up

run_local_xl.py

@@ -17,7 +17,7 @@ api = HfApi()
 start_time = time.time()
 
 use_refiner = bool(int(sys.argv[1]))
-use_diffusers = True
+use_diffusers = False
 
 vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16, force_upcast=True)
 if use_diffusers:

run_local_xl_inpaint.py

@@ -42,15 +42,17 @@ if use_refiner:
     # refiner.enable_sequential_cpu_offload()
 
 prompt = "A majestic tiger sitting on a bench"
-steps = 100
+steps = 50
 seed = 3
+denoising_end = None
+
 seed_everything(seed)
 start_time = time.time()
-image = pipe(prompt=prompt, image=init_image, mask_image=mask_image, num_inference_steps=steps, denoising_end=0.8, strength=0.80, output_type="latent").images
+image = pipe(prompt=prompt, image=init_image, mask_image=mask_image, num_inference_steps=steps, denoising_end=denoising_end, strength=0.80, output_type="latent").images
 print(time.time() - start_time)
 
 if use_refiner:
-    image = refiner(prompt=prompt, image=image, mask_image=mask_image, num_inference_steps=steps, denoising_start=0.8).images[0]
+    image = refiner(prompt=prompt, image=image, mask_image=mask_image, num_inference_steps=steps, denoising_start=denoising_end).images[0]
 
 file_name = f"aaa_1"
 path = os.path.join(Path.home(), "images", "ediffi_sdxl", f"{file_name}.png")

run_xl_ediffi.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-from diffusers import DiffusionPipeline, EulerDiscreteScheduler, StableDiffusionPipeline, KDPM2DiscreteScheduler, StableDiffusionImg2ImgPipeline, HeunDiscreteScheduler, KDPM2AncestralDiscreteScheduler, DDIMScheduler
+from diffusers import DiffusionPipeline, EulerDiscreteScheduler, StableDiffusionPipeline, KDPM2DiscreteScheduler, StableDiffusionImg2ImgPipeline, HeunDiscreteScheduler, KDPM2AncestralDiscreteScheduler, DDIMScheduler, HeunDiscreteScheduler, DEISMultistepScheduler
 from diffusers import DiffusionPipeline
 import time
 from pytorch_lightning import seed_everything
@@ -21,11 +21,11 @@ start_time = time.time()
 model_id = "stabilityai/stable-diffusion-xl-base-0.9"
 model_id = "runwayml/stable-diffusion-v1-5"
 pipe_high_noise = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16, variant="fp16", use_safetensors=True, local_files_only=True)
-pipe_high_noise.scheduler = EulerDiscreteScheduler.from_config(pipe_high_noise.scheduler.config)
+pipe_high_noise.scheduler = DEISMultistepScheduler.from_config(pipe_high_noise.scheduler.config)
 pipe_high_noise.to("cuda")
 
 pipe_low_noise = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
-pipe_low_noise.scheduler = EulerDiscreteScheduler.from_config(pipe_low_noise.scheduler.config)
+pipe_low_noise.scheduler = DEISMultistepScheduler.from_config(pipe_low_noise.scheduler.config)
 pipe_low_noise.to("cuda")
 
 prompt = "A majestic lion jumping from a big stone at night"