up

.gitignore

@@ -1,2 +1 @@
-gradio_cached_examples
 flagged

app.py

@@ -2,20 +2,29 @@ import gradio as gr
 import torch
 from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler
 
+use_cuda = torch.cuda.is_available()
+
+if use_cuda:
+  dtype = torch.float16
+else:
+  dtype = torch.float32
+
 controlnet = ControlNetModel.from_pretrained(
     "williamberman/controlnet-fill50k", 
-    torch_dtype=torch.float16
+    torch_dtype=dtype
 )
 
 pipe = StableDiffusionControlNetPipeline.from_pretrained(
     "runwayml/stable-diffusion-v1-5", 
     controlnet=controlnet,
     safety_checker=None,
-    torch_dtype=torch.float16, 
+    torch_dtype=dtype
 )
 pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
-pipe.enable_xformers_memory_efficient_attention()
-pipe.enable_model_cpu_offload()
+
+if use_cuda:
+  pipe.enable_xformers_memory_efficient_attention()
+  pipe.enable_model_cpu_offload()
 
 def inference(prompt, image, seed=-1):
     if seed == -1:

gradio_cached_examples/17/log.csv

@@ -0,0 +1,7 @@
+output,flag,username,timestamp
+output/tmpmmt1sbea.png,,,2023-03-13 05:32:01.492640
+output/tmp51idisi8.png,,,2023-03-13 05:32:05.214562
+output/tmprdh4k7n4.png,,,2023-03-13 05:32:08.741490
+output/tmpw7cik_mi.png,,,2023-03-13 05:32:12.270382
+output/tmpsnz6ewc7.png,,,2023-03-13 05:32:15.736019
+output/tmp_smsd0eq.png,,,2023-03-13 05:32:19.265256