Spaces:
Running
Running
update ui
Browse files
app.py
CHANGED
@@ -5,9 +5,7 @@ os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
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import uuid
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import GPUtil
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import gradio as gr
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import psutil
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import spaces
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from videosys import CogVideoXConfig, CogVideoXPABConfig, VideoSysEngine
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@@ -30,33 +28,6 @@ def generate(engine, prompt, num_inference_steps=50, guidance_scale=6.0):
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return output_path
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def get_server_status():
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cpu_percent = psutil.cpu_percent()
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memory = psutil.virtual_memory()
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disk = psutil.disk_usage("/")
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gpus = GPUtil.getGPUs()
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gpu_info = []
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for gpu in gpus:
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gpu_info.append(
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{
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"id": gpu.id,
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"name": gpu.name,
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"load": f"{gpu.load*100:.1f}%",
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"memory_used": f"{gpu.memoryUsed}MB",
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"memory_total": f"{gpu.memoryTotal}MB",
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}
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)
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return {"cpu": f"{cpu_percent}%", "memory": f"{memory.percent}%", "disk": f"{disk.percent}%", "gpu": gpu_info}
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@spaces.GPU(duration=540)
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def generate_vanilla(model_name, prompt, num_inference_steps, guidance_scale, progress=gr.Progress(track_tqdm=True)):
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engine = load_model(model_name)
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video_path = generate(engine, prompt, num_inference_steps, guidance_scale)
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return video_path
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@spaces.GPU(duration=400)
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def generate_vs(
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model_name,
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@@ -75,33 +46,6 @@ def generate_vs(
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return video_path
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def get_server_status():
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cpu_percent = psutil.cpu_percent()
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memory = psutil.virtual_memory()
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disk = psutil.disk_usage("/")
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try:
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gpus = GPUtil.getGPUs()
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if gpus:
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gpu = gpus[0]
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gpu_memory = f"{gpu.memoryUsed}/{gpu.memoryTotal}MB ({gpu.memoryUtil*100:.1f}%)"
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else:
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gpu_memory = "No GPU found"
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except:
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gpu_memory = "GPU information unavailable"
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return {
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"cpu": f"{cpu_percent}%",
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"memory": f"{memory.percent}%",
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"disk": f"{disk.percent}%",
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"gpu_memory": gpu_memory,
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}
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def update_server_status():
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status = get_server_status()
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return (status["cpu"], status["memory"], status["disk"], status["gpu_memory"])
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css = """
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body {
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font-family: Arial, sans-serif;
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@@ -203,7 +147,7 @@ with gr.Blocks(css=css) as demo:
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with gr.Row():
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with gr.Column():
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prompt = gr.Textbox(label="Prompt (Less than 200 Words)", value="Sunset over the sea.", lines=
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with gr.Column():
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gr.Markdown("**Generation Parameters**<br>")
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@@ -212,44 +156,40 @@ with gr.Blocks(css=css) as demo:
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["THUDM/CogVideoX-2b", "THUDM/CogVideoX-5b"], label="Model Type", value="THUDM/CogVideoX-2b"
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)
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with gr.Row():
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num_inference_steps = gr.
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guidance_scale = gr.
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with gr.Row():
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pab_range = gr.
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label="
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)
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pab_threshold_start = gr.Number(label="PAB Start Timestep", value=850, info="Start from step 1000.")
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pab_threshold_end = gr.Number(label="PAB End Timestep", value=100, info="End at step 0.")
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with gr.Row():
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generate_button_vs = gr.Button("⚡️ Generate Video with VideoSys
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generate_button = gr.Button("🎬 Generate Video (Original)")
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with gr.Column(elem_classes="server-status"):
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gr.Markdown("#### Server Status")
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with gr.Row():
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cpu_status = gr.Textbox(label="CPU", scale=1)
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memory_status = gr.Textbox(label="Memory", scale=1)
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with gr.Row():
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disk_status = gr.Textbox(label="Disk", scale=1)
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gpu_status = gr.Textbox(label="GPU Memory", scale=1)
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with gr.Row():
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refresh_button = gr.Button("Refresh")
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with gr.Column():
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with gr.Row():
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video_output_vs = gr.Video(label="CogVideoX with VideoSys", width=720, height=480)
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with gr.Row():
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video_output = gr.Video(label="CogVideoX", width=720, height=480)
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generate_button.click(
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generate_vanilla,
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inputs=[model_name, prompt, num_inference_steps, guidance_scale],
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outputs=[video_output],
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concurrency_id="gen",
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concurrency_limit=1,
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)
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generate_button_vs.click(
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generate_vs,
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@@ -267,8 +207,6 @@ with gr.Blocks(css=css) as demo:
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concurrency_limit=1,
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)
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refresh_button.click(update_server_status, outputs=[cpu_status, memory_status, disk_status, gpu_status])
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demo.load(update_server_status, outputs=[cpu_status, memory_status, disk_status, gpu_status], every=1)
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if __name__ == "__main__":
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demo.queue(max_size=10, default_concurrency_limit=1)
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import uuid
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import gradio as gr
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import spaces
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from videosys import CogVideoXConfig, CogVideoXPABConfig, VideoSysEngine
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return output_path
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@spaces.GPU(duration=400)
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def generate_vs(
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model_name,
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return video_path
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css = """
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body {
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font-family: Arial, sans-serif;
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with gr.Row():
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with gr.Column():
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prompt = gr.Textbox(label="Prompt (Less than 200 Words)", value="Sunset over the sea.", lines=2)
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with gr.Column():
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gr.Markdown("**Generation Parameters**<br>")
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["THUDM/CogVideoX-2b", "THUDM/CogVideoX-5b"], label="Model Type", value="THUDM/CogVideoX-2b"
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)
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with gr.Row():
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num_inference_steps = gr.Slider(label="Inference Steps", maximum=50, value=50)
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guidance_scale = gr.Slider(label="Guidance Scale", value=6.0, maximum=15.0)
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gr.Markdown("**Pyramid Attention Broadcast Parameters**<br>")
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with gr.Row():
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pab_range = gr.Slider(
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label="Broadcast Range",
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value=2,
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step=1,
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minimum=1,
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maximum=4,
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info="Attention broadcast range.",
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)
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pab_threshold_start = gr.Slider(
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label="Start Timestep",
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minimum=500,
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maximum=1000,
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value=850,
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step=1,
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info="Broadcast start timestep (1000 is the fisrt).",
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)
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pab_threshold_end = gr.Slider(
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label="End Timestep",
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minimum=0,
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maximum=500,
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step=1,
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value=100,
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info="Broadcast end timestep (0 is the last).",
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)
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with gr.Row():
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generate_button_vs = gr.Button("⚡️ Generate Video with VideoSys")
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with gr.Column():
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with gr.Row():
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video_output_vs = gr.Video(label="CogVideoX with VideoSys", width=720, height=480)
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generate_button_vs.click(
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generate_vs,
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concurrency_limit=1,
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)
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if __name__ == "__main__":
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demo.queue(max_size=10, default_concurrency_limit=1)
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