torch.cat was indented into the per-item loop, so with two or more
latents the first iteration replaced the list with a tensor and the
next iteration concatenated its dim-0 slices, destroying the batch
dimension. Concatenate once after the loop.
https: //claude.ai/code/session_014QWKWgKvMevcuvfCnsYoT2
Co-Authored-By: Claude <noreply@anthropic.com>
tile_width/tile_height and tile_col_overlap/tile_row_overlap were cross-assigned from p.height/p.width, transposing output geometry for every non-square tile size. Fixes#4902.
padding loops used insert(0) which shifts existing prompt/seed entries
to higher indices, so subsequent index lookups - including the caller's
own p.prompts[i]/p.seeds[i] reads on the same aliased lists - return
values belonging to a different image; append preserves existing
index-to-entry mapping and pads missing slots at the end
https://claude.ai/code/session_01UZT4ypkGQH5fzJ89dXPFYp
Drives txt2img/img2img with the full per-sampler scheduler-option matrix
(sigma method, prediction type, timestep spacing, beta schedule, solver
order, shift, low order, thresholding, dynamic shift, rescale betas), one
option at a time over a pinned baseline, and measures every case against
the default: applied, inert, marginal, rejected, or fallback. Detects
silent fallback via the infotext Scheduler class and annotates every saved
image with its full requested configuration. --sweep runs a reduced matrix
per sampler and emits an empirical capability report.
Sampler capability gates raised plain ValueError when schedulers_fallback is
disabled, so the API middleware and the gradio call wrapper printed a full
backtrace for an expected outcome. Add errors.ValidationError, raise it from
the gates, and report it message-only in errors.display; the UI error box and
the API error response already carry the message.
The ER-SDE FlowMatch presets carried only use_flow_sigmas, so the sigma
method selector could not drive karras/beta/exponential for the FlowMatch
variants. Add use_karras_sigmas/use_exponential_sigmas/use_beta_sigmas to
match the plain ER-SDE presets and the Euler/UniPC/Flash FlowMatch presets,
which use the same boolean-flag mechanism.
create_sampler restored the model default scheduler on a prediction-type
mismatch, on an unknown sampler config, and on any scheduler-constructor
exception regardless of schedulers_fallback; only SD_SAMPLER_DEBUG could turn
the prediction mismatch into an error. Raise like the other capability gates
when the fallback setting is disabled.
An unresolved sampler name substituted UniPC before any of those gates could
run; pass the requested name through instead, so it falls back to the model
default (or raises when fallback is disabled) and the infotext records
Default rather than the unresolved name. find_sampler now also resolves an
unspecified sampler to Default instead of UniPC, matching the platform
default used everywhere else.
In flow mode ER-SDE only ran karras/beta/exponential on the VP path and
silently dropped them, unlike FlowMatchEuler and DPM FlowMatch which
redistribute the shifted flow sigmas. Apply the same transform to the
flow sigmas in _setup_flow so the sigma method works in flow mode and
the ER-SDE FlowMatch variants gain karras/beta/exponential. Default flow
schedule is unchanged.
The sigma-method override silently fell back to the sampler's default
schedule when the selected method has no matching config key. Now warns and
uses the default schedule with schedulers_fallback enabled, or raises like
the other capability gates when it is disabled.
ERSDEScheduler now accepts use_karras_sigmas, use_exponential_sigmas,
use_beta_sigmas, and use_flow_sigmas, matching the other flow schedulers.
The VP path derives alpha/sigma/lambda from the k-diffusion sigma so the
karras/beta/exponential transforms can use fractional timesteps; the
default schedule is numerically unchanged. use_flow_sigmas triggers flow
mode and add_noise tolerates fractional timesteps.
Wire the new keys into the ER-SDE presets so the sigma method selector
drives them, and cover ER-SDE in the scheduler stability test.
schedulers_sigma is a hidden OptionInfo registration; the visible control is the sampler-accordion dropdown. Its choices still listed the k-diffusion set, including polyexponential (which the diffusers backend does not support) and omitting betas, lambdas, and flowmatch. Align the list with what sd_samplers_diffusers accepts and the dropdown offers. The list feeds warn-only validation, so this clears a dead value and spurious debug logs, not user-facing behavior.
img2img still defaulted sampler_name to UniPC after the txt2img default was switched to Default in 7fbac675f, so an img2img request that omits the sampler forced UniPC instead of keeping the model's own scheduler. The control endpoint already used Default; align img2img with both.
validate_sampler_name only matched the exact, case-sensitive name, so near-miss client names such as lowercase variants were rejected while an omitted name silently used the model scheduler via the Default sentinel. Fall back to find_sampler and return the canonical name so create_sampler applies the intended sampler; unknown names still return 404. Add an API test covering case-insensitive resolution and rejection of unknown names.
Claude
Vladimir Mandic
QualiaRain
Oleksandr Liutyi
CalamitousFelicitousness
Disty0