Purpose & architecture
InfoVAE is local Generator Core registry configuration 55, created by NewInfoVAE in the variational package. Its exact constructor and configuration settings are preserved below.
The shared implementation encodes latent means and log variances, samples with reparameterization, decodes the sample and computes a Gaussian KL term. Train combines binary cross-entropy reconstruction loss with a configurable beta multiplier on KL divergence.
Train returns the objective without an optimizer update. Named configurations such as VQ-VAE add parameter flags to the shared variational implementation; their names alone do not supply a vector-quantization codebook or the complete original architecture.
This source generation
This record follows the claude/improve-math-logic-ehIW1 branch of Janady13/complete-agi-core at commit 33aa84f2aa61cedbe010240ada7f4efbdfe795a7. The snapshot identifies the source inspected in this audit. It is not a statement about which revision is currently running on a device.
| Field | Source record |
|---|---|
| Revision | 33aa84f2aa61cedbe010240ada7f4efbdfe795a7 |
| Branch | claude/improve-math-logic-ehIW1 |
| Recorded generation | Generator Core · variational |
Recovered implementation structure
These paths locate the components and entry points represented by this build. The source register contains their inspected revisions.
- generator_core/pkg/generators/variational/variational.go
Behavior & verification limits
Train returns the objective without an optimizer update. Named configurations such as VQ-VAE add parameter flags to the shared variational implementation; their names alone do not supply a vector-quantization codebook or the complete original architecture.
Original project documentation
The following documentation is preserved as a dated source account. Claims in it retain the source’s wording and must be read alongside the implementation notes above.
func NewInfoVAE() *VariationalGenerator {
g := NewVariationalGenerator(55, "InfoVAE", 64)
g.Config().Params["mmd_weight"] = 100.0
return g
}
Equations in this build
4 linked mathematical records. Each opens its notation, interpretation and source.
variational · ELBO
This relation defines ELBO in the source section “variational · ELBO”. It specifies the displayed relationship between the named quantities or parameters. Its interpretation…
func (g *VariationalGenerator) encode(x []float64) ([]float64, []float64) · reparameterize performs reparameterization trick: z
This relation defines reparameterize performs reparameterization trick: z in the source section “func (g *VariationalGenerator) encode(x []float64) ([]float64, []float64) ·…
func (g *VariationalGenerator) klDivergence(mu, logVar []float64) float64 · KL
This relation defines KL in the source section “func (g *VariationalGenerator) klDivergence(mu, logVar []float64) float64 · KL”. Uses logarithmic scaling; its base and the…
func (g *VariationalGenerator) Train(input, target []float64) (float64, error) · ELBO
This relation defines ELBO in the source section “func (g *VariationalGenerator) Train(input, target []float64) (float64, error) · ELBO”. It specifies the displayed relationship…