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grammar
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Signed-off-by: Can-Zhao <[email protected]>
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Can-Zhao committed Nov 21, 2024
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### Training GPU Memory Usage
The VAE is trained on patches and can be trained using a 16G GPU if the patch size is set to a small value, such as [64, 64, 64].
Users can adjust the patch size to fit the available GPU memory.
For the released model, we initially trained the autoencoder on a 16G V100 GPU with a small patch size of [64, 64, 64], and then continued training on a 32G V100 GPU with a larger patch size of [128, 128, 128].
The VAE is trained on patches and can be trained using a 16G GPU if the patch size is set to a small value, such as [64, 64, 64]. Users can adjust the patch size to fit the available GPU memory. For the released model, we initially trained the autoencoder on a 16G V100 GPU with a small patch size of [64, 64, 64], and then continued training on a 32G V100 GPU with a larger patch size of [128, 128, 128].

The DM and ControlNet are trained on whole images rather than patches.
The GPU memory usage during training depends on the size of the input images.
The DM and ControlNet are trained on whole images rather than patches. The GPU memory usage during training depends on the size of the input images.

| image size | latent size | Peak Memory |
|--------------|:------------- |:-----------:|
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