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https://github.com/invoke-ai/InvokeAI
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Merge branch 'main' into model-manager-ui-30
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commit
d4931522d4
@ -67,7 +67,7 @@ title: Home
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implementation of Stable Diffusion, the open source text-to-image and
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image-to-image generator. It provides a streamlined process with various new
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features and options to aid the image generation process. It runs on Windows,
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Mac and Linux machines, and runs on GPU cards with as little as 4 GB or RAM.
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Mac and Linux machines, and runs on GPU cards with as little as 4 GB of RAM.
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**Quick links**: [<a href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>]
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[<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a
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@ -7,7 +7,7 @@ import einops
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from pydantic import BaseModel, Field, validator
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import torch
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from diffusers import ControlNetModel
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from diffusers import ControlNetModel, DPMSolverMultistepScheduler
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from diffusers.image_processor import VaeImageProcessor
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from diffusers.schedulers import SchedulerMixin as Scheduler
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@ -233,7 +233,17 @@ class TextToLatentsInvocation(BaseInvocation):
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h_symmetry_time_pct=None,#h_symmetry_time_pct,
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v_symmetry_time_pct=None#v_symmetry_time_pct,
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),
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).add_scheduler_args_if_applicable(scheduler, eta=0.0)#ddim_eta)
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)
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conditioning_data = conditioning_data.add_scheduler_args_if_applicable(
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scheduler,
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# for ddim scheduler
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eta=0.0, #ddim_eta
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# for ancestral and sde schedulers
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generator=torch.Generator(device=uc.device).manual_seed(0),
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)
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return conditioning_data
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def create_pipeline(self, unet, scheduler) -> StableDiffusionGeneratorPipeline:
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@ -22,6 +22,10 @@ SAMPLER_CHOICES = [
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"dpmpp_2s_k",
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"dpmpp_2m",
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"dpmpp_2m_k",
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"dpmpp_2m_sde",
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"dpmpp_2m_sde_k",
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"dpmpp_sde",
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"dpmpp_sde_k",
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"unipc",
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]
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@ -1,7 +1,7 @@
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from diffusers import DDIMScheduler, DPMSolverMultistepScheduler, KDPM2DiscreteScheduler, \
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KDPM2AncestralDiscreteScheduler, EulerDiscreteScheduler, EulerAncestralDiscreteScheduler, \
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HeunDiscreteScheduler, LMSDiscreteScheduler, PNDMScheduler, UniPCMultistepScheduler, \
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DPMSolverSinglestepScheduler, DEISMultistepScheduler, DDPMScheduler
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DPMSolverSinglestepScheduler, DEISMultistepScheduler, DDPMScheduler, DPMSolverSDEScheduler
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SCHEDULER_MAP = dict(
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ddim=(DDIMScheduler, dict()),
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@ -21,5 +21,9 @@ SCHEDULER_MAP = dict(
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dpmpp_2s_k=(DPMSolverSinglestepScheduler, dict(use_karras_sigmas=True)),
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dpmpp_2m=(DPMSolverMultistepScheduler, dict(use_karras_sigmas=False)),
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dpmpp_2m_k=(DPMSolverMultistepScheduler, dict(use_karras_sigmas=True)),
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dpmpp_2m_sde=(DPMSolverMultistepScheduler, dict(use_karras_sigmas=False, algorithm_type='sde-dpmsolver++')),
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dpmpp_2m_sde_k=(DPMSolverMultistepScheduler, dict(use_karras_sigmas=True, algorithm_type='sde-dpmsolver++')),
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dpmpp_sde=(DPMSolverSDEScheduler, dict(use_karras_sigmas=False, noise_sampler_seed=0)),
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dpmpp_sde_k=(DPMSolverSDEScheduler, dict(use_karras_sigmas=True, noise_sampler_seed=0)),
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unipc=(UniPCMultistepScheduler, dict(cpu_only=True))
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)
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@ -20,6 +20,10 @@ SAMPLER_CHOICES = [
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"dpmpp_2s_k",
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"dpmpp_2m",
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"dpmpp_2m_k",
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"dpmpp_2m_sde",
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"dpmpp_2m_sde_k",
