ruslanmv commited on
Commit
93cdc3b
·
1 Parent(s): 996f9bb
Files changed (1) hide show
  1. flux_app/backend.py +2 -3
flux_app/backend.py CHANGED
@@ -30,7 +30,6 @@ class ModelManager:
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  self.initialize_models()
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- @spaces.GPU(duration=100)
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  def initialize_models(self):
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  """Initializes the diffusion pipelines and autoencoders."""
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  self.taef1 = AutoencoderTiny.from_pretrained(TAEF1_MODEL, torch_dtype=DTYPE).to(DEVICE)
@@ -48,9 +47,10 @@ class ModelManager:
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  ).to(DEVICE)
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  setattr(self.pipe, "flux_pipe_call_that_returns_an_iterable_of_images", self.process_images)
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- @spaces.GPU(duration=100)
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  def process_images(self, *args, **kwargs):
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  return flux_pipe_call_that_returns_an_iterable_of_images(self.pipe, *args, **kwargs)
 
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  @spaces.GPU(duration=100)
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  def generate_image(self, prompt_mash, steps, seed, cfg_scale, width, height, lora_scale):
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  """Generates an image using the FLUX pipeline."""
@@ -70,7 +70,6 @@ class ModelManager:
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  good_vae=self.good_vae,
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  ):
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  yield img
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- #@spaces.GPU(duration=100)
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  def generate_image_to_image(self, prompt_mash, image_input_path, image_strength, steps, cfg_scale, width, height, lora_scale, seed):
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  """Generates an image using image-to-image processing."""
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  generator = torch.Generator(device=DEVICE).manual_seed(seed)
 
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  self.initialize_models()
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  def initialize_models(self):
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  """Initializes the diffusion pipelines and autoencoders."""
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  self.taef1 = AutoencoderTiny.from_pretrained(TAEF1_MODEL, torch_dtype=DTYPE).to(DEVICE)
 
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  ).to(DEVICE)
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  setattr(self.pipe, "flux_pipe_call_that_returns_an_iterable_of_images", self.process_images)
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+
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  def process_images(self, *args, **kwargs):
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  return flux_pipe_call_that_returns_an_iterable_of_images(self.pipe, *args, **kwargs)
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+
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  @spaces.GPU(duration=100)
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  def generate_image(self, prompt_mash, steps, seed, cfg_scale, width, height, lora_scale):
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  """Generates an image using the FLUX pipeline."""
 
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  good_vae=self.good_vae,
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  ):
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  yield img
 
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  def generate_image_to_image(self, prompt_mash, image_input_path, image_strength, steps, cfg_scale, width, height, lora_scale, seed):
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  """Generates an image using image-to-image processing."""
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  generator = torch.Generator(device=DEVICE).manual_seed(seed)