def generic_test_main(test_file,
test_data_file,
test_func,
comparator=None,
res_printer=None):
"""
The main test starter.
:param test_file - name of the test file
:param test_data_file - file with test data
:param test_func - function to be tested
:param comparator - custom comparator. A function that accepts
(expected, computed result) and returns a boolean value
:param res_printer - function for customized printing
"""
try:
with open(
get_file_path_in_judge_dir('config.json')) as config_file_data:
config_override = json.load(config_file_data)
commandline_args = sys.argv[1:]
config = TestConfig.from_command_line(
test_file, test_data_file, config_override['timeoutSeconds'],
config_override['numFailedTestsBeforeStop'], commandline_args)
set_output_opts(config.tty_mode, config.color_mode)
test_handler = GenericTestHandler(test_func, comparator=comparator)
return run_tests(test_handler, config, res_printer)
except RuntimeError as e:
print(
'\nCritical error({}): {}'.format(e.__class__.__name__, e),
file=sys.stderr)
return TestResult.RUNTIME_ERROR
def test_WriteToXMP_JPG(self):
method_name = sys._getframe(0).f_code.co_name
print "**** %s ****" % method_name
fn = self.data['ferns']
backup_folder = TestConfig.getInstance().output_path
backup_file = backupFile(fn, outputPath=backup_folder, overwrite=True)
print backup_file
ex = ExifTool(backup_file, False)
now = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
ex.setAttributes("exif", {"DateTimeOriginal": now})
dates = ex.getDateAttributes()
for k, v in dates.iteritems():
print "%40s = %s" % (k, v)
import sys
sys.path.append(os.path.dirname(__file__))
from test_config import TestConfig # noqa
some_messages_from_std_msgs = [
'std_msgs/msg/Bool',
'std_msgs/msg/Float32',
'std_msgs/msg/Float64',
]
configs = [
TestConfig(
command='msg',
arguments=['list'],
expected_output=some_messages_from_std_msgs,
),
TestConfig(
command='msg',
arguments=['package', 'std_msgs'],
expected_output=some_messages_from_std_msgs,
),
TestConfig(
command='msg',
arguments=['packages'],
expected_output=['std_msgs'],
),
TestConfig(
command='msg',
arguments=['show', 'std_msgs/msg/String'],
def before_all(context):
context.config = TestConfig()
context.config.driver = None
context.config.components = Components()
def test_model_losses(self):
config = TestConfig()
config.hidden_layer_sizes = [32]
config.value_dim = 1
config.learning_rate = 5e-3
# simple dataset, learn to output the sum
n_samples = 10
n_timesteps = 4
input_dim = 1
x = np.random.rand(n_samples, n_timesteps, input_dim)
y = np.ones((n_samples, n_timesteps)) * 0.5
for loss_type in ['mse', 'ce']:
tf.reset_default_graph()
with tf.Session() as session:
predictor = model.LSTMPredictor((input_dim, ), config)
target_placeholder = tf.placeholder(tf.float32, [None, 1],
'target')
if loss_type == 'mse':
loss = tf.reduce_sum(
(predictor.vf - target_placeholder)**2)
elif loss_type == 'ce':
yt = target_placeholder
yp = predictor.vf
loss = tf.reduce_sum(
(yt * -tf.log(tf.nn.sigmoid(yp)) +
(1 - yt) * -tf.log(1 - tf.nn.sigmoid(yp))))
opt = tf.train.AdamOptimizer(config.learning_rate)
train_op = opt.minimize(loss)
session.run(tf.global_variables_initializer())
def run_sample(p, x, y, state_in, train=True):
feed_dict = {
p.x: x,
target_placeholder: y,
p.dropout_keep_prob_ph: 1.,
p.state_in[0]: state_in[0],
p.state_in[1]: state_in[1],
}
outputs_list = [loss]
if train:
outputs_list += [train_op]
fetched = session.run(outputs_list, feed_dict=feed_dict)
if train:
val_loss, _ = fetched
else:
val_loss = fetched[0]
return val_loss
n_epochs = 100
n_train = int(n_samples * .8)
n_val = n_samples - n_train
verbose = False
for epoch in range(n_epochs):
# train
train_loss_mean = 0
for sidx in range(n_train):
train_loss = run_sample(predictor, x[sidx, :, :],
y[sidx].reshape(-1, 1),
predictor.state_init)
train_loss_mean += train_loss / n_train
# val
val_loss_mean = 0
for sidx in range(n_val):
val_loss = run_sample(predictor,
x[sidx, :, :],
y[sidx].reshape(-1, 1),
predictor.state_init,
train=False)
val_loss_mean += val_loss / n_val
value = predictor.value(x[sidx, :, :],
predictor.state_init[0],
predictor.state_init[1],
sequence=True)
if loss_type == 'ce':
value = 1 / (1 + np.exp(-value))
# print('x: {}\ny: {}\ny_pred: {}\n'.format(
# x[sidx,:,:], y[sidx].reshape(-1,1), value))
# input()
# report
if verbose:
print('epoch: {} / {}\ttrain loss: {}\tval loss: {}'.
