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Hello, and thanks for the code! I want to replicate the audio results from the paper, but the DeepMind repo does not have a VQ-VAE example for audio (see google-deepmind/sonnet#141 ), and it seems quite different from the one for CIFAR:
We train a VQ-VAE where the encoder has 6 strided convolutions with stride 2 and window-size 4. This yields a latent space 64x smaller than the original waveform. The latents consist of one feature map and the discrete space is 512-dimensional.
Could you please include an example of using your code for audio?
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