Comments (4)
grad (and potentially also fval) won't be computed when using least squares optimizers, so they can't be stored in history.
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after looking at #902, I realized there already are multiple conversion functions, so I would agree that these fields are no longer necessary.
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these are 1-1 to fval, grad,
Ideally
waste of storage
At least for HDF5, when enabling compression, this shouldn't be a big deal
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grad (and potentially also fval) won't be computed when using least squares optimizers, so they can't be stored in history.
In
pyPESTO/pypesto/history/base.py
Line 339 in e3099c0
fval, grad, hess etc are computed from res, sres if applicable. This function is always called before storing stuff to history, so these values should then be available in history.
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Related Issues (20)
- Reading ensemble_predictions from hd5f fails if summary was saved
- Software using pymc HOT 2
- Flaky test `test_pipeline[Metropolis-rosenbrock]` HOT 1
- `ReturnDataReportingMode` not handled correctly for `AggregatedObjective` HOT 9
- fval is not saved in hdf5 file in multistart optimization HOT 2
- Problems with startpoint method HOT 2
- SciPy optimizer does redundant function evaluations e.g. for AMICI objectives HOT 1
- Pypesto Optimization ignores bounds HOT 6
- `ScipyDifferentialEvolutionOptimizer` appears to load the AMICI model many times HOT 4
- Deprecation for `get_for_key` notice suggests code that will error. HOT 2
- Flaky test `test/sample/test_sample.py::test_samples_cis` HOT 8
- Python version support policy HOT 1
- Failure to load HDF5 history from write-protected files
- AMICI expects rdata not dict HOT 5
- pymc sampler appears to not sample correctly HOT 1
- pypesto import is slow HOT 13
- Q: Remove theano? HOT 1
- Issue using MultiProcess engine HOT 2
- Plenty of GitHub Actions warnings
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