format(epoch, n_epochs, train_loss_mean,
val_loss_mean))
self.assertTrue(np.abs(value - .5) < 1e-2)
def test_full_sequence_prediction(self):
config = TestConfig()
config.hidden_layer_sizes = [32, 32]
config.value_dim = 1
config.learning_rate = 1e-3
# simple dataset, learn to output the sum
n_samples = 100
n_timesteps = 4
input_dim = 1
x = np.random.rand(n_samples, n_timesteps, input_dim)
y = np.sum(x, axis=(1, 2)).reshape(-1, 1)
with tf.Session() as session:
predictor = model.LSTMPredictor((input_dim, ), config)
target_placeholder = tf.placeholder(tf.float32, [None, 1],
'target')
loss = tf.reduce_sum((predictor.vf[-1] - target_placeholder)**2)
opt = tf.train.AdamOptimizer(config.learning_rate)
train_op = opt.minimize(loss)
session.run(tf.global_variables_initializer())
def run_sample(p, x, y, state_in, train=True):
feed_dict = {
p.x: x,
target_placeholder: y,
p.dropout_keep_prob_ph: 1.,
p.state_in[0]: state_in[0],
p.state_in[1]: state_in[1],
}
outputs_list = [loss]
if train:
outputs_list += [train_op]
else:
outputs_list += [p.vf[-1]]
fetched = session.run(outputs_list, feed_dict=feed_dict)
if train:
val_loss, _ = fetched
return val_loss
else:
val_loss, val_vf = fetched
return val_loss, val_vf
n_epochs = 10
n_train = int(n_samples * .8)
n_val = n_samples - n_train
verbose = False
for epoch in range(n_epochs):
# train
train_loss_mean = 0
for sidx in range(n_train):
train_loss = run_sample(predictor, x[sidx, :, :],
y[sidx].reshape(1, -1),
predictor.state_init)
train_loss_mean += train_loss / n_train
# val
val_loss_mean = 0
for sidx in range(n_val):
val_loss, val_vf = run_sample(predictor,
x[sidx, :, :],
y[sidx].reshape(1, -1),
predictor.state_init,
train=False)
val_loss_mean += val_loss / n_val
# print('x: {}\ny: {}\ny_pred: {}'.format(
# x[sidx,:,:], y[sidx].reshape(1,-1), val_vf))
# input()
# report
if verbose:
print(
'epoch: {} / {}\ttrain loss: {}\tval loss: {}'.format(
epoch, n_epochs, train_loss_mean, val_loss_mean))
self.assertTrue(train_loss_mean < 1e-2)
self.assertTrue(val_loss_mean < 1e-2)
import random
from behave import then, step
from utils import random_string, filter_list_by_parameter_start_with, validate_json
from hamcrest import *
import requests
from test_config import TestConfig
from datetime import datetime
from random import choice
dataset_name_prefix = "test_dataset_name_"
orb_url = TestConfig.configs().get('orb_url')
configs = TestConfig.configs()
@step("{amount_of_datasets} new dataset is created using the policy, {group_order} group and {amount_of_sinks}"
" {sink_number}")
def create_new_dataset(context, amount_of_datasets, group_order, amount_of_sinks, sink_number):
assert_that(sink_number, any_of(equal_to("sink"), equal_to("sinks")), "Unexpected value for sink")
assert_that(group_order, any_of(equal_to("first"), equal_to("second"), equal_to("last"), equal_to("an existing")),
"Unexpected value for group.")
if group_order == "an existing":
groups_to_be_used = random.sample(list(context.agent_groups.keys()), int(amount_of_datasets))
else:
assert_that(str(amount_of_datasets), equal_to(str(1)), "For more than one dataset, pass 'an existing' as group"
" parameter")
order_convert = {"first": 0, "last": -1, "second": 1}
groups_to_be_used = [list(context.agent_groups.keys())[order_convert[group_order]]]
from users import authenticate
from behave import given, when, then, step
from test_config import TestConfig
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from ui_utils import go_to_page, input_text_by_id
from hamcrest import *
configs = TestConfig.configs()
user_email = configs.get('email')
user_password = configs.get('password')
orb_url = configs.get('orb_url')
@given("the Orb user logs in through the UI")
def logs_in_orb_ui(context):
orb_page(context)
use_credentials(context)
check_home_page(context)
context.token = authenticate(user_email, user_password)['token']
@step("that the user is on the orb page")
def orb_page(context):
current_url = go_to_page(orb_url, context)
assert_that(current_url, equal_to(f"{orb_url}/auth/login"),
"user not enabled to access orb login page")
@when("the Orb user logs in Orb UI")
def use_credentials(context):
def test_prediction_long_term_hard_brake(self):
config = TestConfig()
config.n_global_steps = 20000
config.env_id = 'HeuristicRiskEnv-v0'
config.discount = 0. # 599. / 600
config.max_timesteps = 10000
config.prime_timesteps = 50
config.learning_rate = 1e-3
config.adam_beta1 = .995
config.adam_beta2 = .999
config.dropout_keep_prob = 1.
config.l2_reg = 0.
config.local_steps_per_update = 20
config.hidden_layer_sizes = [32, 16]
config.hard_brake_threshold = -3.
config.hard_brake_n_past_frames = 1
config.target_loss_index = 3
config.loss_type = 'mse'
env = build_envs.create_env(config)
test_state = env.reset()
summary_writer = tf.summary.FileWriter('/tmp/test')
with tf.Session() as sess:
trainer = async_td.AsyncTD(env, 0, config)
sess.run(tf.global_variables_initializer())
sess.run(trainer.sync)
trainer.start(sess, summary_writer)
global_step = sess.run(trainer.global_step)
c, h = trainer.network.get_initial_features()
while global_step < config.n_global_steps:
trainer.process(sess)
global_step = sess.run(trainer.global_step)
value = trainer.network.value(test_state, c, h)
print(value)
def test_heuristic_deterministic_case(self):
config = TestConfig()
config.n_global_steps = 50000
config.max_timesteps = 50
config.env_id = 'BayesNetRiskEnv-v0'
config.discount = 1. # 49. / 50
config.value_dim = 5
config.adam_beta1 = .9
config.local_steps_per_update = 100
config.hidden_layer_sizes = [128]
config.learning_rate = 1e-3
config.learning_rate_end = 5e-6
config.loss_type = 'mse'
config.target_loss_index = 1
config.validation_dataset_filepath = '/Users/wulfebw/Dropbox/School/Stanford/research/risk/risk_prediction/data/experiments/heuristic_determinstic_1_lane_5_sec/data/subselect_proposal_prediction_data.h5'
config.max_validation_samples = 1
config.validate_every = 1000
config.visualize_every = 10000
config.summarize_features = True
validation.transfer_dataset_settings_to_config(
config.validation_dataset_filepath, config)
config.base_bn_filepath = '/Users/wulfebw/Dropbox/School/Stanford/research/risk/risk_prediction/data/experiments/heuristic_determinstic_1_lane_5_sec/data/base_bn_filepath.h5'
config.base_prop_filepath = '/Users/wulfebw/Dropbox/School/Stanford/research/risk/risk_prediction/data/experiments/heuristic_determinstic_1_lane_5_sec/data/prop_bn_filepath.h5'
