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from hypergan.samplers.base_sampler import BaseSampler
import tensorflow as tf
class StaticBatchSampler(BaseSampler):
def __init__(self, gan, samples_per_row=8):
BaseSampler.__init__(self, gan, samples_per_row)
self.z = None
self.y = None
self.x = None
def _sample(self):
gan = self.gan
z_t = gan.encoder.z
inputs_t = gan.inputs.x
if self.z is None:
self.z = gan.encoder.z.eval()
self.input = gan.session.run(gan.inputs.x)
g=tf.get_default_graph()
with g.as_default():
tf.set_random_seed(1)
return {
'generator': gan.session.run(gan.generator.sample, feed_dict={z_t: self.z, inputs_t: self.input})
}
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