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poolio commented Mar 7, 2017

  • The StochasticTensor in the generative model is used to keep track of the sample x ~ p(x|z) and the density p(x|z) so we can evaluate it when computing the log probability of the data given the sampled latent state, z.

  • In practice we don't have acess to T* and use the current discriminator T as a replacement. T does not directly depend on the parameters of p, so d/dp -T(x, z) is 0, and the gradients are identical to the gradients using the separate losses in the paper.

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JulienSiems commented Mar 8, 2017

Makes sense! Thank you for taking the time to reply!

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clarken92 commented Dec 5, 2018

Thank you for your interesting post. Please forgive me if I ask a dumb question. How could I find "stochastic_tensor" module on tensorflow? I use the version 1.8 installed with pip but it says there is no such module. Thank you.

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