New in 0.17.0 (2022-07-14)#
Experimental MuData support for
TOTALVIvia the method
setup_mudata(). For several of the existing
AnnDataFieldclasses, there is now a MuData counterpart with an additional
mod_keyargument used to indicate the modality where the data lives (e.g.
MuDataLayerField). These modified classes are simply wrapped versions of the original
AnnDataFieldcode via the new
Modification of the
generative()method’s outputs to return prior and likelihood properties as
Distributionobjects. Concerned modules are
VAEC. This allows facilitating the manipulation of these distributions for model training and inference #1356.
Major changes to Jax support for scvi-tools models to generalize beyond
JaxSCVI. Support for Jax remains experimental and is subject to breaking changes:
Enable basic device management in Jax-backed modules #1585.
Refactor metrics code and use
MetricCollectionto update metrics in bulk #1529.
Any methods relying on the output of
generativefrom existing scvi-tools models (e.g.
SCANVI) will need to be modified to accept
torch.Distributionobjects rather than tensors for each parameter (e.g.
The signature of
compute_and_log_metrics()has changed to support the use of
MetricCollection. The typical modification required will look like changing
self.compute_and_log_metrics(scvi_loss, self.train_metrics, "train"). The same is necessary for validation metrics except with
self.val_metricsand the mode
Fix issue with
get_normalized_expression()with multiple samples and additional continuous covariates. This bug originated from
generative()failing to match the dimensions of the continuous covariates with the input when
inference()in multiple module classes #1548.