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78ca150
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108dbc4
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Browse files- .ipynb_checkpoints/app-checkpoint.py +4 -4
- app.py +4 -4
.ipynb_checkpoints/app-checkpoint.py
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@@ -20,12 +20,12 @@ magic_model = keras_cv.models.StableDiffusion(
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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()
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app.py
CHANGED
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@@ -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()
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