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SDXL-Lightning fix

pull/101/head
tin2tin 9 months ago committed by GitHub
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1 changed files with 38 additions and 35 deletions
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  1. 65
      __init__.py

65
__init__.py
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@ -1143,7 +1143,7 @@ class GeneratorAddonPreferences(AddonPreferences):
"Stable Diffusion XL 1.0 (1024x1024)", "Stable Diffusion XL 1.0 (1024x1024)",
"stabilityai/stable-diffusion-xl-base-1.0", "stabilityai/stable-diffusion-xl-base-1.0",
), ),
("ByteDance/SDXL-Lightning", "SDXL-Lightning 2 Step (1024 x 1024)", "ByteDance/SDXL-Lightning"), ("ByteDance/SDXL-Lightning", "SDXL-Lightning (1024 x 1024)", "ByteDance/SDXL-Lightning"),
# ("stabilityai/stable-cascade", "Stable Cascade (1024 x 1024)", "stabilityai/stable-cascade"), # ("stabilityai/stable-cascade", "Stable Cascade (1024 x 1024)", "stabilityai/stable-cascade"),
# ("thibaud/sdxl_dpo_turbo", "SDXL DPO TURBO (1024x1024)", "thibaud/sdxl_dpo_turbo"), # ("thibaud/sdxl_dpo_turbo", "SDXL DPO TURBO (1024x1024)", "thibaud/sdxl_dpo_turbo"),
# ( # (
@ -1695,7 +1695,7 @@ class SEQUENCER_PT_pallaidium_panel(Panel): # UI
"svd_decode_chunk_size", "svd_decode_chunk_size",
text="Decode Frames", text="Decode Frames",
) )
if bpy.context.scene.sequence_editor is not None and image_model_card != "diffusers/controlnet-canny-sdxl-1.0-small" and image_model_card != "ByteDance/SDXL-Lightning": if bpy.context.scene.sequence_editor is not None and image_model_card != "diffusers/controlnet-canny-sdxl-1.0-small":
if len(bpy.context.scene.sequence_editor.sequences) > 0: if len(bpy.context.scene.sequence_editor.sequences) > 0:
if input == "input_strips" and type == "image": if input == "input_strips" and type == "image":
col.prop_search( col.prop_search(
@ -1820,9 +1820,6 @@ class SEQUENCER_PT_pallaidium_panel(Panel): # UI
context.scene, "movie_num_inference_steps", text="Quality Steps" context.scene, "movie_num_inference_steps", text="Quality Steps"
) )
else:
if type == "image" and image_model_card == "ByteDance/SDXL-Lightning":
pass
else: else:
col.prop( col.prop(
context.scene, "movie_num_inference_steps", text="Quality Steps" context.scene, "movie_num_inference_steps", text="Quality Steps"
@ -1839,9 +1836,6 @@ class SEQUENCER_PT_pallaidium_panel(Panel): # UI
scene.use_lcm and not ( scene.use_lcm and not (
type == "image" type == "image"
and image_model_card == "Lykon/dreamshaper-8" and image_model_card == "Lykon/dreamshaper-8"
) and not (
type == "image"
and image_model_card == image_model_card == "ByteDance/SDXL-Lightning"
) )
): ):
pass pass
@ -3183,7 +3177,6 @@ class SEQUENCER_OT_generate_image(Operator):
and not image_model_card == "monster-labs/control_v1p_sdxl_qrcode_monster" and not image_model_card == "monster-labs/control_v1p_sdxl_qrcode_monster"
and not image_model_card == "Salesforce/blipdiffusion" and not image_model_card == "Salesforce/blipdiffusion"
and not image_model_card == "Lykon/dreamshaper-8" and not image_model_card == "Lykon/dreamshaper-8"
and not image_model_card == "ByteDance/SDXL-Lightning"
) )
do_convert = ( do_convert = (
(scene.image_path or scene.movie_path) (scene.image_path or scene.movie_path)
@ -3193,7 +3186,6 @@ class SEQUENCER_OT_generate_image(Operator):
and not image_model_card == "h94/IP-Adapter" and not image_model_card == "h94/IP-Adapter"
and not image_model_card == "monster-labs/control_v1p_sdxl_qrcode_monster" and not image_model_card == "monster-labs/control_v1p_sdxl_qrcode_monster"