config.max_validation_samples = 1000
# config.roadway_radius = 400.
# config.roadway_length = 100.
# config.lon_accel_std_dev = 0.
# config.lat_accel_std_dev = 0.
# config.overall_response_time = .2
# config.lon_response_time = .0
# config.err_p_a_to_i = .15
# config.err_p_i_to_a = .3
# config.max_num_vehicles = 50
# config.min_num_vehicles = 50
# config.hard_brake_threshold = -3.
# config.hard_brake_n_past_frames = 2
# config.min_base_speed = 30.
# config.max_base_speed = 30.
# config.min_vehicle_length = 5.
# config.max_vehicle_length = 5.
# config.min_vehicle_width = 2.5
# config.max_vehicle_width = 2.5
# config.min_init_dist = 10.
# config.heuristic_behavior_type = "normal"
# build env
env = build_envs.create_env(config)
dataset = validation.build_dataset(config, env)
print('mean validation targets: {}'.format(np.mean(dataset.y, axis=0)))
# run it
summary_writer = tf.summary.FileWriter('/tmp/test')
avg_loss = -1
last_global_step_val = 0
with tf.Session() as sess:
trainer = async_td.AsyncTD(env, 0, config)
sess.run(tf.global_variables_initializer())
sess.run(trainer.sync)
trainer.start(sess, summary_writer)
global_step = sess.run(trainer.global_step)
while global_step < config.n_global_steps:
trainer.process(sess)
if (global_step -
last_global_step_val) > config.validate_every:
avg_loss = trainer.validate(sess, dataset)
last_global_step_val = global_step
global_step = sess.run(trainer.global_step)
def test_validate(self):
# config
config = TestConfig()
config.n_global_steps = 5000
config.env_id = 'SeqSumDebugEnv-v0'
config.discount = 1.
config.value_dim = 1
config.adam_beta1 = .99
config.local_steps_per_update = 100000
config.hidden_layer_sizes = [128]
config.learning_rate = 5e-4
config.learning_rate_end = 5e-6
config.loss_type = 'mse'
config.target_loss_index = None
# build env
env = gym.make(config.env_id)
# build validation set
# in this case just sequences of either 1s or 0s (const per sequence)
# e.g.,
# horizon = 4, and seeing 1s: [1 1 1 1]
# then after seeing [1 1], should predict a value from this point of 2
# because that is the amount of reward expect to accrue in the future
horizon = 4
n_samples = 2
n_timesteps = 2 # predict after seeing this many timesteps
input_dim = 1
# half ones and half neg ones
x = np.ones((n_samples, n_timesteps, input_dim))
x[int(n_samples / 2):] = -1
# expect value to be how many timesteps have left * -1 or 1
y = x[:, 0, :] * (horizon - n_timesteps + 1)
w = np.ones(n_samples)
dataset = validation.Dataset(x, y, w)
# run it
summary_writer = tf.summary.FileWriter('/tmp/test')
avg_loss = -1
with tf.Session() as sess:
trainer = async_td.AsyncTD(env, 0, config)
sess.run(tf.global_variables_initializer())
sess.run(trainer.sync)
trainer.start(sess, summary_writer)
global_step = sess.run(trainer.global_step)
while global_step < config.n_global_steps:
trainer.process(sess)
if global_step % 10 == 0:
avg_loss = trainer.validate(sess, dataset)
global_step = sess.run(trainer.global_step)
self.assertTrue(avg_loss < .1)
def __init__(self, test_path='', test_config=None):
"""Create a new instance of a TestCase. Must be called by inheriting
classes.
Keyword Arguments:
test_path Optional parameter that specifies the path where this test
resides
test_config Loaded YAML test configuration
"""
if not len(test_path):
self.test_name = os.path.dirname(sys.argv[0])
else:
self.test_name = test_path
# We're not using /tmp//full//test//name because it gets so long that
# it doesn't fit in AF_UNIX paths (limited to around 108 chars) used
# for the rasterisk CLI connection. As a quick fix, we hash the path
# using md5, to make it unique enough.
self.realbase = self.test_name.replace("tests/", "", 1)
self.base = md5(self.realbase).hexdigest()
# We provide a symlink to it from a named path.
named_dir = os.path.join(Asterisk.test_suite_root, self.realbase)
try:
os.makedirs(os.path.dirname(named_dir))
except OSError:
pass
try:
join_path = os.path.relpath(
os.path.join(Asterisk.test_suite_root, self.base),
os.path.dirname(named_dir)
)
os.symlink(join_path, named_dir)
except OSError:
pass
self.ast = []
self.ami = []
self.fastagi = []
self.base_config_path = None
self.reactor_timeout = 30
self.passed = None
self.fail_tokens = []
self.timeout_id = None
self.global_config = TestConfig(os.getcwd())
self.test_config = TestConfig(self.test_name, self.global_config)
self.condition_controller = None
self.pcap = None
self.pcapfilename = None
self.create_pcap = False
self._stopping = False
self.testlogdir = self._set_test_log_directory()
self.ast_version = AsteriskVersion()
self._start_callbacks = []
self._stop_callbacks = []
self._ami_callbacks = []
self._pcap_callbacks = []
self._stop_deferred = None
log_full = True
log_messages = True
if os.getenv("VALGRIND_ENABLE") == "true":
self.reactor_timeout *= 20
# Pull additional configuration from YAML config if possible
if test_config:
if 'config-path' in test_config:
self.base_config_path = test_config['config-path']
if 'reactor-timeout' in test_config:
self.reactor_timeout = test_config['reactor-timeout']
self.ast_conf_options = test_config.get('ast-config-options')
log_full = test_config.get('log-full', True)
log_messages = test_config.get('log-messages', True)
else:
self.ast_conf_options = None
os.makedirs(self.testlogdir)
# Set up logging
setup_logging(self.testlogdir, log_full, log_messages)
LOGGER.info("Executing " + self.test_name)
if PCAP_AVAILABLE and self.create_pcap:
self.pcapfilename = os.path.join(self.testlogdir, "dumpfile.pcap")
self.pcap = self.create_pcap_listener(dumpfile=self.pcapfilename)
self._setup_conditions()
# Enable twisted logging
observer = log.PythonLoggingObserver()
observer.start()
reactor.callWhenRunning(self._run)
class TestCase(object):
"""The base class object for python tests. This class provides common
functionality to all tests, including management of Asterisk instances, AMI,
twisted reactor, and various other utilities.
"""
def __init__(self, test_path='', test_config=None):
"""Create a new instance of a TestCase. Must be called by inheriting
classes.
Keyword Arguments:
test_path Optional parameter that specifies the path where this test
resides
test_config Loaded YAML test configuration
"""
if not len(test_path):
self.test_name = os.path.dirname(sys.argv[0])
else:
self.test_name = test_path
# We're not using /tmp//full//test//name because it gets so long that
# it doesn't fit in AF_UNIX paths (limited to around 108 chars) used
# for the rasterisk CLI connection. As a quick fix, we hash the path
# using md5, to make it unique enough.
self.realbase = self.test_name.replace("tests/", "", 1)
self.base = md5(self.realbase).hexdigest()
# We provide a symlink to it from a named path.
named_dir = os.path.join(Asterisk.test_suite_root, self.realbase)
try:
os.makedirs(os.path.dirname(named_dir))
except OSError:
pass
try:
join_path = os.path.relpath(
os.path.join(Asterisk.test_suite_root, self.base),
os.path.dirname(named_dir)
)
os.symlink(join_path, named_dir)
except OSError:
pass
self.ast = []
self.ami = []
self.fastagi = []
self.base_config_path = None
self.reactor_timeout = 30
self.passed = None
self.fail_tokens = []
self.timeout_id = None
self.global_config = TestConfig(os.getcwd())
self.test_config = TestConfig(self.test_name, self.global_config)
self.condition_controller = None
self.pcap = None
self.pcapfilename = None
self.create_pcap = False
self._stopping = False
self.testlogdir = self._set_test_log_directory()
self.ast_version = AsteriskVersion()
self._start_callbacks = []
self._stop_callbacks = []
self._ami_callbacks = []
self._pcap_callbacks = []
self._stop_deferred = None
log_full = True
log_messages = True
if os.getenv("VALGRIND_ENABLE") == "true":
self.reactor_timeout *= 20
# Pull additional configuration from YAML config if possible
if test_config:
if 'config-path' in test_config:
self.base_config_path = test_config['config-path']
if 'reactor-timeout' in test_config:
self.reactor_timeout = test_config['reactor-timeout']
self.ast_conf_options = test_config.get('ast-config-options')
log_full = test_config.get('log-full', True)
log_messages = test_config.get('log-messages', True)
else:
self.ast_conf_options = None
os.makedirs(self.testlogdir)
# Set up logging
setup_logging(self.testlogdir, log_full, log_messages)
LOGGER.info("Executing " + self.test_name)
if PCAP_AVAILABLE and self.create_pcap:
self.pcapfilename = os.path.join(self.testlogdir, "dumpfile.pcap")
self.pcap = self.create_pcap_listener(dumpfile=self.pcapfilename)
self._setup_conditions()
# Enable twisted logging
observer = log.PythonLoggingObserver()
observer.start()
reactor.callWhenRunning(self._run)
def _set_test_log_directory(self):
"""Determine which logging directory we should use for this test run
Returns:
The full path that should be used as the directory for all log data
"""
i = 1
base_path = os.path.join(Asterisk.test_suite_root, self.base)
while os.path.isdir(os.path.join(base_path, "run_%d" % i)):
i += 1
full_path = os.path.join(base_path, "run_%d" % i)
return full_path
def _setup_conditions(self):
"""Register pre and post-test conditions.
Note that we have to first register condition checks without related
conditions, so that those that have dependencies can find them
"""
self.condition_controller = TestConditionController(self.test_config,
self.ast,
self.stop_reactor)
global_conditions = self.global_config.get_conditions()
conditions = self.test_config.get_conditions()
# Get those global conditions that are not in the self conditions
for g_cond in global_conditions:
disallowed = [i for i in conditions
if i[0].get_name() == g_cond[0].get_name()
and i[1] == g_cond[1]]
if len(disallowed) == 0:
conditions.append(g_cond)
for cond in conditions:
# cond is a 3-tuple of object, pre-post type, and related name
obj, pre_post_type, related_name = cond
if pre_post_type == "PRE":
self.condition_controller.register_pre_test_condition(obj)
elif pre_post_type == "POST":
self.condition_controller.register_post_test_condition(obj, related_name)
else:
msg = "Unknown condition type [%s]" % pre_post_type
LOGGER.warning(msg)
self.condition_controller.register_observer(
self.handle_condition_failure, 'Failed')
def get_asterisk_hosts(self, count):
"""Return a list of host dictionaries for Asterisk instances
Keyword Arguments:
count The number of Asterisk instances to create, if no remote
Asterisk instances have been specified
"""
if (self.global_config.config and
'asterisk-instances' in self.global_config.config):
asterisks = self.global_config.config.get('asterisk-instances')
else:
asterisks = [{'num': i + 1, 'host': '127.0.0.%d' % (i + 1)}
for i in range(count)]
return asterisks
def create_asterisk(self, count=1, base_configs_path=None):
"""Create n instances of Asterisk
Note: if the instances of Asterisk being created are remote, the
keyword arguments to this function are ignored.
Keyword arguments:
count The number of Asterisk instances to create. Each
Asterisk instance will be hosted on 127.0.0.x, where x
is the 1-based index of the instance created.
base_configs_path Provides common configuration for Asterisk instances
to use. This is useful for certain test types that use
the same configuration all the time. This
configuration can be overwritten by individual tests,
however.
"""
for i, ast_config in enumerate(self.get_asterisk_hosts(count)):
local_num = ast_config.get('num')
host = ast_config.get('host')
if not host:
msg = "Cannot manage Asterisk instance without 'host'"
raise Exception(msg)
if local_num:
LOGGER.info("Creating Asterisk instance %d" % local_num)
ast_instance = Asterisk(base=self.testlogdir, host=host,
ast_conf_options=self.ast_conf_options)
else:
LOGGER.info("Managing Asterisk instance at %s" % host)
ast_instance = Asterisk(base=self.testlogdir, host=host,
remote_config=ast_config)
self.ast.append(ast_instance)
self.condition_controller.register_asterisk_instance(self.ast[i])
if local_num:
# If a base configuration for this Asterisk instance has been
# provided, install it first
if base_configs_path is None:
base_configs_path = self.base_config_path
if base_configs_path:
ast_dir = "%s/ast%d" % (base_configs_path, local_num)
self.ast[i].install_configs(ast_dir,
self.test_config.get_deps())
# Copy test specific config files
self.ast[i].install_configs("%s/configs/ast%d" %
(self.test_name, local_num),
self.test_config.get_deps())
def create_ami_factory(self, count=1, username="******", secret="mysecret",
port=5038):
"""Create n instances of AMI. Each AMI instance will attempt to connect
to a previously created instance of Asterisk. When a connection is
complete, the ami_connect method will be called.
Keyword arguments:
count The number of instances of AMI to create
username The username to login with
secret The password to login with
port The port to connect over
"""
def on_reconnect(login_deferred):
"""Called if the connection is lost and re-made"""
login_deferred.addCallbacks(self._ami_connect, self.ami_login_error)
for i, ast_config in enumerate(self.get_asterisk_hosts(count)):
host = ast_config.get('host')
ami_config = ast_config.get('ami', {})
actual_user = ami_config.get('username', username)
actual_secret = ami_config.get('secret', secret)
actual_port = ami_config.get('port', port)
self.ami.append(None)
LOGGER.info("Creating AMIFactory %d to %s" % ((i + 1), host))
try:
ami_factory = manager.AMIFactory(actual_user, actual_secret, i,
on_reconnect=on_reconnect)
except:
ami_factory = manager.AMIFactory(actual_user, actual_secret, i)
deferred = ami_factory.login(ip=host, port=actual_port)
deferred.addCallbacks(self._ami_connect, self.ami_login_error)
def create_fastagi_factory(self, count=1):
"""Create n instances of AGI. Each AGI instance will attempt to connect
to a previously created instance of Asterisk. When a connection is
complete, the fastagi_connect method will be called.
Keyword arguments:
count The number of instances of AGI to create
"""
for i, ast_config in enumerate(self.get_asterisk_hosts(count)):
host = ast_config.get('host')
self.fastagi.append(None)
LOGGER.info("Creating FastAGI Factory %d" % (i + 1))
fastagi_factory = fastagi.FastAGIFactory(self.fastagi_connect)
reactor.listenTCP(4573, fastagi_factory,
self.reactor_timeout, host)
def fastagi_connect(self, agi):
"""Callback called by starpy when FastAGI connects
This method should be overridden by derived classes that use
create_fastagi_factory
Keyword arguments:
agi The AGI manager
"""
pass
def create_pcap_listener(self, device=None, bpf_filter=None, dumpfile=None,
snaplen=None, buffer_size=None):
"""Create a single instance of a pcap listener.
Keyword arguments:
device The interface to listen on. Defaults to the first interface
beginning with 'lo'.
bpf_filter BPF (filter) describing what packets to match, i.e.
"port 5060"
dumpfile The filename at which to save a pcap capture
snaplen Number of bytes to capture from each packet. Defaults to
65535.
buffer_size The ring buffer size. Defaults to 0.
"""
if not PCAP_AVAILABLE:
msg = ("PCAP not available on this machine. "
"Test config is missing pcap dependency.")
raise Exception(msg)
# TestCase will create a listener for logging purposes, and individual
# tests can create their own. Tests may only want to watch a specific
# port, while a general logger will want to watch more general traffic
# which can be filtered later.
return PcapListener(device, bpf_filter, dumpfile, self._pcap_callback,
snaplen, buffer_size)
def start_asterisk(self):
"""This method will be called when the reactor is running, but
immediately before instances of Asterisk are launched. Derived classes
can override this if needed.
"""
pass
def _start_asterisk(self):
"""Start the instances of Asterisk that were previously created. See
create_asterisk. Note that this should be the first thing called
when the reactor has started to run
"""
def __check_success_failure(result):
"""Make sure the instances started properly"""
for (success, value) in result:
if not success:
LOGGER.error(value.getErrorMessage())
self.stop_reactor()
return result
def __perform_pre_checks(result):
"""Execute the pre-condition checks"""
deferred = self.condition_controller.evaluate_pre_checks()
if deferred is None:
return result
else:
return deferred
def __run_callback(result):
"""Notify the test that we are running"""
for callback in self._start_callbacks:
callback(self.ast)
self.run()
return result
# Call the method that derived objects can override
self.start_asterisk()
# Gather up the deferred objects from each of the instances of Asterisk
# and wait until all are finished before proceeding
start_defers = []
for index, ast in enumerate(self.ast):
LOGGER.info("Starting Asterisk instance %d" % (index + 1))
temp_defer = ast.start(self.test_config.get_deps())
start_defers.append(temp_defer)
deferred = defer.DeferredList(start_defers, consumeErrors=True)
deferred.addCallback(__check_success_failure)
deferred.addCallback(__perform_pre_checks)
deferred.addCallback(__run_callback)
def stop_asterisk(self):
"""This method is called when the reactor is running but immediately
before instances of Asterisk are stopped. Derived classes can override
this method if needed.
"""
pass
def _stop_asterisk(self):
"""Stops the instances of Asterisk.
Returns:
A deferred object that can be used to be notified when all instances
of Asterisk have stopped.
"""
def __check_success_failure(result):
"""Make sure the instances stopped properly"""
for (success, value) in result:
if not success:
LOGGER.warning(value.getErrorMessage())
# This should already be called when the reactor is being
# terminated. If we couldn't stop the instance of Asterisk,
# there isn't much else to do here other then complain
self._stop_deferred.callback(self)
return result
def __stop_instances(result):
"""Stop the instances"""
# Call the overridable method now
self.stop_asterisk()
# Gather up the stopped defers; check success failure of stopping
# when all instances of Asterisk have stopped
stop_defers = []
for index, ast in enumerate(self.ast):
LOGGER.info("Stopping Asterisk instance %d" % (index + 1))
temp_defer = ast.stop()
stop_defers.append(temp_defer)
defer.DeferredList(stop_defers).addCallback(
__check_success_failure)
return result
self._stop_deferred = defer.Deferred()
deferred = self.condition_controller.evaluate_post_checks()
if deferred:
deferred.addCallback(__stop_instances)
else:
__stop_instances(None)
return self._stop_deferred
def stop_reactor(self):
"""Stop the reactor and cancel the test."""
def __stop_reactor(result):
"""Called when the Asterisk instances are stopped"""
LOGGER.info("Stopping Reactor")
if reactor.running:
try:
reactor.stop()
except twisted_error.ReactorNotRunning:
# Something stopped it between our checks - at least we're
# stopped
pass
return result
if not self._stopping:
self._stopping = True
deferred = self._stop_asterisk()
for callback in self._stop_callbacks:
deferred.addCallback(callback)
deferred.addCallback(__stop_reactor)
def _reactor_timeout(self):
"""A wrapper function for stop_reactor(), so we know when a reactor
timeout has occurred.
"""
LOGGER.warning("Reactor timeout: '%s' seconds" % self.reactor_timeout)
self.on_reactor_timeout()
self.stop_reactor()
def on_reactor_timeout(self):
"""Virtual method called when reactor times out"""
pass
def _run(self):
"""Private entry point called when the reactor first starts up. This
needs to first ensure that Asterisk is fully up and running before
moving on.
"""
if self.ast:
self._start_asterisk()
else:
# If no instances of Asterisk are needed, go ahead and just run
self.run()
def run(self):
"""Base implementation of the test execution method, run. Derived
classes should override this and start their Asterisk dependent logic
from this method.
Derived classes must call this implementation, as this method provides a
fail out mechanism in case the test hangs.
"""
if self.reactor_timeout > 0:
self.timeout_id = reactor.callLater(self.reactor_timeout,
self._reactor_timeout)
def ami_login_error(self, reason):
"""Handler for login errors into AMI. This will stop the test.
Keyword arguments:
ami The instance of AMI that raised the login error
"""
LOGGER.error("Error logging into AMI: %s" % reason.getErrorMessage())
LOGGER.error(reason.getTraceback())
self.stop_reactor()
return reason
def ami_connect(self, ami):
"""Virtual method used after create_ami_factory() successfully logs into
the Asterisk AMI.
"""
pass
def _ami_connect(self, ami):
"""Callback when AMI first connects"""
LOGGER.info("AMI Connect instance %s" % (ami.id + 1))
self.ami[ami.id] = ami
try:
for callback in self._ami_callbacks:
callback(ami)
self.ami_connect(ami)
except:
LOGGER.error("Exception raised in ami_connect:")
LOGGER.error(traceback.format_exc())
self.stop_reactor()
return ami
def pcap_callback(self, packet):
"""Virtual method used to receive captured packets."""
pass
def _pcap_callback(self, packet):
"""Packet capture callback"""
self.pcap_callback(packet)
for callback in self._pcap_callbacks:
callback(packet)
def handle_originate_failure(self, reason):
"""Fail the test on an Originate failure
Convenience callback handler for twisted deferred errors for an AMI
originate call. Derived classes can choose to add this handler to
originate calls in order to handle them safely when they fail.
This will stop the test if called.
Keyword arguments:
reason The reason the originate failed
"""
LOGGER.error("Error sending originate: %s" % reason.getErrorMessage())
LOGGER.error(reason.getTraceback())
self.stop_reactor()
return reason
def reset_timeout(self):
"""Resets the reactor timeout"""
if self.timeout_id is not None:
original_time = datetime.fromtimestamp(self.timeout_id.getTime())
self.timeout_id.reset(self.reactor_timeout)
new_time = datetime.fromtimestamp(self.timeout_id.getTime())
msg = ("Reactor timeout originally scheduled for %s, "
"rescheduled for %s" % (str(original_time), str(new_time)))
LOGGER.info(msg)
def handle_condition_failure(self, test_condition):
"""Callback handler for condition failures"""
if test_condition.pass_expected:
msg = ("Test Condition %s failed; setting passed status to False" %
test_condition.get_name())
LOGGER.error(msg)
self.passed = False
else:
msg = ("Test Condition %s failed but expected failure was set; "
"test status not modified" % test_condition.get_name())
LOGGER.info(msg)
def evaluate_results(self):
"""Return whether or not the test has passed"""
while len(self.fail_tokens):
fail_token = self.fail_tokens.pop(0)
LOGGER.error("Fail token present: %s" % fail_token['message'])
self.passed = False
return self.passed
def register_pcap_observer(self, callback):
"""Register an observer that will be called when a packet is received
from a created pcap listener
Keyword Arguments:
callback The callback to receive the packet. The callback function
should take in a single parameter, which will be the packet
received
"""
self._pcap_callbacks.append(callback)
def register_start_observer(self, callback):
"""Register an observer that will be called when all Asterisk instances
have started
Keyword Arguments:
callback The deferred callback function to be called when all instances
of Asterisk have started. The callback should take no
parameters.
"""
self._start_callbacks.append(callback)
def register_stop_observer(self, callback):
"""Register an observer that will be called when Asterisk is stopped
Keyword Arguments:
callback The deferred callback function to be called when Asterisk is
stopped
Note:
This appends a callback to the deferred chain of callbacks executed when
all instances of Asterisk are stopped.
"""
self._stop_callbacks.append(callback)
def register_ami_observer(self, callback):
"""Register an observer that will be called when TestCase connects with
Asterisk over the Manager interface
Parameters:
callback The deferred callback function to be called when AMI connects
"""
self._ami_callbacks.append(callback)
def create_fail_token(self, message):
"""Add a fail token to the test. If any fail tokens exist at the end of
the test, the test will fail.
Keyword Arguments:
message A text message describing the failure
Returns:
A token that can be removed from the test at a later time, if the test
should pass
"""
fail_token = {'uuid': uuid.uuid4(), 'message': message}
self.fail_tokens.append(fail_token)
return fail_token
def remove_fail_token(self, fail_token):
"""Remove a fail token from the test.
Keyword Arguments:
fail_token A previously created fail token to be removed from the test
"""
if not fail_token in self.fail_tokens:
LOGGER.warning('Attempted to remove an unknown fail token: %s',
fail_token['message'])
self.passed = False
return
self.fail_tokens.remove(fail_token)
def set_passed(self, value):
"""Accumulate pass/fail value.
If a test module has already claimed that the test has failed, then this
method will ignore any further attempts to change the pass/fail status.
