unsloth/studio/backend/models
Daniel Han efc7a44747 Studio diffusion (Phase 12): First-Block-Cache step caching for many-step DiT
Add opt-in step caching (First-Block-Cache) for the diffusion transformer. Across
denoise steps a DiT's output settles, so once the first block's residual barely
changes the remaining blocks are skipped and their cached output reused. diffusers
ships it natively (FirstBlockCacheConfig + transformer.enable_cache, with the
standalone apply_first_block_cache hook as a fallback).

Measured on Flux.1-dev (28 steps, 1024px): ~1.4x on top of torch.compile (2.83 ->
2.03s) at LPIPS ~0.08 vs the no-cache output, well inside the quality bar.

OFF by default and a per-load opt-in: the win scales with step count, so it is for
many-step models (Flux / Qwen-Image) and pointless for few-step distilled models
(e.g. Z-Image-Turbo at ~8 steps), where a single skipped step is a large fraction
of the trajectory. It composes with regional compile only with fullgraph=False (the
cache's per-step decision is a torch.compiler.disable graph break), which the speed
layer now switches to automatically when a cache is engaged. Best-effort: a model
whose block signature the hook does not recognise is caught and the load proceeds
uncached.

- new core/inference/diffusion_cache.py: normalize_transformer_cache + apply_step_cache
  (enable_cache / apply_first_block_cache fallback; threshold auto-raised for a
  quantised transformer per ParaAttention's fp8 guidance; lazy diffusers import).
- diffusion_speed.py: apply_speed_optims takes cache_active; compile drops fullgraph
  when a cache is engaged.
- diffusion.py: apply_step_cache before compile; thread transformer_cache /
  transformer_cache_threshold through begin_load -> load_pipeline and report the
  engaged mode in status().
- models/inference.py + routes/inference.py: transformer_cache (off | fbcache) and
  transformer_cache_threshold request fields, engaged mode in the status response.
- hermetic tests for normalisation, the enable_cache / hook-fallback paths, threshold
  selection, and best-effort failure handling, plus route threading + validation.
- scripts/fbcache_flux_probe.py: the Flux validation probe (latency / speedup / VRAM /
  LPIPS vs the compiled no-cache baseline).
2026-06-26 12:35:50 +00:00
..
.gitkeep fix: restore models directory files deleted during restructure 2026-02-02 19:36:30 +00:00
__init__.py Studio: make code comments and docstrings more succinct (#6029) 2026-06-08 23:07:28 -07:00
auth.py Studio: make code comments and docstrings more succinct (#6029) 2026-06-08 23:07:28 -07:00
data_recipe.py Studio: make code comments and docstrings more succinct (#6029) 2026-06-08 23:07:28 -07:00
datasets.py Studio fix recipe dataset preview (#6031) 2026-06-09 14:02:00 +02:00
export.py Studio: free chat model VRAM at training start only when the GPU is tight (#6243) 2026-06-18 09:04:01 -07:00
inference.py Studio diffusion (Phase 12): First-Block-Cache step caching for many-step DiT 2026-06-26 12:35:50 +00:00
mcp_servers.py studio: show MCP "Import config" on the add-server form (#6030) 2026-06-11 16:17:22 +01:00
models.py transparent image rail; hide fine-tuned shortcut; custom folders filtered to diffusion GGUFs 2026-06-24 16:00:17 -03:00
providers.py Studio: Add custom provider option to Connections (#6112) 2026-06-12 13:09:35 +02:00
responses.py Studio: make code comments and docstrings more succinct (#6029) 2026-06-08 23:07:28 -07:00
training.py Studio: shareable per-checkpoint preview links (#6486) 2026-06-24 06:31:53 -07:00
users.py Studio: make code comments and docstrings more succinct (#6029) 2026-06-08 23:07:28 -07:00