The prefetch already scopes the file list (no packaged root singles, no
dtype-variant twins, no ONNX/Flax exports), but from_pretrained was then
called with the hub id, and its own snapshot sweep re-downloaded the
skipped files anyway: 24 GB per FLUX.1 repo and 65 GB on FLUX.2-dev, as
found in the blob cache. Return the snapshot dir from the prefetch (keyed
on the pipeline manifest) and hand it to every pipeline-assembly
from_pretrained site; any prefetch failure keeps the hub id and the old
behavior.
- Free reserved VRAM in the diffusion load worker's failure path: a load-time OOM
never commits _state and the next load's _unload_locked early-returns, so nothing
else reclaimed the half-built pipeline's memory
- Use a monotonic clock for the denoise ETA rate
- Sync _GENERATION_DEFAULTS with the UI table: kontext, flux.2-dev, sdxl-turbo and
SDXL base rows so /v1/images/generations stops falling back to 9 steps / CFG 0
- 400 (not sanitized 500) when /v1/images/generations hits an edit-only model
- Fail fast on pre-Ampere CUDA in the DiT trainer instead of dying in model load
- Run the trainer trust gate in the diffusion training route before freeing GPU
residents so an untrusted base cannot tear down loaded chat/Images models
- Protect native sd.cpp companion VAE/text-encoder repos from cache deletion while
a load is downloading them
- Exempt the task-scoped Images picker from the chat-only GGUF/MLX format gate so
local diffusers pipelines stay selectable on no-GPU hosts
The wheel-only pip install for an optional attention kernel ran inside
load_pipeline under _lock and _generate_lock, so a slow or hanging install
blocked unload and cancellation for up to the 600s timeout. Resolve and install
the kernel before taking the locks (only an explicit backend ever pulls a
package, and its resolution ignores the speed tier); the in-lock apply call is
then a fast no-op. Also decode and log pip's stderr on a failed install so the
fallback to native is diagnosable instead of showing only the exit code.
The raw speed_mode string was forwarded to _enable_fp16_accumulation, so a
case-variant like MAX failed the speed_mode != SPEED_MAX check and wrongly
disabled fp16 accumulation on float16 pipelines. Forward the normalized mode
and cover the case-insensitive path in the test.
Measured on the fresh linux x64 prebuilt (z-image Q8_0, sd-cli, 192 CPU
threads, 512x512, 9 steps, steady state): sampling 56.1s vs 51.3s (about
9 percent faster), VAE decode unchanged, peak RSS identical. The sd.cpp
engine only serves the no-GPU tier, so the default profile now matches
max: --diffusion-fa plus --diffusion-conv-direct.
An unset transformer_quant used to mean off (run the GGUF as-is), so the
hardware ladder only engaged when auto was explicitly chosen and the panel
showed Off as the default. Unset (or auto) now hands the decision to the
ladder: a dense-capable GPU gets at least int8, data-center silicon fp8,
falling back to the GGUF when the device, VRAM, family deny table or disk
cannot take it. An explicit none/off pins GGUF-as-is and is now
expressible in the API (previously only omission meant off, so pinned-off
and unset were indistinguishable); an explicit scheme pins that scheme.
The dense candidate also gains a free-disk gate: with auto as the default
the bf16 base download (up to ~40 GB) must never wedge a nearly-full
model-cache disk, so the candidate is dropped (GGUF build kept) when free
space cannot hold it plus a 10 GiB margin. Unprobeable disk passes.
Frontend: the Dtype select defaults to Auto (fastest for GPU), keeps Off
as an explicit choice, and sends none through instead of omitting it.
Suite: 622 diffusion tests green (default-load test rewritten to the new
contract, explicit-off short-circuit covered), CI-sim green.
resolve_dense_quant_candidate now passes fam.name to
select_transformer_quant_scheme so the policy's proposed scheme honors the
family deny table (qwen-image lands on int8 instead of proposing fp8 that
the execution path would refuse). Test stub updated for the new keyword.