"""
if self.passed is False:
return
self.passed = value
def test_prediction_across_target_variance(val_x,
val_y,
sigma=0,
n_mc=1,
hidden_layer_sizes=[32, 32],
n_epochs=50,
n_samples=100,
input_dim=1,
n_timesteps=2):
config = TestConfig()
config.hidden_layer_sizes = hidden_layer_sizes
config.value_dim = 1
config.learning_rate = 1e-3
config.n_epochs = n_epochs
# simple dataset
x, y = generate_data(sigma, n_mc, n_samples, n_timesteps, input_dim)
val_losses = []
with tf.Session() as session:
predictor = model.LSTMPredictor((input_dim, ), config)
target_placeholder = tf.placeholder(tf.float32, [None, 1], 'target')
loss = tf.reduce_sum((predictor.vf[-1] - target_placeholder)**2)
opt = tf.train.AdamOptimizer(config.learning_rate)
train_op = opt.minimize(loss)
session.run(tf.global_variables_initializer())
def run_sample(p, x, y, state_in, train=True):
feed_dict = {
p.x: x,
target_placeholder: y,
p.dropout_keep_prob_ph: 1.,
p.state_in[0]: state_in[0],
p.state_in[1]: state_in[1],
}
outputs_list = [loss]
if train:
outputs_list += [train_op]
else:
outputs_list += [p.vf[-1]]
fetched = session.run(outputs_list, feed_dict=feed_dict)
if train:
val_loss, _ = fetched
return val_loss
else:
val_loss, val_vf = fetched
return val_loss, val_vf
n_val = len(val_x)
for epoch in range(n_epochs):
# train
train_loss_mean = 0
for sidx in range(n_samples):
train_loss = run_sample(predictor, x[sidx, :, :],
y[sidx].reshape(1, -1),
predictor.state_init)
train_loss_mean += train_loss / n_samples
# val
val_loss_mean = 0
for sidx in range(n_val):
val_loss, val_vf = run_sample(predictor,
val_x[sidx, :, :],
val_y[sidx].reshape(1, -1),
predictor.state_init,
train=False)
val_loss_mean += val_loss / n_val
# print('x: {}\ny: {}\ny_pred: {}'.format(
# x[sidx,:,:], y[sidx].reshape(1,-1), val_vf))
# input()
# report, track
val_losses.append(val_loss_mean)
print('epoch: {} / {}\ttrain loss: {}\tval loss: {}'.format(
epoch, n_epochs, train_loss_mean, val_loss_mean))
return val_losses
class TestCase(object):
"""The base class object for python tests. This class provides common
functionality to all tests, including management of Asterisk instances, AMI,
twisted reactor, and various other utilities.
"""
def __init__(self, test_path='', test_config=None):
"""Create a new instance of a TestCase. Must be called by inheriting
classes.
Keyword Arguments:
test_path Optional parameter that specifies the path where this test
resides
test_config Loaded YAML test configuration
"""
if not len(test_path):
self.test_name = os.path.dirname(sys.argv[0])
else:
self.test_name = test_path
# We're not using /tmp//full//test//name because it gets so long that
# it doesn't fit in AF_UNIX paths (limited to around 108 chars) used
# for the rasterisk CLI connection. As a quick fix, we hash the path
# using md5, to make it unique enough.
self.realbase = self.test_name.replace("tests/", "", 1)
self.base = md5(self.realbase).hexdigest()
# We provide a symlink to it from a named path.
named_dir = os.path.join(Asterisk.test_suite_root, self.realbase)
try:
os.makedirs(os.path.dirname(named_dir))
except OSError:
pass
try:
join_path = os.path.relpath(
os.path.join(Asterisk.test_suite_root, self.base),
os.path.dirname(named_dir)
)
os.symlink(join_path, named_dir)
except OSError:
pass
self.ast = []
self.ami = []
self.fastagi = []
self.base_config_path = None
self.reactor_timeout = 30
self.passed = None
self.fail_tokens = []
self.timeout_id = None
self.global_config = TestConfig(os.getcwd())
self.test_config = TestConfig(self.test_name, self.global_config)
self.condition_controller = None
self.pcap = None
self.pcapfilename = None
self.create_pcap = False
self._stopping = False
self.testlogdir = self._set_test_log_directory()
self.ast_version = AsteriskVersion()
self._start_callbacks = []
self._stop_callbacks = []
self._ami_callbacks = []
self._pcap_callbacks = []
self._stop_deferred = None
log_full = True
log_messages = True
if os.getenv("VALGRIND_ENABLE") == "true":
self.reactor_timeout *= 20
# Pull additional configuration from YAML config if possible
if test_config:
if 'config-path' in test_config:
self.base_config_path = test_config['config-path']
if 'reactor-timeout' in test_config:
self.reactor_timeout = test_config['reactor-timeout']
self.ast_conf_options = test_config.get('ast-config-options')
log_full = test_config.get('log-full', True)
log_messages = test_config.get('log-messages', True)
else:
self.ast_conf_options = None
os.makedirs(self.testlogdir)
# Set up logging
setup_logging(self.testlogdir, log_full, log_messages)
LOGGER.info("Executing " + self.test_name)
if PCAP_AVAILABLE and self.create_pcap:
self.pcapfilename = os.path.join(self.testlogdir, "dumpfile.pcap")
self.pcap = self.create_pcap_listener(dumpfile=self.pcapfilename)
self._setup_conditions()
# Enable twisted logging
observer = log.PythonLoggingObserver()
observer.start()
reactor.callWhenRunning(self._run)
def _set_test_log_directory(self):
"""Determine which logging directory we should use for this test run
Returns:
The full path that should be used as the directory for all log data
"""
i = 1
base_path = os.path.join(Asterisk.test_suite_root, self.base)
while os.path.isdir(os.path.join(base_path, "run_%d" % i)):
i += 1
full_path = os.path.join(base_path, "run_%d" % i)
return full_path
def _setup_conditions(self):
"""Register pre and post-test conditions.
