vae training and autovae #11592
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vae training and autovae #11592
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Signed-off-by: linnan wang <[email protected]>
ethanhe42
previously approved these changes
Dec 14, 2024
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| self.discriminator = NLayerDiscriminator( | ||
| input_nc=disc_in_channels, n_layers=disc_num_layers, use_actnorm=use_actnorm |
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Explicit returns mixed with implicit (fall through) returns Note
Signed-off-by: linnan wang <[email protected]>
ethanhe42
approved these changes
Dec 16, 2024
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@pablo-garay @ethanhe42 thanks! |
abhinavg4
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Jan 30, 2025
* vae training Signed-off-by: linnan wang <[email protected]> * vae training Signed-off-by: linnan wang <[email protected]> --------- Signed-off-by: linnan wang <[email protected]> Signed-off-by: Abhinav Garg <[email protected]>
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What does this PR do ?
this PR introduces VAE training into NeMo that allows users to customize a 16x or 8x reduction VAE on their in house data. Besides, we also introduce a feature that automatically designs VAE based on the GPU memory and latency requirements.
Collection: NeMo/Diffusion/VAE
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