successfully, but these errors were encountered: