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Dense layer in variational_layers is not saved and cannot be used to generate latent variables #40

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hengshiyu opened this issue May 10, 2021 · 0 comments

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@hengshiyu
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I found the variational_layers gives the posterior log variances for the latent variables from the last encoding layer through a dense layer link. However, this dense in the variational_layers is not saved after training and thus users cannot obtain the latent posterior log variances or samples.

The example provided only uses the posterior means to decode to smiles. Can you actually encode smiles to posterior samples rather than posterior means after training?

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