def test_jacobian(self):
m_np = np.array([[1., 2.], [3., 4.]], np.float32)
m = tf.Variable(m_np)
x = tf.Variable([4., -1.], tf.float32)
y = tf.einsum('nm,m->n', m, x)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
jacobian = tfutils.jacobian(y, x)
jacobian_actual = sess.run(jacobian)
self.assertTrue(np.allclose(jacobian_actual, m_np))
def test_jacobian_multirank_y(self):
m_np = np.array([[1., 2.], [3., 4.]], np.float32)
m = tf.Variable(m_np)
x = tf.Variable([4.], tf.float32)
y = m * x
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
jacobian = tfutils.jacobian(y, x)
jacobian_actual = sess.run(jacobian)
jacobian_actual = np.reshape(jacobian_actual, m_np.shape)
self.assertTrue(np.allclose(jacobian_actual, m_np))
def test_jacobian_dynamic_dim(self):
m_np = np.array([[1., 2.], [3., 4.]], np.float32)
# m = tf.Variable(m_np)
# x = tf.Variable([4., -1.], tf.float32)
m = tf.placeholder(tf.float32, shape=[2, None])
x = tf.placeholder(tf.float32, shape=[None])
y = tf.einsum('nm,m->n', m, x)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
jacobian = tfutils.jacobian(y, x)
jacobian_actual = sess.run(jacobian, feed_dict={m: m_np, x: [4., -1.]})
self.assertTrue(np.allclose(jacobian_actual, m_np))