Denoiser

Pinned implementation and paper LDLM @ e18c42a, not yet public · arXiv:2605.07933v1 · OpenWebText · 1024 · checkpoint, tokenizer and saved statistics not verified · How to read

Sampler › Denoiser

Predicted clean latents

×

tensor

The denoiser’s estimate of the clean latents.

shape
z^0\hat z_0 [B batch, T positions, 768 d]
Sources

Contextual evidence from Denoiser

The denoiser owns the time embedding’s two affine layers, one rotary table for all blocks, an affine projection of the concatenated input, and the stack.

The implementation, pinned at revision e18c42acdfb7, not yet public

Contextual evidence from Denoiser

The time embedding passes its MLP and a SiLU; the noised latents are concatenated with the previous clean estimate, zeros when there is none, and projected; the stack runs in bfloat16.

The implementation, pinned at revision e18c42acdfb7, not yet public

Contextual evidence from Denoiser

The denoiser’s stack applies the blocks in order and then the output layer, each with the time condition.

The implementation, pinned at revision e18c42acdfb7, not yet public

Contextual evidence from Denoiser

Diffusion: self-conditioning on, `t_min` 0.05 and `eps` 10⁻⁵; the adaptive time sampler has 100 bins, a minimum weight of 0.0001, an EMA of 0.9 and updates every 5,000 steps; the denoiser’s EMA decay is 0.9999; scheduler `tanh` with d = 3, solver `euler`, `ode_sampling` false, N = 128 by default; the denoiser has 12 blocks of width 768 with 12 heads, time conditioning `adaln`, a standard MLP, softcap 50 and self-conditioning by concatenation; the timestep embedding’s `max_period` is 10.

The implementation, pinned at revision e18c42acdfb7, not yet public

Contextual evidence from Noise estimate

The denoiser’s clean prediction is converted into the noise estimate and the score with the marginal’s mean and standard deviation.

The implementation, pinned at revision e18c42acdfb7, not yet public

Contextual evidence from Noise estimate

The tangent schedule: α = 1/√(1 + d² tan²(πt/2)), σ = √(1 − α²); β(t) is evaluated with t clipped at 0.95.

The implementation, pinned at revision e18c42acdfb7, not yet public

Contextual evidence from Output projection

The output layer: gain-only LayerNorm, a shift and a scale from the time condition, and an affine projection initialized at zero.

The implementation, pinned at revision e18c42acdfb7, not yet public