Releases: sequential-parameter-optimization/spotPython
Releases · sequential-parameter-optimization/spotPython
v0.15.14: 0.15.14
New pytorch regression models with lr-sched. and initialization functions
v0.15.12: 0.15.12
- hidden_size generatot in nn_linear_regressor.py
- anisotropic is set to default in spot.py
v0.15.11: 0.15.11
surrogate_control_init accepts n_theta="anisotropic" which is the new default
print output reduced
v0.15.10: 0.15.10
spot.get_importance() returns zeros when no importance information is available due to isotropic Kriging
v0.15.9: 0.15.9
Documentation of the netlightregression classes updated
v0.15.8: 0.15.8
- Improved documentation for light.regression (init.py handling)
- Takes care of the FutureWarning:
torch.testing.assert_allclose()is deprecated since 1.12 and will be removed in a future release. Please usetorch.testing.assert_close()instead. You can find detailed upgrade instructions in pytorch/pytorch#61844.
v0.15.7: 0.15.7
tkagg
v0.15.6: 0.15.6
TkAgg Handling implemented for contour and importance plots
v0.15.5: 0.15.5
3.12 github workflows
v0.15.3
py312