and not image_model_card == "Salesforce/blipdiffusion" and not image_model_card == "Salesforce/blipdiffusion"
and not image_model_card == "ByteDance/SDXL-Lightning"
and not do_inpaint and not do_inpaint
) )
do_refine = scene.refine_sd and not do_convert do_refine = scene.refine_sd and not do_convert
@ -3765,7 +3757,7 @@ class SEQUENCER_OT_generate_image(Operator):
base = "stabilityai/stable-diffusion-xl-base-1.0" base = "stabilityai/stable-diffusion-xl-base-1.0"
repo = "ByteDance/SDXL-Lightning" repo = "ByteDance/SDXL-Lightning"
ckpt = "sdxl_lightning_2step_lora.pth" # Use the correct ckpt for your step setting! ckpt = "sdxl_lightning_2step_lora.safetensors" # Use the correct ckpt for your step setting!
# Load model. # Load model.
pipe = StableDiffusionXLPipeline.from_pretrained(base, torch_dtype=torch.float16, variant="fp16").to("cuda") pipe = StableDiffusionXLPipeline.from_pretrained(base, torch_dtype=torch.float16, variant="fp16").to("cuda")
@ -3776,21 +3768,44 @@ class SEQUENCER_OT_generate_image(Operator):
pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing") pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
elif image_model_card == "dataautogpt3/ProteusV0.3": elif image_model_card == "dataautogpt3/ProteusV0.3":
from diffusers import StableDiffusionXLPipeline, KDPM2AncestralDiscreteScheduler from diffusers import StableDiffusionXLPipeline
from diffusers import AutoencoderKL # from diffusers import AutoencoderKL
vae = AutoencoderKL.from_pretrained( # vae = AutoencoderKL.from_pretrained(
"madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16 # "madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16
) # )
pipe = StableDiffusionXLPipeline.from_pretrained( pipe = StableDiffusionXLPipeline.from_single_file(
"dataautogpt3/ProteusV0.3", "dataautogpt3/ProteusV0.3",
vae=vae, #vae=vae,
torch_dtype=torch.float16, torch_dtype=torch.float16,
#variant="fp16", #variant="fp16",
) )
pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config) # from diffusers import DPMSolverMultistepScheduler
# pipe.scheduler = DPMSolverMultistepScheduler.from_config(
# pipe.scheduler.config
# )
if low_vram():
pipe.enable_model_cpu_offload()
else:
pipe.to(gfx_device) pipe.to(gfx_device)
# # Load VAE component
# vae = AutoencoderKL.from_pretrained(
# "madebyollin/sdxl-vae-fp16-fix",
# torch_dtype=torch.float16
# )
# Configure the pipeline
#pipe = StableDiffusionXLPipeline.from_pretrained(
# pipe = AutoPipelineForText2Image.from_pretrained(
# "dataautogpt3/ProteusV0.2",
# #vae=vae,
# torch_dtype=torch.float16,
# local_files_only=local_files_only,
# )
#pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config)
elif image_model_card == "stabilityai/stable-cascade": elif image_model_card == "stabilityai/stable-cascade":
import torch import torch
from diffusers import StableCascadeDecoderPipeline, StableCascadePriorPipeline from diffusers import StableCascadeDecoderPipeline, StableCascadePriorPipeline
@ -4310,18 +4325,6 @@ class SEQUENCER_OT_generate_image(Operator):
).images[0] ).images[0]
decoder = None decoder = None
elif image_model_card == "dataautogpt3/ProteusV0.3":
image = pipe(
# prompt_embeds=prompt, # for compel - long prompts
prompt,
negative_prompt=negative_prompt,
num_inference_steps=image_num_inference_steps,
guidance_scale=image_num_guidance,
height=y,
width=x,
generator=generator,
).images[0]
# Inpaint # Inpaint
elif do_inpaint: elif do_inpaint:
print("Process: Inpaint") print("Process: Inpaint")

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