add local run script

run_k_diffusion.py

@@ -0,0 +1,38 @@
+#!/usr/bin/env python3
+#from diffusers import DiffusionPipeline, StableDiffusionPipeline, KDPM2DiscreteScheduler, KDPM2AncestralDiscreteScheduler, HeunDiscreteScheduler
+from diffusers import DiffusionPipeline, StableDiffusionPipeline, HeunDiscreteScheduler
+import torch
+import os
+
+seed = 33
+inference_steps = 25
+
+old_pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", custom_pipeline="sd_text2img_k_diffusion")
+old_pipe = old_pipe.to("cuda")
+
+for prompt in ["astronaut riding horse", "whale falling from sky", "magical forest", "highly photorealistic picture of johnny depp"]:
+    # for sampler in ["sample_dpm_2_ancestral", "sample_dpm_2", "sample_heun"]:
+#    for sampler in ["heun", "sample_dpm_2_ancestral", "sample_dpm_2"]:
+    for sampler in ["sample_heun"]:
+        old_pipe.set_sampler(sampler)
+        torch.manual_seed(0)
+        image = old_pipe(prompt, num_inference_steps=inference_steps).images[0]
+        folder = f"a_{'_'.join(prompt.split())}"
+        os.makedirs(f"/home/patrick_huggingface_co/images/{folder}", exist_ok=True)
+        image.save(f"/home/patrick_huggingface_co/images/{folder}/{sampler}.png")
+
+        pipe = StableDiffusionPipeline(**old_pipe.components)
+        pipe = pipe.to("cuda")
+
+#        if sampler == "sample_dpm_2":
+#            pipe.scheduler = KDPM2DiscreteScheduler.from_config(pipe.scheduler.config)
+#        elif sampler == "sample_dpm_2_ancestral":
+#            pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config)
+        if sampler == "sample_heun":
+            pipe.scheduler = HeunDiscreteScheduler.from_config(pipe.scheduler.config)
+
+        torch.manual_seed(0)
+        image = pipe(prompt, num_inference_steps=inference_steps).images[0]
+
+        image.save(f"/home/patrick_huggingface_co/images/{folder}/hf_{sampler}.png")
+    break

run_local.py

@@ -0,0 +1,18 @@
+#!/usr/bin/env python3
+from diffusers import DiffusionPipeline
+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"]
+
+pipe = DiffusionPipeline.from_pretrained(local_path, torch_dtype=torch.float16)
+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")