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3dccffc
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Parent(s):
79a1e5b
Update app.py
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app.py
CHANGED
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@@ -154,19 +154,15 @@ def run_lora(prompt, negative, lora_scale, selected_state, sdxl_loras, progress=
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full_path_lora = state_dicts[repo_name]["saved_name"]
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loaded_state_dict = state_dicts[repo_name]["state_dict"]
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cross_attention_kwargs = None
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print("Last LoRA:", last_lora, "Was it last merged? ", last_merged, "Was it last fused?", last_fused)
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print("Current LoRA: ", repo_name)
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if last_lora != repo_name:
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is_compatible = sdxl_loras[selected_state.index]["is_compatible"]
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if is_compatible:
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@@ -187,6 +183,7 @@ def run_lora(prompt, negative, lora_scale, selected_state, sdxl_loras, progress=
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embedding_path = hf_hub_download(repo_id=repo_name, filename=text_embedding_name, repo_type="model")
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embhandler = TokenEmbeddingsHandler(text_encoders, tokenizers)
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embhandler.load_embeddings(embedding_path)
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else:
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merge_incompatible_lora(full_path_lora, lora_scale)
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last_fused=False
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@@ -198,7 +195,6 @@ def run_lora(prompt, negative, lora_scale, selected_state, sdxl_loras, progress=
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width=1024,
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height=1024,
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num_inference_steps=20,
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cross_attention_kwargs = {"scale" : lora_scale},
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guidance_scale=7.5,
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).images[0]
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last_lora = repo_name
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full_path_lora = state_dicts[repo_name]["saved_name"]
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loaded_state_dict = state_dicts[repo_name]["state_dict"]
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cross_attention_kwargs = None
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if last_lora != repo_name:
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if last_merged:
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del pipe
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gc.collect()
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pipe = copy.deepcopy(original_pipe)
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pipe.to(device)
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elif(last_fused):
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pipe.unfuse_lora()
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pipe.unload_lora_weights()
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is_compatible = sdxl_loras[selected_state.index]["is_compatible"]
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if is_compatible:
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embedding_path = hf_hub_download(repo_id=repo_name, filename=text_embedding_name, repo_type="model")
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embhandler = TokenEmbeddingsHandler(text_encoders, tokenizers)
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embhandler.load_embeddings(embedding_path)
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else:
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merge_incompatible_lora(full_path_lora, lora_scale)
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last_fused=False
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width=1024,
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height=1024,
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num_inference_steps=20,
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guidance_scale=7.5,
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).images[0]
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last_lora = repo_name
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