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ReginaldIII t1_iqzu0z9 wrote

I've been using the KerasCV's implementation with a T4 GPU on Colab with 16 bit floats and jitted to do batch size 5, 25 steps in 13 seconds. So I don't think it's fair to say you outright beat Keras' performance.

Amazing work all the same.

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Norlax_42 OP t1_ir2k1z5 wrote

Please notice that I reported 25.48 seconds for 50 steps. While you're talking about 25 steps. I expect this implementation to take less than 13 seconds for 15 steps.

In keras's blog they reported a runtime of 28.97s for 50 steps, thus the claim to beat their performance.

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DuLLSoN t1_ir04t67 wrote

5x 512x512 images with 25 steps on T4 Colab in 13 seconds? I would like to see a notebook of that.

I wonder if you mean 13 seconds per image because this implementation reports ~10s per image with mixed precision.

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ReginaldIII t1_ir067hc wrote 

import keras_cv
from tensorflow import keras

keras.mixed_precision.set_global_policy("mixed_float16")
model = keras_cv.models.StableDiffusion(img_width=512, img_height=512, jit_compile=True)

images = model.text_to_image("photograph of an astronaut riding a horse", batch_size=5)
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