up

run_local.py

@@ -1,18 +1,30 @@
 #!/usr/bin/env python3
-from diffusers import DiffusionPipeline
+from diffusers import StableDiffusionPipeline, DPMSolverSinglestepScheduler, DPMSolverMultistepScheduler, DEISMultistepScheduler, HeunDiscreteScheduler
+import time
+from huggingface_hub import HfApi
 import torch
-import os
-
 import sys
 
-local_path = sys.argv[1]
-local_path = os.path.abspath(local_path)
-
-prompts = ["astronaut on mars", "Barack Obama smiling with a big grin"]
+path = sys.argv[1]
 
-pipe = DiffusionPipeline.from_pretrained(local_path, torch_dtype=torch.float16)
+api = HfApi()
+start_time = time.time()
+pipe = StableDiffusionPipeline.from_pretrained(path, torch_dtype=torch.float16)
+pipe.scheduler = HeunDiscreteScheduler.from_config(pipe.scheduler.config)
 pipe = pipe.to("cuda")
 
-for prompt in prompts:
-    image = pipe(prompt).images[0]
-    image.save(f"/home/patrick_huggingface_co/images/a_{'_'.join(prompt.split())}.png")
+prompt = "a highly realistic photo of green turtle"
+generator = torch.Generator(device="cuda").manual_seed(0)
+image = pipe(prompt, generator=generator, num_inference_steps=25).images[0]
+print("Time", time.time() - start_time)
+
+path = "/home/patrick_huggingface_co/images/aa.png"
+image.save(path)
+
+api.upload_file(
+    path_or_fileobj=path,
+    path_in_repo=path.split("/")[-1],
+    repo_id="patrickvonplaten/images",
+    repo_type="dataset",
+)
+print("https://huggingface.co/datasets/patrickvonplaten/images/blob/main/aa.png")