def train_model2(train_op, n_epoch_2, opt, model1, sess, X_dataset, Y_dataset, W_dataset, Z_dataset):
train_gen_op_xyw = train_op.get_train_gen_op_xyw()
train_disc_op_xyw = train_op.get_train_disc_op_xyw()
FD_xyw = []
FG_xyw = []
DG_xyw = DG()
DG_xyw.initial()
dmb1 = [[0]*2]*128
dmb2 = [[1]*2]*128
x = model1.get_x()
y = model1.get_y()
w = model1.get_w()
z = model1.get_z()
d1 = model1.get_d1()
d2 = model1.get_d2()
for epoch in tqdm( range(n_epoch_2), total=n_epoch_2):
X_dataset = shuffle(X_dataset)
Y_dataset = shuffle(Y_dataset)
W_dataset = shuffle(W_dataset)
Z_dataset = shuffle(Z_dataset)
i = 0
for xmb, ymb, wmb, zmb in iter_data(X_dataset, Y_dataset, W_dataset, Z_dataset, size=batch_size):
i = i + 1
for _ in range(1):
f_d_xyw, _ = sess.run([model1.get_disc_loss_xyw(), train_disc_op_xyw], feed_dict={x: xmb, y:ymb, w:wmb, z:zmb, d1:dmb1, d2:dmb2})
for _ in range(5):
f_g_xyw, _ = sess.run([[model1.get_gen_loss_xyw(), model1.get_gen_loss_x(), model1.get_cost_x(), model1.get_cost_xz()], train_gen_op_xyw], feed_dict={x: xmb, y:ymb, w:wmb, z:zmb, d1:dmb1, d2:dmb2})
FG_xyw.append(f_g_xyw)
FD_xyw.append(f_d_xyw)
print_xy(epoch, i, f_d_xyw, f_g_xyw[0], f_g_xyw[1], f_g_xyw[2], f_g_xyw[3])
DG_xyw.set_FD(FD_xyw)
DG_xyw.set_FG(FG_xyw)
return sess, DG_xyw, model1
feed_dict={
x: xmb,
y: ymb,
z: zmb
})
for _ in range(5):
f_g_xy, _ = sess.run(
[[gen_loss, gen_loss_xz, cost_x, cost_xz], train_gen_op_xy],
feed_dict={
x: xmb,
y: ymb,
z: zmb
})
FG_xy.append(f_g_xy)
FD_xy.append(f_d_xy)
print_xy(epoch, i, f_d_xy, f_g_xy[0], f_g_xy[1], f_g_xy[2], f_g_xy[3])
DG_xy.set_FD(FD_xy)
DG_xy.set_FG(FG_xy)
#[sess,DG_xz,DG_yz,DG_xy]=train(option, sess, data_x.get_dataset(), data_y.get_dataset(), data_z.get_dataset(), print_xz, train_gen_op_xy, train_disc_op_xy, train_gen_op_x, train_disc_op_x, gen_loss_x, disc_loss_x,train_gen_op_y, train_disc_op_y, gen_loss_y, disc_loss_y, x, y, z,gen_loss_xz, cost_x, cost_xz, gen_loss_yz, cost_y, cost_yz, gen_loss_xy, disc_loss_xy, cost_yzxz, cost_xzyz)
""" testing the results """
n_viz = 1
[imxz, rmxz, imzx, rmzx, imyz, rmyz, imzy, rmzy, rmyzy,
rmxzx] = test(option, data_x.get_dataset_test(), data_y.get_dataset_test(),
data_z.get_dataset_test(), q_xz, rec_xz, p_x, q_yz, rec_yz, p_y,
rec_zx, rec_zy, n_viz, sess, x, y, z)
# print all
plot_all(option, DG_xz, DG_yz, DG_xy, imxz, rmxz, imzx, rmzx, imyz, rmyz, imzy,
rmzy, rmyzy, rmxzx, data_x.get_label_test(), data_y.get_label_test(),
data_z.get_label_test(), n_viz)