def test_run_vars(self):
app_driver = get_initialised_driver()
test_graph = app_driver.create_graph(app_driver.app, 1, True)
test_tensor = test_graph.get_tensor_by_name("G/conv_bn_selu/conv_/w:0")
train_eval_msgs = []
test_vals = []
def get_iter_msgs(_sender, **msg):
"""" Captures iter_msg and model values for testing"""
train_eval_msgs.append(msg['iter_msg'])
test_vals.append(sess.run(test_tensor))
print(msg['iter_msg'].to_console_string())
ITER_FINISHED.connect(get_iter_msgs)
with self.test_session(graph=test_graph) as sess:
GRAPH_CREATED.send(app_driver.app, iter_msg=None)
SESS_STARTED.send(app_driver.app, iter_msg=None)
iterations = IterationMessageGenerator(initial_iter=0,
final_iter=3,
validation_every_n=2,
validation_max_iter=1,
is_training_action=True)
app_driver.loop(app_driver.app, iterations())
# Check sequence of iterations
self.assertRegexpMatches(train_eval_msgs[0].to_console_string(),
'training')
self.assertRegexpMatches(train_eval_msgs[1].to_console_string(),
'training')
self.assertRegexpMatches(train_eval_msgs[2].to_console_string(),
'validation')
self.assertRegexpMatches(train_eval_msgs[3].to_console_string(),
'training')
# Check durations
for iter_msg in train_eval_msgs:
self.assertGreater(iter_msg.iter_duration, 0.0)
# Check training changes test tensor
self.assertNotAlmostEqual(
np.mean(np.abs(test_vals[0] - test_vals[1])), 0.0)
self.assertNotAlmostEqual(
np.mean(np.abs(test_vals[2] - test_vals[3])), 0.0)
# Check validation doesn't change test tensor
self.assertAlmostEqual(
np.mean(np.abs(test_vals[1] - test_vals[2])), 0.0)
app_driver.app.stop()
ITER_FINISHED.disconnect(get_iter_msgs)
def test_init(self):
app_driver = get_initialised_driver()
test_graph = app_driver.create_graph(app_driver.app, 1, True)
app_driver.app.set_iteration_update = set_iteration_update
app_driver.app.interpret_output = self.create_interpreter()
app_driver.load_event_handlers([
'niftynet.engine.handler_model.ModelRestorer',
'niftynet.engine.handler_network_output.OutputInterpreter',
'niftynet.engine.handler_sampler.SamplerThreading'
])
with self.test_session(graph=test_graph) as sess:
SESS_STARTED.send(app_driver.app, iter_msg=None)
iterator = IterationMessageGenerator(is_training_action=False)
app_driver.loop(app_driver.app, iterator())
app_driver.app.stop()