| 88 | |
| 89 | |
| 90 | class LossType(enum.Enum): |
| 91 | MSE = enum.auto() # use raw MSE loss (and KL when learning variances) |
| 92 | RESCALED_MSE = ( |
| 93 | enum.auto() |
| 94 | ) # use raw MSE loss (with RESCALED_KL when learning variances) |
| 95 | KL = enum.auto() # use the variational lower-bound |
| 96 | RESCALED_KL = enum.auto() # like KL, but rescale to estimate the full VLB |
| 97 | |
| 98 | def is_vb(self): |
| 99 | return self == LossType.KL or self == LossType.RESCALED_KL |
| 100 | |
| 101 | |
| 102 | class GaussianDiffusion: |
nothing calls this directly
no outgoing calls
no test coverage detected