Honor discard_tuned_samples during KeyboardInterrupt #3785
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
junpenglao
reviewed
Jan 23, 2020
pymc3/sampling.py
Outdated
| @@ -470,7 +470,7 @@ def sample( | |||
| _log.info("Multiprocess sampling ({} chains in {} jobs)".format(chains, cores)) | |||
| _print_step_hierarchy(step) | |||
| try: | |||
| trace = _mp_sample(**sample_args) | |||
| trace = _mp_sample(**sample_args, discard_tuned_samples=discard_tuned_samples) | |||
There was a problem hiding this comment.
why not add it to sample_args?
Codecov Report
@@ Coverage Diff @@
## master #3785 +/- ##
=========================================
Coverage ? 90.61%
=========================================
Files ? 133
Lines ? 20340
Branches ? 0
=========================================
Hits ? 18432
Misses ? 1908
Partials ? 0
|
junpenglao
approved these changes
Jul 1, 2020
gmingas
added a commit
to alan-turing-institute/pymc3
that referenced
this pull request
Jul 22, 2020
* Update GP NBs to use standard notebook style (pymc-devs#3978) * update gp-latent nb to use arviz * rerun, run black * rerun after fixes from comments * rerun black * rewrite radon notebook using ArviZ and xarray (pymc-devs#3963) * rewrite radon notebook using ArviZ and xarray Roughly half notebook has been updated * add comments on xarray usage * rewrite 2n half of notebook * minor fix * rerun notebook and minor changes * rerun notebook on pymc3.9.2 and ArviZ 0.9.0 * remove unused import * add change to release notes * SMC: refactor, speed-up and run multiple chains in parallel for diagnostics (pymc-devs#3981) * first attempt to vectorize smc kernel * add ess, remove multiprocessing * run multiple chains * remove unused imports * add more info to report * minor fix * test log * fix type_num error * remove unused imports update BF notebook * update notebook with diagnostics * update notebooks * update notebook * update notebook * Honor discard_tuned_samples during KeyboardInterrupt (pymc-devs#3785) * Honor discard_tuned_samples during KeyboardInterrupt * Do not compute convergence checks without samples * Add time values as sampler stats for NUTS (pymc-devs#3986) * Add time values as sampler stats for NUTS * Use float time counters for nuts stats * Add timing sampler stats to release notes * Improve doc of time related sampler stats Co-authored-by: Alexandre ANDORRA <[email protected]> Co-authored-by: Alexandre ANDORRA <[email protected]> * Drop support for py3.6 (pymc-devs#3992) * Drop support for py3.6 * Update RELEASE-NOTES.md Co-authored-by: Colin <[email protected]> Co-authored-by: Colin <[email protected]> * Fix Mixture distribution mode computation and logp dimensions Closes pymc-devs#3994. * Add more info to divergence warnings (pymc-devs#3990) * Add more info to divergence warnings * Add dataclasses as requirement for py3.6 * Fix tests for extra divergence info * Remove py3.6 requirements * follow-up of py36 drop (pymc-devs#3998) * Revert "Drop support for py3.6 (pymc-devs#3992)" This reverts commit 1bf867e. * Update README.rst * Update setup.py * Update requirements.txt * Update requirements.txt Co-authored-by: Adrian Seyboldt <[email protected]> * Show pickling issues in notebook on windows (pymc-devs#3991) * Merge close remote connection * Manually pickle step method in multiprocess sampling * Fix tests for extra divergence info * Add test for remote process crash * Better formatting in test_parallel_sampling Co-authored-by: Junpeng Lao <[email protected]> * Use mp_ctx forkserver on MacOS * Add test for pickle with dill Co-authored-by: Junpeng Lao <[email protected]> * Fix keep_size for arviz structures. (pymc-devs#4006) * Fix posterior pred. sampling keep_size w/ arviz input. Previously posterior predictive sampling functions did not properly handle the `keep_size` keyword argument when getting an xarray Dataset as parameter. Also extended these functions to accept InferenceData object as input. * Reformatting. * Check type errors. Make errors consistent across sample_posterior_predictive and fast_sample_posterior_predictive, and add 2 tests. * Add changelog entry. Co-authored-by: Robert P. Goldman <[email protected]> * SMC-ABC add distance, refactor and update notebook (pymc-devs#3996) * update notebook * move dist functions out of simulator class * fix docstring * add warning and test for automatic selection of sort sum_stat when using wassertein and energy distances * update release notes * fix typo * add sim_data test * update and add tests * update and add tests * add docs for interpretation of length scales in periodic kernel (pymc-devs#3989) * fix the expression of periodic kernel * revert change and add doc * FIXUP: add suggested doc string * FIXUP: revertchanges in .gitignore * Fix Matplotlib type error for tests (pymc-devs#4023) * Fix for issue 4022. Check for support for `warn` argument in `matplotlib.use()` call. Drop it if it causes an error. * Alternative fix. * Switch from pm.DensityDist to pm.Potential to describe the likelihood in MLDA notebooks and script examples. This is done because of the bug described in arviz-devs/arviz#1279. The commit also changes a few parameters in the MLDA .py example to match the ones in the equivalent notebook. * Remove Dirichlet distribution type restrictions (pymc-devs#4000) * Remove Dirichlet distribution type restrictions Closes pymc-devs#3999. * Add missing Dirichlet shape parameters to tests * Remove Dirichlet positive concentration parameter constructor tests This test can't be performed in the constructor if we're allowing Theano-type distribution parameters. * Add a hack to statically infer Dirichlet argument shapes Co-authored-by: Brandon T. Willard <[email protected]> Co-authored-by: Bill Engels <[email protected]> Co-authored-by: Oriol Abril-Pla <[email protected]> Co-authored-by: Osvaldo Martin <[email protected]> Co-authored-by: Adrian Seyboldt <[email protected]> Co-authored-by: Alexandre ANDORRA <[email protected]> Co-authored-by: Colin <[email protected]> Co-authored-by: Brandon T. Willard <[email protected]> Co-authored-by: Junpeng Lao <[email protected]> Co-authored-by: rpgoldman <[email protected]> Co-authored-by: Robert P. Goldman <[email protected]> Co-authored-by: Tirth Patel <[email protected]> Co-authored-by: Brandon T. Willard <[email protected]>
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
We used to ignore the
discard_tuned_samplessetting when deciding which samples to keep when we interrupt sampling with Ctrl-C, so that pymc3 would not give us any trace if there were no non-tuning samples yet.