[Doc] diffusion: Document reference resizing, LoRA auto mode and image profiling

docs/cookbook/diffusion/MiniMax/MiniMax-H3.mdx

@@ -667,6 +667,23 @@ An image condition here is semantic reference material rather than a
 pixel-aligned first frame. Use the FL2VA tab when animating a screenshot from
 that exact starting composition.
 
+Set `reference_resize_mode` on the request to choose how reference images are
+resized before encoding:
+
+- `diffusers` (default) scales the short edge to 2048 pixels, including upscaling
+  small inputs. This preserves the original preprocessing behavior.
+- `max` only downsizes references whose short edge exceeds 2048 pixels.
+- `match` downsizes to the target canvas pixel area when needed, without
+  upscaling smaller references. Use this with the
+  [ModelTC Ref2VA Turbo LoRA](https://github.com/ModelTC/Minimax-H3-Turbo#note-on-reference-image-resizing),
+  whose training uses this policy.
+
+All modes scale without cropping, then round each dimension to the nearest
+multiple of 32. This rounding can slightly change the aspect ratio. The option
+affects Ref2VA image references, not FL2VA keyframes, video, or audio references.
+Changing it changes the conditioning input, so keep it fixed for quality and
+performance comparisons; the server does not infer it from the adapter name.
+
 ```bash Command
 curl -sS -X POST http://127.0.0.1:30010/v1/videos \
   -H "Content-Type: application/json" \

docs/docs/sglang-diffusion/api/cli.mdx

@@ -86,7 +86,7 @@ Use `sglang generate --help` and `sglang serve --help` for the full argument lis
 - `--lora-weight-name {FILE}`: select one adapter file from a repository that contains multiple LoRA revisions. The Hub download is filtered to that file plus JSON metadata, so unused weights are not downloaded.
 - `--lora-alpha {N}`: supply the training alpha when a single-file adapter omits both per-layer alpha tensors and `adapter_config.json`. Do not set it when the adapter already records alpha metadata.
 - PEFT `adapter_config.json` semantics are applied automatically for named adapter slots, RSLoRA, and per-layer `alpha_pattern`. Adapters that require unsupported auxiliary parameters or runtime behavior, such as DoRA, fail before weight injection instead of silently using ordinary LoRA math.
-- `--lora-merge-mode {auto|merge|dynamic}`: choose how LoRA is applied. `auto` statically merges regular weights and uses dynamic LoRA for FSDP-sharded weights to avoid full-gather peaks.
+- `--lora-merge-mode {auto|merge|dynamic}`: choose how LoRA is applied. `auto` normally merges regular weights, but keeps FSDP-sharded weights dynamic to avoid full-gather peaks. For a single adapter, it also stays dynamic when an estimate shows that merging would round away more than 50% of the update's norm. `merge` forces merging; `dynamic` applies the adapter at forward time.
 - `--num-gpus {N}`: number of GPUs to use
 - `--numa-node {N} [N ...]`: NUMA node for each GPU worker, the i-th value for the worker on local GPU i. When unset, each worker binds its CPUs and host memory to its GPU's NUMA node on multi-socket hosts, as srt does (CPUs only without `CAP_SYS_NICE`); set `SGLANG_AUTO_NUMA_BIND=0` to turn that off. Unbound workers on a two-socket host (e.g. GB200/GB300) can drift to the other socket, which slows host-bound steps and makes latency vary run to run.
 - `--performance-mode {manual|auto|speed|memory}` / `--mode`: preset for latency/throughput and memory defaults. `auto` is the default and dispatches residency from selected-GPU headroom and workload type: image DiTs stay resident above the 45 GiB threshold, while video DiT placement remains model-specific. It uses FSDP only for validated DiT-offload replacement paths. `speed` keeps `torch.compile` disabled unless a model-specific deployment config opts in after validation; pass `--enable-torch-compile true` to enable it explicitly. Use `manual` to keep performance-related server args under explicit user control. Explicit offload, FSDP, and parallelism flags take precedence in all modes.

docs/docs/sglang-diffusion/profiling.mdx

@@ -43,6 +43,32 @@ sglang generate \
 **Parameters:**
 - `--profile-all-stages`: Used with `--profile`, profile all pipeline stages instead of just denoising
 
+### Image API requests
+
+For an already running image server, enable profiling on an individual request.
+The JSON generations endpoint accepts the same controls with underscores:
+
+```bash
+curl -sS http://127.0.0.1:30000/v1/images/generations \
+  -H 'Content-Type: application/json' \
+  -d '{
+    "prompt": "A mountain lake at sunrise",
+    "seed": 0,
+    "profile": true,
+    "num_profiled_timesteps": 5,
+    "profile_all_stages": false
+  }'
+```
+
+For `/v1/images/edits`, pass these controls as multipart form fields alongside
+the image and prompt: `-F profile=true -F num_profiled_timesteps=5`.
+Add `-F profile_all_stages=true` to profile the full pipeline instead.
+
+Traces are written on the server, not returned as image-response attachments.
+Use `perf_dump_path` for a lightweight timing report instead of a profiler trace.
+Run latency benchmarks separately with profiling disabled, since collecting a
+trace adds overhead.
+
 ### Output Location
 
 By default, trace files are saved in the ./logs/ directory.