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Composable sampling functions for diffusion models

Project description

Skrample 0.4.1

Composable sampling functions for diffusion models

Status

Vertical slice, overtaking most diffusers features in quickdif

Feature Flags

  • beta-schedule -> scipy : For the Beta() schedule modifier
  • brownian-noise -> torchsde : For the Brownian() noise generator
  • cdf-schedule -> scipy : For the SigmoidCDF() schedule
  • diffusers-wrapper -> torch : For the diffusers integration module
  • pytorch -> torch : For the pytorch module
    • pytorch.noise : Custom generators
  • all : All of the above
  • dev : For running tests/

Samplers

  • Euler
  • DPM
    • 1st order, 2nd order, 3rd order
    • SDE
  • Adams/IPNDM
  • UniP & UniPC
    • N order, limited to 9 for stability
    • Custom solver via other SkrampleSampler types
  • SPC
    • Basic fully customizable midpoint corrector

Schedules

  • Linear
  • Scaled
    • uniform flag, AKA "trailing" in diffusers
  • SigmaCDF
  • ZSNR

Schedule modifiers

  • Karras
  • Exponential
  • FlowShift
  • Beta
  • Hyper

Predictors

  • Epsilon
  • Velocity / vpred
  • Flow

Noise generators

  • Random
  • Brownian
  • Offset
  • Pyramid

Integrations

Diffusers

  • Compatibility for pipelines
    • SD1
    • SDXL
    • SD3
    • Flux
    • Others?
  • Import from config
    • Sampler
    • Schedule
    • Predictor
  • Manage state
    • Steps
    • Higher order
    • Generators
    • Config as presented

Implementations

quickdif

My diffusers cli quickdif has full support for all major Skrample features, allowing extremely fine-grained customization.

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