Delete app.py

app.py

@@ -1,54 +0,0 @@
-import gradio as gr
-import torch
-from baseline import run as run_baseline
-
-# print(torch.cuda.is_available())
-prompt_placeholder = "A painting of a dog eating hamburger."
-
-html = f"""<h1>LLM Diffusion"""
-
-
-def get_baseline_image(prompt, seed=0):
-    if prompt == "":
-        prompt = prompt_placeholder
-    
-    scheduler_key = "dpm_scheduler"
-    num_inference_steps = 20
-    
-    image_np = run_baseline(prompt, bg_seed=seed, scheduler_key=scheduler_key, num_inference_steps=num_inference_steps)
-    return [image_np]
-
-
-with gr.Blocks(title="LLM Diffusion") as iface:
-    gr.HTML(html)
-    with gr.Tab("Our LLM Diffusion"):
-        with gr.Row():
-            with gr.Column(scale=1):
-                prompt = gr.Textbox(lines=2, label="Prompt for the overall image", placeholder=prompt_placeholder)
-                generate_btn = gr.Button("Generate", elem_classes="btn")
-            with gr.Column(scale=1):
-                output = gr.Textbox(lines=8, label="Details from LLM")
-
-        with gr.Row():
-            gallery = gr.Gallery(
-                    label="Generated image", elem_id="gallery1", columns=[1], rows=[1], object_fit="contain", preview=True
-                )
-
-
-    with gr.Tab("Baseline: Stable Diffusion"):
-        with gr.Row():
-            with gr.Column(scale=1):
-                sd_prompt = gr.Textbox(lines=2, label="Prompt for baseline SD", placeholder=prompt_placeholder)
-                seed = gr.Slider(0, 10000, value=0, step=1, label="Seed")
-                generate_btn = gr.Button("Generate", elem_classes="btn")
-            # with gr.Column(scale=1):
-            #     output = gr.Image(shape=(512, 512), elem_classes="img", elem_id="img")
-            with gr.Column(scale=1):
-                gallery = gr.Gallery(
-                    label="Generated image", show_label=False, elem_id="gallery2", columns=[1], rows=[1], object_fit="contain", preview=True
-                )
-        generate_btn.click(fn=get_baseline_image, inputs=[sd_prompt, seed], outputs=gallery, api_name="baseline")
-
-
-
-iface.launch(share=True)