Hi, thanks for this amazing tool!
I trained a scVI model(scvi.model.SCVI) and tried to generate cell expression(cells number x genes number) from latent space(cells number x latent dims). I try to make this by using scvi.model.SCVI.generative() and get a set of ZINB distribution. But when I run ZINB.sample() I get an error:
Blockquote
Expected parameter rate (Tensor of shape (68579, 17789)) of distribution Gamma(concentration: torch.Size([68579, 17789]), rate: torch.Size([68579, 17789])) to satisfy the constraint GreaterThan(lower_bound=0.0), but found invalid values:\ntensor([[0., 0., 0., …, 0., 0., 0.], [0., 0., 0., …, 0., 0., 0.], [0., 0., 0., …, 0., 0., 0.], …, [0., 0., 0., …, 0., 0., 0.], [0., 0., 0., …, 0., 0., 0.], [0., 0., 0., …, 0., 0., 0.]], device=‘cuda:0’)"
I fund that the generated mu for the ZINB is all inf. I wander is there anything wrong when I generate the cell expression? I used the latent expression from get_latent_representation() and library size from get_latent_library_size().
Or is there any easier way to directly generate cell expression from the latent representation? Any help would be very appreciated!