def test_affine(self):
with self.test_session() as sess:
x = tf.placeholder(tf.float32, shape=[None, 3])
z = graph.affine_layer(10, x)
self.assertAllEqual(10, z.get_shape()[-1])
x_val = np.array([[3., 2., 1.]])
sess.run(tf.global_variables_initializer())
z_val = sess.run(z, feed_dict={x: x_val})
self.assertEquals((1, 10), z_val.shape)
self.assertAllClose([[
-0.92742872, 2.20097542, 0.72329885, -0.8619436, -0.09275365,
1.63259518, 3.04762506, 0.80803722, 0.48845479, 2.23918748
]], z_val)
def test_affine(self):
with self.test_session() as sess:
x = tf.placeholder(tf.float32, shape=[None, 3])
z = graph.affine_layer(10, x)
# Verify graph properties.
self.assertAllEqual(10, z.get_shape()[-1])
# Setup for running the graph.
sess.run(tf.global_variables_initializer())
# Verify that dimensions work with more than one row.
sess.run(z, feed_dict={x: np.array([[1., 2., 3.], [4., 5., 6.]])})
# Verify computation correct.
x_val = np.array([[3., 2., 1.]])
z_val = sess.run(z, feed_dict={x: x_val})
self.assertEquals((1, 10), z_val.shape)
self.assertAllClose([[
-0.92742872, 2.20097542, 0.72329885, -0.8619436, -0.09275365,
1.63259518, 3.04762506, 0.80803722, 0.48845479, 2.23918748
]], z_val)
def test_affine(self):
tf.set_random_seed(0)
with self.test_session() as sess:
x = tf.placeholder(tf.float32, shape=[None, 3])
z = graph.affine_layer(10, x)
# Verify graph properties.
self.assertAllEqual(10, z.get_shape()[-1])
# Setup for running the graph.
sess.run(tf.global_variables_initializer())
# Verify that dimensions work with more than one row.
sess.run(z, feed_dict={x: np.array([[1., 2., 3.], [4., 5., 6.]])})
# Verify computation correct.
x_val = np.array([[3., 2., 1.]])
z_val = sess.run(z, feed_dict={x: x_val})
self.assertEqual((1, 10), z_val.shape)
self.assertAllClose([[
-1.477905, -0.144029, 0.96745, 0.491507, -0.105209, -0.558219,
0.77895, 2.462549, -0.855641, 2.503024
]], z_val)
def test_affine(self):
tf.set_random_seed(0)
with self.test_session() as sess:
x = tf.placeholder(tf.float32, shape=[None, 3])
z = graph.affine_layer(10, x)
# Verify graph properties.
self.assertAllEqual(10, z.get_shape()[-1])
# Setup for running the graph.
sess.run(tf.global_variables_initializer())
# Verify that dimensions work with more than one row.
sess.run(z, feed_dict={
x: np.array([[1., 2., 3.], [4., 5., 6.]])})
# Verify computation correct.
x_val = np.array([[3., 2., 1.]])
z_val = sess.run(z, feed_dict={x: x_val})
self.assertEqual((1, 10), z_val.shape)
self.assertAllClose([[
-1.477905, -0.144029, 0.96745,
0.491507, -0.105209, -0.558219,
0.77895 , 2.462549, -0.855641,
2.503024]], z_val)