def test__tf_propagate_forward(self): X, Y = create_placeholders(12288, 6) parameters = initialize_tf_parameters([12288, 25, 12, 6], seed=1) Z = _tf_propagate_forward(parameters, X) np.random.seed(1) dict_X = np.random.randn(12288, 1080) init = tf.global_variables_initializer() with tf.Session() as sess: sess.run(init) Z = sess.run(Z, feed_dict={X: dict_X}) self.assertAlmostEqual(Z[0][0], -2.46408725) self.assertAlmostEqual(Z[5][1079], -0.9831996) self.assertEqual(Z.shape, (6, 1080))
def test__tf_cost(self): X, Y = create_placeholders(12288, 6) parameters = initialize_tf_parameters([12288, 25, 12, 6], seed=1) Z = _tf_propagate_forward(parameters, X) cost = _tf_cost(Z, Y) np.random.seed(1) dict_X = np.random.randn(12288, 1080) dict_Y = np.random.randn(6, 1080) init = tf.global_variables_initializer() with tf.Session() as sess: sess.run(init) cost = sess.run(cost, feed_dict={X: dict_X, Y: dict_Y}) self.assertAlmostEqual(cost, 0.11581959)
def test_initialize_tf_parameters(self): parameters = initialize_tf_parameters([12288, 25, 12, 6], seed=1) init = tf.global_variables_initializer() with tf.Session() as sess: sess.run(init) parameters = sess.run(parameters) self.assertEqual(parameters['W1'].shape, (25, 12288)) self.assertAlmostEqual(parameters['W1'][0][0], -0.01962241) self.assertEqual(parameters['b1'].shape, (25, 1)) self.assertEqual(np.sum(parameters['b1']), 0) self.assertEqual(parameters['W2'].shape, (12, 25)) self.assertAlmostEqual(parameters['W2'][0][0], -0.35795909) self.assertEqual(parameters['b2'].shape, (12, 1)) self.assertEqual(np.sum(parameters['b2']), 0) self.assertEqual(parameters['W3'].shape, (6, 12)) self.assertAlmostEqual(parameters['W3'][0][0], -0.5132134) self.assertEqual(parameters['b3'].shape, (6, 1)) self.assertEqual(np.sum(parameters['b3']), 0)