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Hi @LTH14 I have a question for the VAE training.
Your project code doesn't involve VAE training, which I completely understand since you only need a pre-trained VAE to extract tokens. I now want t…
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I used autoencoder_vq_f4.pth as the VQGAN model to train my own dataset, but during inference, I encountered the error KeyError: 'vae'.
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Paper: https://arxiv.org/abs/1312.6114
Example implementations (non-official): https://github.com/clementchadebec/benchmark_VAE
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I want to create a denoising autoencoder using CNTK deconv and Unpooling functions.
The example for autoencoders only use the input image for comparison with the output from the autoencoder: (err …
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# Problem
Might be good to have a single *autoencoder* class that is completely *customizable* (i.e. you can not only configure the layer parameters, but also change the layer type).
# Solution
T…
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```
pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
pipe = pipe.to("cuda")
prompt = "a beautiful landscape photograph"
pipe.enable_vae_tiling()
```
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What's the reasoning behind having the first layer smaller than the middle layers, unlike what the picture shows? Is it to reduce the number of parameters and overfitting, or simply the best configura…
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http://arxiv.org/pdf/1511.05644v2.pdf
Use adversarial framework instead of variational.
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There is a concern regarding how to transmit complex symbols from the last layer of the autoencoder to the receiver, which typically handles a bitstream of 0s and 1s. Current applications rely on such…
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Can you give Autoencoder/autoencoder.py example code? Thanks!