def test_train_q_rev_kl(self):
"""Verify that train_q_rev_kl doesn't raise any exceptions."""
q = train_ebm.MeanFieldGaussianQ()
u = lambda x: tf.reduce_sum(tf.square(x), axis=[1, 2, 3])
opt = tf.optimizers.Adam()
loss, entropy = train_ebm.train_q_rev_kl(q, u, opt)
self.assertTrue(np.all(np.isfinite(loss)))
self.assertTrue(np.all(np.isfinite(entropy)))
def test_train_q_mle(self):
"""Verify that train_q_mle doesn't raise any exceptions."""
num_samples = 16
x = tf.random.normal([num_samples, N_WH, N_WH, N_CH], seed=12)
q = train_ebm.MeanFieldGaussianQ()
opt = tf.optimizers.Adam()
x = tf.random.normal([num_samples, N_WH, N_WH, N_CH], seed=13)
loss = train_ebm.train_q_mle(q, x, opt)
self.assertTrue(np.all(np.isfinite(loss)))
def test_train_q_rev_kl_mle(self):
"""Verify that train_q_rev_kl_mle doesn't raise any exceptions."""
num_samples = 16
x = tf.random.normal([num_samples, N_WH, N_WH, N_CH], seed=12)
q = train_ebm.MeanFieldGaussianQ()
u = lambda x: tf.reduce_sum(tf.square(x), axis=[1, 2, 3])
opt = tf.optimizers.Adam()
x = tf.random.normal([num_samples, N_WH, N_WH, N_CH], seed=12)
(loss, entropy, neg_e_q, mle_loss, grads_ebm_norm,
grads_mle_norm) = train_ebm.train_q_rev_kl_mle(q, u, x, 1., opt)
self.assertTrue(np.all(np.isfinite(loss)))
self.assertTrue(np.all(np.isfinite(entropy)))
self.assertTrue(np.all(np.isfinite(neg_e_q)))
self.assertTrue(np.all(np.isfinite(mle_loss)))
self.assertTrue(np.all(np.isfinite(grads_ebm_norm)))
self.assertTrue(np.all(np.isfinite(grads_mle_norm)))
def test_train_p(self):
"""Verify that train_p doesn't raise any exceptions."""
num_samples = 16
x = tf.random.normal([num_samples, N_WH, N_WH, N_CH], seed=12)
q = train_ebm.MeanFieldGaussianQ()
u = train_ebm.EbmConv(anchor_size=1)
opt = tf.optimizers.Adam()
x = tf.random.normal([num_samples, N_WH, N_WH, N_CH], seed=13)
(x_neg_q, x_neg_p, p_accept, step_size, pos_e, pos_e_updated, neg_e_q,
neg_e_p, neg_e_p_updated) = train_ebm.train_p(q, u, x, 0.1, opt)
self.assertTrue(np.all(np.isfinite(x_neg_q)))
self.assertTrue(np.all(np.isfinite(x_neg_p)))
self.assertTrue(np.all(np.isfinite(p_accept)))
self.assertTrue(np.all(np.isfinite(step_size)))
self.assertTrue(np.all(np.isfinite(pos_e)))
self.assertTrue(np.all(np.isfinite(pos_e_updated)))
self.assertTrue(np.all(np.isfinite(neg_e_q)))
self.assertTrue(np.all(np.isfinite(neg_e_p)))
self.assertTrue(np.all(np.isfinite(neg_e_p_updated)))
