Comments (3)
lucianopaz
commented on July 24, 2024
@ferrine, what would be an updated status on the tasks here? Some refer to the multi backend things that were discarded later. The executors now work and are tested but I don't know if there are tests against a scipy model. The transformed API seems to be inplace but I don't know if there are transformations that should still be tested. Currently, the forward sampler for posterior predictive samples needs to be aware of autotransformed variables, and does so by relying on what the transformed executor does.
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ferrine
commented on July 24, 2024
Updated
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ferrine
commented on July 24, 2024
I think we can add some more input to the board
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Related Issues (20)
- No transformations for Bounded Distributions
- Class level dimension and parameter information HOT 1
- Backport support for coords from pymc3
- Add log likelihood to arviz trace objects
- `sample_prior_predictive` and `sample_posterior_predictive` issues with `use_auto_batching=False` HOT 2
- Write a notebook on manual model vectorization HOT 1
- Mass matrix adaptation sampling code in notebooks fails HOT 1
- Error in transformed variables with manual model vectorization HOT 4
- Make pm.sample work with AR distribution HOT 6
- Changes in PR #271 don't work with BatchStacker HOT 2
- PyMC3 vs PyMC4 for a new project? HOT 2
- [Question] Is there a timeline or roadmap for PyMC4? HOT 2
- Numerical instabilities with tf.float32 for cholesky decomposition HOT 3
- ValueError: Cannot create a tensor proto whose content is larger than 2GB. HOT 2
- Connecting pymc4 and diffeqpy for differential equations HOT 1
- Sampling fails when `num_chains=1` HOT 5
- PYMC4.Bound not found HOT 3
- Add support for LocalLinearTrend and Seasonal HOT 1
- calculation with tensor run errors HOT 2
- ERROR (aesara.graph.opt): Optimization failure due to: constant_folding HOT 1
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