from model import DCGAN import os import scipy.misc import numpy as np from model import DCGAN from utils import pp, visualize, to_json flags = tf.app.flags #flags.DEFINE_float("learning_rate", 0.0002, "Learning rate of for adam [0.0002]") #flags.DEFINE_float("beta1", 0.5, "Momentum term of adam [0.5]") #flags.DEFINE_string("checkpoint_dir", "checkpoint_new2", "Directory name to save the checkpoints [checkpoint]") FLAGS = flags.FLAGS from PIL import Image from tensorflow.contrib.framework.python.framework import checkpoint_utils config = tf.ConfigProto() # config.gpu_options.allow_growth = True with tf.Session(config=config) as sess: dcgan = DCGAN( sess, batch_size=1024, sample_size=1024, num_iters=80000, LEARNING_RATE=1., ) dcgan.ReverseBatchwithNoise(FLAGS)