def test_colorization(self):
imgs_l, imgs_true_ab, imgs_emb = self._tensors()
# Build the network and the optimizer step
col = Colorization(256)
imgs_ab = col.build(imgs_l, imgs_emb)
opt_operations = color_optimizer(imgs_ab, imgs_true_ab)
self._run(imgs_l, imgs_ab, imgs_true_ab, opt_operations)
def test_colorization(self):
imgs_l, imgs_true_ab, imgs_emb = self._tensors()
# Build the network and the optimizer step
col = Colorization(256)
imgs_ab = col.build(imgs_l, imgs_emb)
cost = tf.reduce_mean(tf.squared_difference(imgs_ab, imgs_true_ab))
optimizer = tf.train.AdamOptimizer(0.001).minimize(cost)
opt_operations = {'cost': cost, 'optimizer': optimizer}
self._run(imgs_l, imgs_ab, imgs_true_ab, opt_operations)