def eval(self, z, y=None):
out = self.sess.run(self.G, feed_dict = {
self.Z: z[:, :self.noise_dim],
self.c_dis: y,
self.c_cont: z[:,self.noise_dim:]
})
out = processing.img_deprocessing(out)
fig = processing.show_images(out,'generated/save.png')
return fig
def eval(self, z, y=None):
out = self.sess.run(self.G, feed_dict={self.Z: z, self.y: y})
out = processing.img_deprocessing(out)
return processing.show_images(out)
def eval(self, z, y=None):
out = self.sess.run(
self.y_queue[self.num_stack],
feed_dict = {self.Z: z, self.y: y, self.X: np.zeros([len(y), self.input_shape[0]])})
out = processing.img_deprocessing(out)
return processing.show_images(out)
def eval(self, z, y=None):
out = self.sess.run(self.G, feed_dict = {self.Z: z, self.y: y, self.X: np.zeros([self.y[0], self.input_shape[0]])})
out = processing.img_deprocessing(out)
return processing.show_images(out)
def eval(self, z, y=None):
out = self.sess.run(self.G, feed_dict={self.Z: z})
out = processing.mnist_deprocessing(out)
fig = processing.show_images(out, 'generated/save.png')
return fig