From ea414443218a1654189a8e62745c5acd23f67da2 Mon Sep 17 00:00:00 2001 From: kozistr Date: Wed, 9 May 2018 00:10:07 +0900 Subject: [PATCH] update: MNIST DataSet loader path --- SGAN/sgan_train.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/SGAN/sgan_train.py b/SGAN/sgan_train.py index ad46ca3..e0524b6 100644 --- a/SGAN/sgan_train.py +++ b/SGAN/sgan_train.py @@ -31,7 +31,7 @@ def main(): start_time = time.time() # Clocking start # MNIST Dataset load - mnist = DataSet().data + mnist = DataSet(ds_path="./").data # GPU configure config = tf.ConfigProto() @@ -45,9 +45,7 @@ def main(): s.run(tf.global_variables_initializer()) sample_x, sample_y = mnist.test.next_batch(model.sample_num) - sample_x = np.reshape(sample_x, [model.sample_num, model.n_input]) - sample_z_0 = np.random.uniform(-1., 1., [model.sample_num, model.z_dim]).astype(np.float32) - sample_z_1 = np.random.uniform(-1., 1., [model.sample_num, model.z_dim]).astype(np.float32) + # sample_x = np.reshape(sample_x, [model.sample_num, model.n_input]) d_overpowered = False for step in range(train_step['global_step']): @@ -101,6 +99,8 @@ def main(): " G loss : {:.8f}".format(g_0_loss)) # Training G model with sample image and noise + sample_z_0 = np.random.uniform(-1., 1., [model.sample_num, model.z_dim]).astype(np.float32) + sample_z_1 = np.random.uniform(-1., 1., [model.sample_num, model.z_dim]).astype(np.float32) _, samples = s.run([model.g_1, model.g_0], feed_dict={ model.y: sample_y,