DOGMA AllSamplerSelect v1.0.11

What this actually is

DOGMAAllSamplerSelectV111 spits out a SAMPLER object. That's it. The interesting part is what's in its dropdown, because it isn't just ComfyUI's stock list.

At schema-build time the node calls a small helper that walks three sources and merges them: comfy.samplers.SAMPLER_NAMES plus KSampler.SAMPLERS (your normal euler/heun/dpmpp crowd), then the six DOGMA samplers from this pack prefixed DOGMA / , then - if RES4LYF happens to be installed - every solver in it prefixed RES4LYF / . So a single node can hand SamplerCustomAdvanced anything from euler to DOGMA_klein_distilled_BALANCED to RES4LYF / beta57.

Why you'd want that: the DOGMA workflow this pack was carved out of switches samplers per phase (their own release notes describe phase 2 at 8 steps Euler/simple and phase 3 at 4 steps Euler/simple, all over a Lying Sigma curve). Wiring three separate KSamplerSelect nodes and swapping links by hand is exactly the kind of fiddling this saves.

The four inputs, honestly

Three of them don't matter most of the time, and it's worth knowing which:

• sampler_name - the dropdown, default euler. This is the one you set.
• res_eta (default 0.3, range -100 to 100), res_bongmath (default true), seed (default 1976) - these are only consumed on the RES4LYF / path. The node forwards them straight into RES4LYF's ClownSampler_Beta as eta, bongmath and seed. That bongmath toggle is RES4LYF's own vocabulary, not something DOGMA invented - if you've ever loaded someone's shared workflow and seen bongmath in the sampler settings, that's where it comes from. On plain ComfyUI samplers and on the DOGMA ones, these three are ignored.
• The seed here is not the image seed. Don't try to use it as a variation control; it's the sampler's internal noise seed for the RES4LYF path.

Output is one thing: sampler, a SAMPLER. Wire it into SamplerCustomAdvanced (paired with any SIGMAS source, including hand-drawn curves) or into anything else that takes a sampler object.

Dispatch, and the error you'll eventually hit

The select function checks membership against a freshly built catalogue before doing anything: RES4LYF names go to ClownSampler_Beta.execute, DOGMA / x goes to the pack's DOGMASamplerSelect().get_sampler(x), everything else to comfy.samplers.sampler_object(name).

That check is where the one predictable failure lives:

ValueError: Sampler no longer installed: RES4LYF / beta57

You get this in two situations. First, someone's workflow JSON (or your own graph, saved on another machine) carries a RES4LYF name and you don't have RES4LYF. Second, you uninstalled a pack mid-project. Fix is either install the pack or re-pick the sampler - the graph will not silently fall back.

Also worth knowing: importing this pack registers the six DOGMA samplers into ComfyUI's global sampler list, so DOGMA_klein_distilled_DETAIL and friends show up in ordinary KSampler, KSampler Advanced and KSamplerSelect dropdowns after a restart. This node is for when you want the name as a soft-switchable value, not because the DOGMA samplers are otherwise unreachable.

Install

Manager → search DOGMA Nodes (publisher axior, registry name comfyui-dogma-nodes). Or:

cd ComfyUI/custom_nodes
git clone https://github.com/axior/ComfyUI-DOGMA-Nodes
# restart ComfyUI afterwards

The only Python dependency the shipped requirements.txt declares is scipy>=1.10; the node's own README claim of "no extra Python dependencies" is stale on that point. Nothing to download into models/. RES4LYF is optional and only widens the dropdown.

Should you care

If you're on plain KSampler with one sampler, no - use KSamplerSelect and move on. This earns its place in multi-phase graphs where sampler choice per phase is a thing you tune, or when you're mixing RES4LYF solvers into a DOGMA mask-and-crop pipeline and got tired of four dropdowns.

One caveat that applies to the whole pack: DOGMA Nodes has essentially no community footprint - it doesn't appear in the r/comfyui / r/StableDiffusion discussion corpus at all. The documentation is the author's changelogs and READMEs, and he states plainly that validation is CPU-only with model calls mocked. The DOGMA samplers themselves are described by their own README as experimental ODE samplers tuned around FLUX.2 Klein 9B (three for the 4–6 step distilled model, three for the 20–50 step base model, no LoRA required). Treat the sampler menu as a convenience wrapper around other people's samplers and you'll be fine.