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0fac10f
1
Parent(s):
9bd2ea4
Update app.py
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app.py
CHANGED
@@ -59,12 +59,9 @@ original_pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-
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def merge_and_run(prompt, negative_prompt, shuffled_items, lora_1_scale=0.5, lora_2_scale=0.5, progress=gr.Progress(track_tqdm=True)):
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state_dict_1 = copy.deepcopy(shuffled_items[0]['state_dict'])
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print("state_1", state_dict_1)
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state_dict_2 = copy.deepcopy(shuffled_items[1]['state_dict'])
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print("state_2", state_dict_2)
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pipe = copy.deepcopy(original_pipe)
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pipe.to("cuda")
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pipe.load_lora_weights(state_dict_1)
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pipe.fuse_lora(lora_1_scale)
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@@ -75,10 +72,10 @@ def merge_and_run(prompt, negative_prompt, shuffled_items, lora_1_scale=0.5, lor
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negative_prompt = None
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image = pipe(prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=20, width=768, height=768).images[0]
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yield image
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del pipe
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gc.collect()
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torch.cuda.empty_cache()
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def get_description(item):
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trigger_word = item["trigger_word"]
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def merge_and_run(prompt, negative_prompt, shuffled_items, lora_1_scale=0.5, lora_2_scale=0.5, progress=gr.Progress(track_tqdm=True)):
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state_dict_1 = copy.deepcopy(shuffled_items[0]['state_dict'])
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state_dict_2 = copy.deepcopy(shuffled_items[1]['state_dict'])
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pipe = copy.deepcopy(original_pipe)
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pipe.to("cuda")
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pipe.load_lora_weights(state_dict_1)
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pipe.fuse_lora(lora_1_scale)
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negative_prompt = None
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image = pipe(prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=20, width=768, height=768).images[0]
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del pipe
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gc.collect()
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torch.cuda.empty_cache()
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return image
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def get_description(item):
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trigger_word = item["trigger_word"]
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