def test_add_inference_step(self):
with tf.Graph().as_default():
# Given
x = tf.placeholder(tf.float32, [2, 2], name="x_input")
# When
softmax = graph.create_inference_step(
x, num_pixels=2, num_dense1=4, num_dense2=3, num_dense3=2, num_classes=2
)
# Then
self.assertIsNotNone(softmax)
self.assertEqual(type(softmax).__name__, "Tensor")
def test_run_inference(self):
with tf.Graph().as_default():
with tf.Session() as sess:
# Input variables
x = tf.Variable([[1.0, 1.0], [1.0, 1.0]], dtype=tf.float32)
# Accuracy
softmax = graph.create_inference_step(
x, num_pixels=2, num_dense1=4, num_dense2=3, num_dense3=2, num_classes=2
)
# Evaluate results
tf.initialize_all_variables().run()
self.assertAllClose(sess.run(softmax), [[0.5, 0.5], [0.5, 0.5]], rtol=1e-2, atol=1e-2)
