up

app.py

@@ -15,8 +15,8 @@ pipeline.to(device)
 if USE_TORCH_COMPILE:
     pipeline.unet = torch.compile(pipeline.unet, mode="reduce-overhead", fullgraph=True)
     
-def generate(prompt_len: int, num_images_per_prompt: int = 1):
-    prompt = prompt_len * "a"
+def generate(num_images_per_prompt: int = 1):
+    prompt = 77 * "a"
     num_inference_steps = 40
     start_time = time.time()
     pipeline(prompt, num_images_per_prompt=num_images_per_prompt, num_inference_steps=num_inference_steps).images
@@ -35,19 +35,12 @@ with gr.Blocks(css="style.css") as demo:
         step=1,
         value=1,
     )
-    prompt_len = gr.Slider(
-        label="Prompt len",
-        minimum=1,
-        maximum=77,
-        step=20,
-        value=1,
-    )
     btn = gr.Button("Benchmark!").style(
         margin=False,
         rounded=(False, True, True, False),
         full_width=False,
     )
 
-    btn.click(fn=generate, inputs=[batch_size, prompt_len])
+    btn.click(fn=generate, inputs=[batch_size])
 
 demo.launch(share=True)