Handle Cholesky errors when fitting a fully bayesian model #1507
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) Summary: Pull Request resolved: pytorch#1507 X-link: facebook/Ax#1271 Adds a `_psd_safe_pyro_mvn_sample` to catch LinAlgErrors that happen in `pyro.sample`, and retries with increased jitter. Modeled after linear operator's `psd_safe_cholesky`. Differential Revision: D41405255 fbshipit-source-id: bddd971e0f27ee14b3674dfa80799871eea95515
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…1507) Summary: X-link: pytorch/botorch#1507 Pull Request resolved: facebook#1271 Adds a `_psd_safe_pyro_mvn_sample` to catch LinAlgErrors that happen in `pyro.sample`, and retries with increased jitter. Modeled after linear operator's `psd_safe_cholesky`. Differential Revision: D41405255 fbshipit-source-id: f56cab6faf07067cd89fe1f48c2be0e7bca30dda
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Summary: X-link: pytorch/botorch#1507 Pull Request resolved: #1271 Adds a `_psd_safe_pyro_mvn_sample` to catch LinAlgErrors that happen in `pyro.sample`, and retries with increased jitter. Modeled after linear operator's `psd_safe_cholesky`. Reviewed By: Balandat Differential Revision: D41405255 fbshipit-source-id: 6fea8f1a953d2ad8ec5c0ca2ca8c13732f729879
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Summary: Adds a
_psd_safe_pyro_sampleto catch LinAlgErrors that happen inpyro.sample, and retries with increased jitter. Modeled after linear operator'spsd_safe_cholesky.Differential Revision: D41405255