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)