Skip to content
This repository has been archived by the owner on Sep 18, 2024. It is now read-only.

Add condition control when passing parameters bounds to scipy.minimize. #4977

Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 2 additions & 1 deletion nni/algorithms/hpo/gp_tuner/util.py
Original file line number Diff line number Diff line change
Expand Up @@ -89,7 +89,8 @@ def acq_max(f_acq, gp, y_max, bounds, space, num_warmup, num_starting_points):
x_seeds = [space.random_sample() for _ in range(int(num_starting_points))]

bounds_minmax = np.array(
[[bound['_value'][0], bound['_value'][-1]] for bound in bounds])
[[bound['_value'][0], bound['_value'][1 if bound['_type'] == 'quniform'
or bound['_type'] == 'qloguniform' else -1]] for bound in bounds])

for x_try in x_seeds:
# Find the minimum of minus the acquisition function
Expand Down