Comments (1)
I don't remember fully without doing more research, but I think it has to do with the fact that the discriminator gets called through two different loss functions on every training cycle, d_loss_real
and d_loss_fake
, and needs to keep the same variable scope between them, whereas the generator only gets called through g_loss
.
That said, I'm feeling rusty on this project as I glance back over it. Maybe @adeshpande3 remembers?
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Related Issues (8)
- Error for running with TensorFlow: ValueError: Variable d_w1/Adam/ does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=None in VarScope? HOT 5
- Python 3.5 TensorFlow 1.2 variable scope related error HOT 2
- What should I do if I want to use this to train my own database HOT 2
- Training Betas and Gammas of the batch normalization HOT 3
- Not able to load pre-trained model HOT 4
- ValueError: Variable d_w1/Adam_5/ does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=tf.AUTO_REUSE in VarScope? HOT 3
- Variable d_w1/Adam_3/ does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=tf.AUTO_REUSE in VarScope? HOT 1
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