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2b2d98d
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1 Parent(s): 78ca150

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Files changed (4) hide show
  1. .ipynb_checkpoints/README-checkpoint.md +1 -1
  2. .ipynb_checkpoints/app-checkpoint.py +4 -4
  3. README.md +1 -1
  4. app.py +4 -4
.ipynb_checkpoints/README-checkpoint.md CHANGED
@@ -7,7 +7,7 @@ sdk: gradio
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  sdk_version: 3.35.2
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  app_file: app.py
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  pinned: false
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- startup_duration_timeout: 1h
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  suggested_hardware: t4-medium
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  license: apache-2.0
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  ---
 
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  sdk_version: 3.35.2
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  app_file: app.py
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  pinned: false
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+ startup_duration_timeout: 4h
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  suggested_hardware: t4-medium
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  license: apache-2.0
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  ---
.ipynb_checkpoints/app-checkpoint.py CHANGED
@@ -20,12 +20,12 @@ magic_model = keras_cv.models.StableDiffusion(
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  )
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  magic_model.diffusion_model.load_weights(weights_path)
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- #magic_model.diffusion_model.compile(jit_compile=True)
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- #magic_model.decoder.compile(jit_compile=True)
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- #magic_model.text_encoder.compile(jit_compile=True)
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  # Warm-up the model
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- #_ = magic_model.text_to_image("flying dragons", batch_size=num_images_to_gen)
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  def generate_image_fn(prompt: str, steps: int) -> list:
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  start_time = time.time()
 
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  )
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  magic_model.diffusion_model.load_weights(weights_path)
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+ magic_model.diffusion_model.compile(jit_compile=True)
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+ magic_model.decoder.compile(jit_compile=True)
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+ magic_model.text_encoder.compile(jit_compile=True)
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  # Warm-up the model
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+ _ = magic_model.text_to_image("flying dragons", batch_size=num_images_to_gen)
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  def generate_image_fn(prompt: str, steps: int) -> list:
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  start_time = time.time()
README.md CHANGED
@@ -7,7 +7,7 @@ sdk: gradio
7
  sdk_version: 3.35.2
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  app_file: app.py
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  pinned: false
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- startup_duration_timeout: 1h
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  suggested_hardware: t4-medium
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  license: apache-2.0
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  ---
 
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  sdk_version: 3.35.2
8
  app_file: app.py
9
  pinned: false
10
+ startup_duration_timeout: 4h
11
  suggested_hardware: t4-medium
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  license: apache-2.0
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  ---
app.py CHANGED
@@ -20,12 +20,12 @@ magic_model = keras_cv.models.StableDiffusion(
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  )
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  magic_model.diffusion_model.load_weights(weights_path)
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- #magic_model.diffusion_model.compile(jit_compile=True)
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- #magic_model.decoder.compile(jit_compile=True)
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- #magic_model.text_encoder.compile(jit_compile=True)
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  # Warm-up the model
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- #_ = magic_model.text_to_image("flying dragons", batch_size=num_images_to_gen)
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  def generate_image_fn(prompt: str, steps: int) -> list:
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  start_time = time.time()
 
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  )
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  magic_model.diffusion_model.load_weights(weights_path)
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+ magic_model.diffusion_model.compile(jit_compile=True)
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+ magic_model.decoder.compile(jit_compile=True)
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+ magic_model.text_encoder.compile(jit_compile=True)
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  # Warm-up the model
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+ _ = magic_model.text_to_image("flying dragons", batch_size=num_images_to_gen)
29
 
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  def generate_image_fn(prompt: str, steps: int) -> list:
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  start_time = time.time()