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"dpmpp_sde",
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"dpmpp_sde_k",
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"unipc",
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]
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@ -9,6 +9,8 @@ export const SCHEDULER_NAMES_AS_CONST = [
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'ddpm',
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'dpmpp_2s',
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'dpmpp_2m',
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'dpmpp_2m_sde',
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'dpmpp_sde',
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'heun',
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'kdpm_2',
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'lms',
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@ -17,6 +19,8 @@ export const SCHEDULER_NAMES_AS_CONST = [
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'euler_k',
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'dpmpp_2s_k',
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'dpmpp_2m_k',
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'dpmpp_2m_sde_k',
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'dpmpp_sde_k',
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'heun_k',
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'lms_k',
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'euler_a',
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@ -32,16 +36,20 @@ export const SCHEDULER_LABEL_MAP: Record<SchedulerParam, string> = {
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deis: 'DEIS',
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ddim: 'DDIM',
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ddpm: 'DDPM',
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dpmpp_sde: 'DPM++ SDE',
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dpmpp_2s: 'DPM++ 2S',
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dpmpp_2m: 'DPM++ 2M',
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dpmpp_2m_sde: 'DPM++ 2M SDE',
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heun: 'Heun',
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kdpm_2: 'KDPM 2',
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lms: 'LMS',
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pndm: 'PNDM',
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unipc: 'UniPC',
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euler_k: 'Euler Karras',
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dpmpp_sde_k: 'DPM++ SDE Karras',
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dpmpp_2s_k: 'DPM++ 2S Karras',
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dpmpp_2m_k: 'DPM++ 2M Karras',
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dpmpp_2m_sde_k: 'DPM++ 2M SDE Karras',
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heun_k: 'Heun Karras',
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lms_k: 'LMS Karras',
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euler_a: 'Euler Ancestral',
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@ -45,7 +45,7 @@ export type InpaintInvocation = {
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/**
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* The scheduler to use
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*/
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scheduler?: 'ddim' | 'ddpm' | 'deis' | 'lms' | 'lms_k' | 'pndm' | 'heun' | 'heun_k' | 'euler' | 'euler_k' | 'euler_a' | 'kdpm_2' | 'kdpm_2_a' | 'dpmpp_2s' | 'dpmpp_2s_k' | 'dpmpp_2m' | 'dpmpp_2m_k' | 'unipc';
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scheduler?: 'ddim' | 'ddpm' | 'deis' | 'lms' | 'lms_k' | 'pndm' | 'heun' | 'heun_k' | 'euler' | 'euler_k' | 'euler_a' | 'kdpm_2' | 'kdpm_2_a' | 'dpmpp_2s' | 'dpmpp_2s_k' | 'dpmpp_2m' | 'dpmpp_2m_k' | 'dpmpp_2m_sde' | 'dpmpp_2m_sde_k' | 'dpmpp_sde' | 'dpmpp_sde_k' | 'unipc';
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/**
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* The model to use (currently ignored)
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*/
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@ -43,7 +43,7 @@ export type LatentsToLatentsInvocation = {
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/**
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* The scheduler to use
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*/
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scheduler?: 'ddim' | 'ddpm' | 'deis' | 'lms' | 'lms_k' | 'pndm' | 'heun' | 'heun_k' | 'euler' | 'euler_k' | 'euler_a' | 'kdpm_2' | 'kdpm_2_a' | 'dpmpp_2s' | 'dpmpp_2s_k' | 'dpmpp_2m' | 'dpmpp_2m_k' | 'unipc';
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scheduler?: 'ddim' | 'ddpm' | 'deis' | 'lms' | 'lms_k' | 'pndm' | 'heun' | 'heun_k' | 'euler' | 'euler_k' | 'euler_a' | 'kdpm_2' | 'kdpm_2_a' | 'dpmpp_2s' | 'dpmpp_2s_k' | 'dpmpp_2m' | 'dpmpp_2m_k' | 'dpmpp_2m_sde' | 'dpmpp_2m_sde_k' | 'dpmpp_sde' | 'dpmpp_sde_k' | 'unipc';
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/**
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* UNet submodel
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*/
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@ -43,7 +43,7 @@ export type TextToLatentsInvocation = {
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/**
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* The scheduler to use
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*/
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scheduler?: 'ddim' | 'ddpm' | 'deis' | 'lms' | 'lms_k' | 'pndm' | 'heun' | 'heun_k' | 'euler' | 'euler_k' | 'euler_a' | 'kdpm_2' | 'kdpm_2_a' | 'dpmpp_2s' | 'dpmpp_2s_k' | 'dpmpp_2m' | 'dpmpp_2m_k' | 'unipc';
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scheduler?: 'ddim' | 'ddpm' | 'deis' | 'lms' | 'lms_k' | 'pndm' | 'heun' | 'heun_k' | 'euler' | 'euler_k' | 'euler_a' | 'kdpm_2' | 'kdpm_2_a' | 'dpmpp_2s' | 'dpmpp_2s_k' | 'dpmpp_2m' | 'dpmpp_2m_k' | 'dpmpp_2m_sde' | 'dpmpp_2m_sde_k' | 'dpmpp_sde' | 'dpmpp_sde_k' | 'unipc';
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/**
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* UNet submodel
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*/
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