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fb4901e
1
Parent(s):
3b6af48
Update app.py
Browse files
app.py
CHANGED
@@ -98,15 +98,19 @@ def merge_and_run(prompt, negative_prompt, shuffled_items, lora_1_scale=0.5, lor
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print("Loading state dicts...")
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start_time = time()
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state_dict_1 = copy.deepcopy(state_dicts[repo_id_1]["state_dict"])
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state_dict_2 = copy.deepcopy(state_dicts[repo_id_2]["state_dict"])
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state_dict_time = time() - start_time
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print(f"State Dict time: {state_dict_time}")
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#pipe = copy.deepcopy(original_pipe)
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start_time = time()
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unet = copy.deepcopy(original_pipe.unet)
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pipe = StableDiffusionXLPipeline(vae=original_pipe.vae,
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-
text_encoder=
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-
text_encoder_2=
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scheduler=original_pipe.scheduler,
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tokenizer=original_pipe.tokenizer,
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tokenizer_2=original_pipe.tokenizer_2,
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print("Loading state dicts...")
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start_time = time()
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state_dict_1 = copy.deepcopy(state_dicts[repo_id_1]["state_dict"])
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state_dict_1 = {k: v.to(device="cuda", dtype=torch.float16) for k,v in state_dict_1.items() if torch.is_tensor(v)}
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state_dict_2 = copy.deepcopy(state_dicts[repo_id_2]["state_dict"])
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state_dict_2 = {k: v.to(device="cuda", dtype=torch.float16) for k,v in state_dict_2.items() if torch.is_tensor(v)}
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state_dict_time = time() - start_time
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print(f"State Dict time: {state_dict_time}")
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#pipe = copy.deepcopy(original_pipe)
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start_time = time()
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unet = copy.deepcopy(original_pipe.unet)
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text_encoder=copy.deepcopy(original_pipe.text_encoder)
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text_encoder_2=copy.deepcopy(original_pipe.text_encoder_2)
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pipe = StableDiffusionXLPipeline(vae=original_pipe.vae,
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text_encoder=text_encoder,
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text_encoder_2=text_encoder_2,
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scheduler=original_pipe.scheduler,
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tokenizer=original_pipe.tokenizer,
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tokenizer_2=original_pipe.tokenizer_2,
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