Allow MCMC transforms for MultipleIndependentConstraints prior #619
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michaeldeistler
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michaeldeistler
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janfb
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Jan 27, 2022
| @@ -9,7 +9,7 @@ | |||
| from sbi.inference.posteriors.mcmc_posterior import MCMCPosterior | |||
| import torch | |||
| from pyknos.mdn.mdn import MultivariateGaussianMDN | |||
| from scipy.stats import beta, multivariate_normal, uniform | |||
| from scipy.stats import beta, multivariate_normal, uniform, lognorm | |||
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you could move this test to transform_tests.py, or copy it to keep both.
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michaeldeistler
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Jan 28, 2022
| @@ -387,7 +387,7 @@ def check_prior_support(prior): | |||
| """ | |||
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| try: | |||
| within_support(prior, prior.sample()) | |||
| within_support(prior, prior.sample((1,))) | |||
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With a MultipleIndependent distribution support.check(sample) requires a batched sample
janfb
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Jan 28, 2022
| @@ -387,7 +387,7 @@ def check_prior_support(prior): | |||
| """ | |||
|
|
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| try: | |||
| within_support(prior, prior.sample()) | |||
| within_support(prior, prior.sample((1,))) | |||
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This PR allows to infer the
transformfor priors that were provided asMultipleIndependentDistributions.In addition, it allows inferring the transform for any bounded distribution (not just interval constraints)