Update app.py

app.py

@@ -9,20 +9,18 @@ from huggingface_hub import hf_hub_download
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
 torch.cuda.max_memory_allocated(device=device)
 torch.cuda.empty_cache()
-#torch.cuda.max_memory_allocated(device=device)
 pipe = DiffusionPipeline.from_pretrained("circulus/canvers-fusionXL-v1", torch_dtype=torch.float16).to(device)
 pipe.enable_xformers_memory_efficient_attention()
 torch.cuda.empty_cache()
 
-#torch.cuda.max_memory_allocated(device=device)
 refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True, torch_dtype=torch.float16, variant="fp16").to(device)
 refiner.enable_xformers_memory_efficient_attention()
 torch.cuda.empty_cache()
 
 
 def genie (Prompt, negative_prompt, height, width, scale, steps, seed):
+    torch.cuda.empty_cache()
     generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
-    #generator=np.random.seed(0)
     int_image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale, output_type="latent").images
     image = refiner(Prompt, negative_prompt=negative_prompt, image=int_image, denoising_start=.99).images[0]
     torch.cuda.empty_cache()
@@ -31,8 +29,8 @@ def genie (Prompt, negative_prompt, height, width, scale, steps, seed):
     
 gr.Interface(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'), 
                                gr.Textbox(label='What you Do Not want the AI to generate. 77 Token Limit'),
-                               gr.Slider(512, 1536, 1024, step=128, label='Height'),
-                               gr.Slider(512, 1536, 1024, step=128, label='Width'),
+                               gr.Slider(512, 1280, 1024, step=128, label='Height'),
+                               gr.Slider(512, 1280, 1024, step=128, label='Width'),
                                gr.Slider(.5, maximum=15, value=7, step=.25, label='Guidance Scale'), 
                                gr.Slider(10, maximum=50, value=25, step=5, label='Number of Prior Iterations'),
                                gr.Slider(minimum=0, step=1, maximum=9999999999999999, randomize=True, label='Seed: 0 is Random')],