Hello, first of all thank you for the code!
I have a question about the forward pass in the srVAE model:
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def forward(self, x, **kwargs): |
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""" Forward pass through the inference and the generative model. """ |
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# y ~ f(x) (determinist) |
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y = self.compressed_transoformation(x) |
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# u ~ q(u| y) |
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u_q_mean, u_q_logvar = self.q_u(y) |
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u_q = self.reparameterize(u_q_mean, u_q_logvar) |
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# z ~ q(z| x, y) |
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z_q_mean, z_q_logvar = self.q_z(x) |
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z_q = self.reparameterize(z_q_mean, z_q_logvar) |
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# x ~ p(x| y, z) |
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x_logits = self.p_x((y, z_q)) |
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# y ~ p(y| u) |
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y_logits = self.p_y(u_q) |
It looks like p_x gets the ground truth y as input. Should this not be the y that is predicted by p_y instead?
Best regards!
Hello, first of all thank you for the code!
I have a question about the forward pass in the srVAE model:
srVAE/src/models/srvae/srvae.py
Lines 178 to 195 in dfee765
It looks like p_x gets the ground truth y as input. Should this not be the y that is predicted by p_y instead?
Best regards!