Spaces:
Running
on
Zero
Running
on
Zero
Commit
·
91db0c0
1
Parent(s):
2c4b825
debug
Browse files
app.py
CHANGED
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@@ -26,6 +26,14 @@ from videox_fun.data.dataset_image_video import derive_ground_object_from_instru
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from videox_fun.utils.lora_utils import merge_lora, unmerge_lora
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from videox_fun.utils.utils import save_videos_grid, timer
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# Redefine create_height_width to remove Chinese and specific defaults if needed,
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# although we will mostly ignore sliders if we use input resolution.
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# We will create a custom version here to avoid modifying the library file if possible,
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@@ -150,7 +158,6 @@ def preload_models(controller, default_model_path, default_lora_name, acc_lora_p
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torch.cuda.empty_cache()
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class VideoCoF_Controller(Wan_Controller):
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@spaces.GPU(duration=300)
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@timer
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def generate(
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self,
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@@ -362,6 +369,8 @@ def ui(GPU_memory_mode, scheduler_dict, config_path, compile_dit, weight_dtype):
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config_path=config_path, compile_dit=compile_dit,
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weight_dtype=weight_dtype
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)
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with gr.Blocks() as demo:
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gr.Markdown("# VideoCoF Demo")
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@@ -472,7 +481,7 @@ def ui(GPU_memory_mode, scheduler_dict, config_path, compile_dit, weight_dtype):
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# Event handlers
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generate_button.click(
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fn=
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inputs=[
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diffusion_transformer_dropdown,
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base_model_dropdown,
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from videox_fun.utils.lora_utils import merge_lora, unmerge_lora
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from videox_fun.utils.utils import save_videos_grid, timer
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global_controller = None
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@spaces.GPU(duration=300)
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@timer
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def generate_wrapper(*args):
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global global_controller
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return global_controller.generate(*args)
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# Redefine create_height_width to remove Chinese and specific defaults if needed,
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# although we will mostly ignore sliders if we use input resolution.
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# We will create a custom version here to avoid modifying the library file if possible,
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torch.cuda.empty_cache()
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class VideoCoF_Controller(Wan_Controller):
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@timer
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def generate(
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self,
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config_path=config_path, compile_dit=compile_dit,
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weight_dtype=weight_dtype
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)
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global global_controller
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global_controller = controller
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with gr.Blocks() as demo:
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gr.Markdown("# VideoCoF Demo")
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# Event handlers
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generate_button.click(
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fn=generate_wrapper,
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inputs=[
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diffusion_transformer_dropdown,
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base_model_dropdown,
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