up

run_local.py

@@ -1,61 +1,33 @@
 #!/usr/bin/env python3
-from diffusers import StableDiffusionPipeline, KDPM2DiscreteScheduler, StableDiffusionImg2ImgPipeline, HeunDiscreteScheduler, KDPM2AncestralDiscreteScheduler, DDIMScheduler
+from diffusers import (
+    SASolverScheduler,
+    StableDiffusionPipeline,
+    KDPM2DiscreteScheduler,
+    StableDiffusionImg2ImgPipeline,
+    HeunDiscreteScheduler,
+    KDPM2AncestralDiscreteScheduler,
+    DDIMScheduler,
+)
 import time
-import os
-from huggingface_hub import HfApi
-# from compel import Compel
 import torch
 import sys
 from pathlib import Path
-import requests
-from PIL import Image
-from io import BytesIO
 
-path = sys.argv[1]
-# path = "ptx0/pseudo-journey-v2"
+# path = sys.argv[1]
+path = "runwayml/stable-diffusion-v1-5"
+device = "mps"
 
-api = HfApi()
-start_time = time.time()
 pipe = StableDiffusionPipeline.from_pretrained(path, torch_dtype=torch.float16)
-pipe.enable_xformers_memory_efficient_attention()
-
-# pipe.unet = torch.compile(pipe.unet)
-
-# pipe = StableDiffusionImg2ImgPipeline.from_pretrained(path, torch_dtype=torch.float16, safety_checker=None)
-
-# compel = Compel(tokenizer=pipe.tokenizer, text_encoder=pipe.text_encoder)
-
-
-pipe = pipe.to("cuda")
+pipe.scheduler = SASolverScheduler.from_config(pipe.scheduler.config)
+pipe.to(device)
 
 prompt = "A lion in galaxies, spirals, nebulae, stars, smoke, iridescent, intricate detail, octane render, 8k"
 
-# rompts = ["a cat playing with a ball++ in the forest", "a cat playing with a ball++ in the forest", "a cat playing with a ball-- in the forest"]
-
-# prompt_embeds = torch.cat([compel.build_conditioning_tensor(prompt) for prompt in prompts])
-
-# generator = [torch.Generator(device="cuda").manual_seed(0) for _ in range(prompt_embeds.shape[0])]
-#
-# url = "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg"
- 
-# response = requests.get(url)
-# image = Image.open(BytesIO(response.content)).convert("RGB")
-# image.thumbnail((768, 768))
-
-
-generator = torch.Generator(device="cpu").manual_seed(0)
-# images = pipe(prompt=prompt, image=image, generator=generator, num_images_per_prompt=4, num_inference_steps=25).images
-images = pipe(prompt=prompt, generator=generator, num_images_per_prompt=1, num_inference_steps=50).images
-
-for i, image in enumerate(images):
-    file_name = f"bb_1_{i}"
-    path = os.path.join(Path.home(), "images", f"{file_name}.png")
-    image.save(path)
+start_time = time.time()
+generator = torch.Generator(device=device).manual_seed(0)
+images = pipe(
+    prompt=prompt, generator=generator, num_images_per_prompt=1, num_inference_steps=30
+).images
+print(time.time() - start_time)
 
-    api.upload_file(
-        path_or_fileobj=path,
-        path_in_repo=path.split("/")[-1],
-        repo_id="patrickvonplaten/images",
-        repo_type="dataset",
-    )
-    print(f"https://huggingface.co/datasets/patrickvonplaten/images/blob/main/{file_name}.png")
+images[0].show()

run_local_sag.py

@@ -0,0 +1,34 @@
+#!/usr/bin/env python3
+from diffusers import (
+    StableDiffusionSAGPipeline,
+    StableDiffusionPipeline,
+    KDPM2DiscreteScheduler,
+    StableDiffusionImg2ImgPipeline,
+    HeunDiscreteScheduler,
+    KDPM2AncestralDiscreteScheduler,
+    DDIMScheduler,
+)
+import time
+import torch
+import sys
+from pathlib import Path
+
+# path = sys.argv[1]
+path = "runwayml/stable-diffusion-v1-5"
+device = "cpu"
+dtype = torch.float32
+
+pipe = StableDiffusionSAGPipeline.from_pretrained(path, torch_dtype=dtype)
+# pipe.scheduler = SASolverScheduler.from_config(pipe.scheduler.config)
+pipe.to(device)
+
+prompt = "A lion in galaxies, spirals, nebulae, stars, smoke, iridescent, intricate detail, octane render, 8k"
+
+start_time = time.time()
+generator = torch.Generator(device=device).manual_seed(0)
+images = pipe(
+    prompt=prompt, generator=generator, num_images_per_prompt=1, num_inference_steps=30
+).images
+print(time.time() - start_time)
+
+images[0].show()