Comments (8)
@riyadparvez, in the short run you can get trials as ax_client.experiment.trials
, and you can get parameters from each one of the trials as trial.arm.parameters
. Will add this functionality to the service API, too, but that should get you unblocked for now.
from ax.
AxClient
class hasget_best_parameters()
method. I don't see any methods inAxClient
class that returns all the trials with their parameters and evaluation results. Is there any plans to add such API?
I think you can get the full results using the experiment object inside the client
ax = AxClient()
result = ax.experiment.fetch_data()
from ax.
This is what I see if I do print(result.df)
arm_name metric_name mean sem trial_index
0 0_0 hartmann6 -0.016126 0.0 0
1 0_0 l2norm 1.384382 0.0 0
2 1_0 hartmann6 -0.114288 0.0 1
3 1_0 l2norm 0.663507 0.0 1
4 2_0 hartmann6 -0.009832 0.0 2
5 2_0 l2norm 1.874537 0.0 2
Still no easy way to get the parameters and the metrics.
from ax.
@lena-kashtelyan thanks, it worked.
Is it also possible to expose which trial yielded the best results?
from ax.
Hello again, @riyadparvez –– currently get_best_parameters
outputs a tuple of parameterization and metric values; you can use the former as a workaround for now, to find which trial output the results.
get_best_parameters
is still somewhat under development; thank you for the good idea of adding the trial index to its output!
from ax.
This is now on master! You can do ax_client.get_trials_data_frame()
: )
from ax.
This functionality is now available in the latest stable version, 0.1.6!
from ax.
Thanks a lot! Will give it a try.
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Related Issues (20)
- Issue with tolerance for floating point and its relevance when using log_scale = True HOT 7
- Question: does Ax support working with Tensorflow models? HOT 2
- Feature Request: Conditional Parameter Constraints HOT 5
- Questions about define how to evaluate HOT 3
- get_countour_plot() not plotting all trials HOT 4
- Error: A list of 'ChoiceParameter' is not iterable HOT 4
- [Bug] Generation Strategy equality check error without call to repr HOT 1
- ax.dev, GitHub readme, and loop tutorial examples are ignoring `minimize` kwarg HOT 2
- Get Started code gives the same result regardless of random seed HOT 3
- Trouble with searching documentation (Algolia, API docs, etc.), for example `get_next_trials` HOT 1
- Issue when starting an AxClient with out-of-design points HOT 2
- cannot import name 'TrainingData' HOT 2
- applying complex constrains HOT 2
- Ax is not not starting as many workers as I'd like to; sometimes, get_next_trials returns 0 new trials HOT 3
- Evaluating custom candidates HOT 2
- Input Feature Selection - Does the relevant code exist? HOT 6
- [Feature Request] support constraints on `ChoiceParameters` HOT 4
- Extending Models.THOMPSON with an extra parameter HOT 1
- There are some questions when i use the Ax HOT 6
- Space characters in the objective name AND specifying a threshold leads to an error message: "AssertionError: Outcome constraint should be of form `metric_name >= x" HOT 1
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