AlekseyCalvin commited on
Commit
7716209
·
verified ·
1 Parent(s): e8d61e0

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -104,7 +104,7 @@ def update_selection(evt: gr.SelectData, width, height):
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  )
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  @spaces.GPU(duration=70)
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- def generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, negative_prompt, no_cfg_until_timestep, lora_scale, progress):
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  pipe.to("cuda")
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  generator = torch.Generator(device="cuda").manual_seed(seed)
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@@ -118,12 +118,12 @@ def generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height,
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  height=height,
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  generator=generator,
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  negative_prompt=negative_prompt,
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- no_cfg_until_timestep=2,
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  joint_attention_kwargs={"scale": lora_scale},
 
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  ).images[0]
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  return image
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- def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, width, height, negative_prompt, no_cfg_until_timestep=2, lora_scale, progress=gr.Progress(track_tqdm=True)):
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  if selected_index is None:
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  raise gr.Error("You must select a LoRA before proceeding.")
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@@ -153,7 +153,7 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, wid
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  if randomize_seed:
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  seed = random.randint(0, MAX_SEED)
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- image = generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, negative_prompt, no_cfg_until_timestep, lora_scale, progress)
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  pipe.to("cpu")
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  pipe.unload_lora_weights()
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  return image, seed
 
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  )
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  @spaces.GPU(duration=70)
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+ def generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, negative_prompt, lora_scale, progress, no_cfg_until_timestep):
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  pipe.to("cuda")
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  generator = torch.Generator(device="cuda").manual_seed(seed)
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  height=height,
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  generator=generator,
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  negative_prompt=negative_prompt,
 
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  joint_attention_kwargs={"scale": lora_scale},
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+ no_cfg_until_timestep=2,
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  ).images[0]
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  return image
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+ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, width, height, negative_prompt, lora_scale, no_cfg_until_timestep=2, progress=gr.Progress(track_tqdm=True)):
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  if selected_index is None:
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  raise gr.Error("You must select a LoRA before proceeding.")
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  if randomize_seed:
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  seed = random.randint(0, MAX_SEED)
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+ image = generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, negative_prompt, lora_scale, progress, no_cfg_until_timestep)
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  pipe.to("cpu")
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  pipe.unload_lora_weights()
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  return image, seed