Checking the effect of "trainable"

[tdeboissiere]

In your code, you set the discriminator to trainable without recompiling.

2 questions:

• Does keras take this into account (the doc seems to imply that you need to compile for the trainable attribute to take effect ?
• I inspected the trainable attribute of the layers of the GAN model after you set make_trainable(discriminator, True) line and got the following output:

(First column: layer name, Second column: layer.trainable)

GAN input_1 False GAN dense_1 True GAN batchnormalization_1 True GAN activation_1 True GAN reshape_1 True GAN upsampling2d_1 True GAN convolution2d_1 True GAN batchnormalization_2 True GAN activation_2 True GAN convolution2d_2 True GAN batchnormalization_3 True GAN activation_3 True GAN convolution2d_3 True GAN activation_4 True GAN input_2 True GAN convolution2d_4 True GAN leakyrelu_1 True GAN dropout_1 True GAN convolution2d_5 True GAN leakyrelu_2 True GAN dropout_2 True GAN flatten_1 True GAN dense_2 True GAN leakyrelu_3 True GAN dropout_3 True GAN dense_3 True

which would imply that the GAN model actually updates the weights of the discriminator. Can you confirm whether this is the case ?

[osh]

just checked in update to MNIST_CNN_GAN_v2.ipynb which works with the latest Keras/TF.