updated code with xformers for faster inf

app.py

@@ -12,9 +12,9 @@ from diffusers import StableDiffusionInstructPix2PixPipeline, EulerAncestralDisc
 model_id = "timbrooks/instruct-pix2pix"
 pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16, revision="fp16") #, safety_checker=None)
 pipe.to("cuda")
-pipe.enable_attention_slicing()
-
-counter = 0
+#pipe.enable_attention_slicing()
+pipe.enable_xformers_memory_efficient_attention()
+pipe.unet.to(memory_format=torch.channels_last)
 
 
 help_text = """ Some notes from the official [instruct-pix2pix](https://huggingface.co/spaces/timbrooks/instruct-pix2pix) Space by the authors and from the official [Diffusers docs](https://huggingface.co/docs/diffusers/main/en/api/pipelines/stable_diffusion/pix2pix) -
@@ -71,8 +71,8 @@ def chat(image_in, in_steps, in_guidance_scale, in_img_guidance_scale, image_hid
     else:
       seed = random.randint(0, 1000000)
       img_name = f"./edited_image_{seed}.png"
-      #Resizing the image
-      basewidth = 512
+      #Resizing the image - 512 or 300 pixels
+      basewidth = 300
       wpercent = (basewidth/float(image_in.size[0]))
       hsize = int((float(image_in.size[1])*float(wpercent)))
       image_in = image_in.resize((basewidth,hsize), Image.Resampling.LANCZOS)