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Prepare branch for the TFP 0.12.0 release #1199
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…hout. PiperOrigin-RevId: 346372466
…thesis tests. PiperOrigin-RevId: 346374625
Hello, this PR again implements the stopping ratio logistic distribution which was already discussed and reviewed [here](tensorflow#963). @srvasude , sorry for closing the other PR. I worked in your requested changes other than the transpose that needs to be done when sampling. Thanks. Cheers, Simon COPYBARA_INTEGRATE_REVIEW=tensorflow#990 from dirmeier:stopping_ratio 0743b54 PiperOrigin-RevId: 346376187
PiperOrigin-RevId: 346378914
…tyle-docstrings PiperOrigin-RevId: 346395749
PiperOrigin-RevId: 346430469
…utions, some nested distributions, and a mean field option. PiperOrigin-RevId: 346440980
…al.nn`. PiperOrigin-RevId: 346614698
This means one must only 'import tensorflow_probability' to load saved models that have serialized TFP keras layers and TFP CompositeTensor specs. PiperOrigin-RevId: 346639386
…he `Restructure` bijector. PiperOrigin-RevId: 346669515
PiperOrigin-RevId: 346676496
This is adapted from `SampleDiscardingKernel`, sans burn-in; it has the advantage of not wrapping `KernelResults`. PiperOrigin-RevId: 346698326
PiperOrigin-RevId: 346793654
…ters. PiperOrigin-RevId: 346868095
PiperOrigin-RevId: 346910502
PiperOrigin-RevId: 347085672
…ated as "_composite_tensor_shape_parameters". Prior to the fix, test fails with "ValueError: Input tensor 'IndependentNormal_2/log_prob/Sum:0' enters the loop with shape (), but has shape <unknown> after one iteration. To allow the shape to vary across iterations, use the `shape_invariants` argument of tf.while_loop to specify a less-specific shape." PiperOrigin-RevId: 347446310
…straining bijector. PiperOrigin-RevId: 347448699
PiperOrigin-RevId: 347460285
PiperOrigin-RevId: 347499168
PiperOrigin-RevId: 347505196
…dSampleDistribution`. PiperOrigin-RevId: 347528419
…on_test.testLogProbSample`. Re-enable after http://b/175654800 is resolved. PiperOrigin-RevId: 347535479
PiperOrigin-RevId: 347638177
PiperOrigin-RevId: 343150107
…able. PiperOrigin-RevId: 347655640
PiperOrigin-RevId: 347660796
… contexts. Add a property-based test that tries to create Distributions in eager mode then sample from them in graph mode, to exercise the failure mode. PiperOrigin-RevId: 347692243
PiperOrigin-RevId: 347710953
Adds `tfp.experimental.distributions.log_prob_ratio(p, x, q, y) = p(x) - q(y)`. Custom implementations are registered for `tfd.Independent`, `tfd.Sample`, `tfd.JointDistribution*`, `tfd.TransformedDistribution`, `tfb.Chain`, and `tfb.ScaleMatvecDiag`. MVNDiag is tested as a proof of concept, in transformed_distribution_test. PiperOrigin-RevId: 347822296
Also fixes an XLA compilation issue (no StringFormat, PrintV2 ops in XLA) introduced by the logdet degree-of-freedom warning. This was exposed by the new test in deterministic_test.py (Deterministic default bijector uses Chain, which uses composition.py). PiperOrigin-RevId: 347832464
Implement burn-in by sequencing two calls of run_kernel, and thinning by inserting a ThinningKernel into the kernel onion. Also change the default tracing function to account for the fact that the chain state history is no longer returned separately by default. Delete tests that no longer make sense. PiperOrigin-RevId: 347836706
Previously, had the exception: "TypeError: Tensors in list passed to 'inputs' of 'AddN' Op have types [float64, float64, float32] that don't all match." PiperOrigin-RevId: 347871205
Gamma(concentration=0) always samples 0. ExpGamma(concentration=0) always samples -inf. Beta(concentration1=0) always samples 0. Beta(concentration0=0) always samples 1. BetaBinomial(concentration1=0) always samples 0. BetaBinomial(concentration0=0) always samples total_counts. likewise for Dirichlet and DirichletMultinomial. Not changing the validation because (i) inertia, and (ii) any of these distributions is still degenerate with a 0 concentration, so should arguably be avoided when possible. PiperOrigin-RevId: 347876446
PiperOrigin-RevId: 348378916
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