Note that we have to first register condition checks without related
conditions, so that those that have dependencies can find them
"""
self.condition_controller = TestConditionController(self.test_config,
self.ast,
self.stop_reactor)
global_conditions = self.global_config.get_conditions()
conditions = self.test_config.get_conditions()
# Get those global conditions that are not in the self conditions
for g_cond in global_conditions:
disallowed = [i for i in conditions
if i[0].get_name() == g_cond[0].get_name() and
i[1] == g_cond[1]]
if len(disallowed) == 0:
conditions.append(g_cond)
for cond in conditions:
# cond is a 3-tuple of object, pre-post type, and related name
obj, pre_post_type, related_name = cond
if pre_post_type == "PRE":
self.condition_controller.register_pre_test_condition(obj)
elif pre_post_type == "POST":
self.condition_controller.register_post_test_condition(obj, related_name)
else:
msg = "Unknown condition type [%s]" % pre_post_type
LOGGER.warning(msg)
self.condition_controller.register_observer(
self.handle_condition_failure, 'Failed')
def get_asterisk_hosts(self, count):
"""Return a list of host dictionaries for Asterisk instances
Keyword Arguments:
count The number of Asterisk instances to create, if no remote
Asterisk instances have been specified
"""
if (self.global_config.config and
'asterisk-instances' in self.global_config.config):
asterisks = self.global_config.config.get('asterisk-instances')
else:
asterisks = [{'num': i + 1, 'host': '127.0.0.%d' % (i + 1)}
for i in range(count)]
return asterisks
def create_asterisk(self, count=1, base_configs_path=None):
"""Create n instances of Asterisk
Note: if the instances of Asterisk being created are remote, the
keyword arguments to this function are ignored.
Keyword arguments:
count The number of Asterisk instances to create. Each
Asterisk instance will be hosted on 127.0.0.x, where x
is the 1-based index of the instance created.
base_configs_path Provides common configuration for Asterisk instances
to use. This is useful for certain test types that use
the same configuration all the time. This
configuration can be overwritten by individual tests,
however.
"""
for i, ast_config in enumerate(self.get_asterisk_hosts(count)):
local_num = ast_config.get('num')
host = ast_config.get('host')
if not host:
msg = "Cannot manage Asterisk instance without 'host'"
raise Exception(msg)
if local_num:
LOGGER.info("Creating Asterisk instance %d" % local_num)
ast_instance = Asterisk(base=self.testlogdir, host=host,
ast_conf_options=self.ast_conf_options)
else:
LOGGER.info("Managing Asterisk instance at %s" % host)
ast_instance = Asterisk(base=self.testlogdir, host=host,
remote_config=ast_config)
self.ast.append(ast_instance)
self.condition_controller.register_asterisk_instance(self.ast[i])
if local_num:
# If a base configuration for this Asterisk instance has been
# provided, install it first
if base_configs_path is None:
base_configs_path = self.base_config_path
if base_configs_path:
ast_dir = "%s/ast%d" % (base_configs_path, local_num)
self.ast[i].install_configs(ast_dir,
self.test_config.get_deps())
# Copy test specific config files
self.ast[i].install_configs("%s/configs/ast%d" %
(self.test_name, local_num),
self.test_config.get_deps())
def create_ami_factory(self, count=1, username="******", secret="mysecret",
port=5038):
"""Create n instances of AMI. Each AMI instance will attempt to connect
to a previously created instance of Asterisk. When a connection is
complete, the ami_connect method will be called.
Keyword arguments:
count The number of instances of AMI to create
username The username to login with
secret The password to login with
port The port to connect over
"""
def on_reconnect(login_deferred):
"""Called if the connection is lost and re-made"""
login_deferred.addCallbacks(self._ami_connect, self.ami_login_error)
for i, ast_config in enumerate(self.get_asterisk_hosts(count)):
host = ast_config.get('host')
ami_config = ast_config.get('ami', {})
actual_user = ami_config.get('username', username)
actual_secret = ami_config.get('secret', secret)
actual_port = ami_config.get('port', port)
self.ami.append(None)
LOGGER.info("Creating AMIFactory %d to %s" % ((i + 1), host))
try:
ami_factory = manager.AMIFactory(actual_user, actual_secret, i,
on_reconnect=on_reconnect)
except:
ami_factory = manager.AMIFactory(actual_user, actual_secret, i)
deferred = ami_factory.login(ip=host, port=actual_port)
deferred.addCallbacks(self._ami_connect, self.ami_login_error)
def create_fastagi_factory(self, count=1):
"""Create n instances of AGI. Each AGI instance will attempt to connect
to a previously created instance of Asterisk. When a connection is
complete, the fastagi_connect method will be called.
Keyword arguments:
count The number of instances of AGI to create
"""
for i, ast_config in enumerate(self.get_asterisk_hosts(count)):
host = ast_config.get('host')
self.fastagi.append(None)
LOGGER.info("Creating FastAGI Factory %d" % (i + 1))
fastagi_factory = fastagi.FastAGIFactory(self.fastagi_connect)
reactor.listenTCP(4573, fastagi_factory,
self.reactor_timeout, host)
def fastagi_connect(self, agi):
"""Callback called by starpy when FastAGI connects
This method should be overridden by derived classes that use
create_fastagi_factory
Keyword arguments:
agi The AGI manager
"""
pass
def create_pcap_listener(self, device=None, bpf_filter=None, dumpfile=None,
snaplen=None, buffer_size=None):
"""Create a single instance of a pcap listener.
Keyword arguments:
device The interface to listen on. Defaults to the first interface
beginning with 'lo'.
bpf_filter BPF (filter) describing what packets to match, i.e.
"port 5060"
dumpfile The filename at which to save a pcap capture
snaplen Number of bytes to capture from each packet. Defaults to
65535.
buffer_size The ring buffer size. Defaults to 0.
"""
if not PCAP_AVAILABLE:
msg = ("PCAP not available on this machine. "
"Test config is missing pcap dependency.")
raise Exception(msg)
# TestCase will create a listener for logging purposes, and individual
# tests can create their own. Tests may only want to watch a specific
# port, while a general logger will want to watch more general traffic
# which can be filtered later.
return PcapListener(device, bpf_filter, dumpfile, self._pcap_callback,
snaplen, buffer_size)
def start_asterisk(self):
"""This method will be called when the reactor is running, but
immediately before instances of Asterisk are launched. Derived classes
can override this if needed.
"""
pass
def _start_asterisk(self):
"""Start the instances of Asterisk that were previously created. See
create_asterisk. Note that this should be the first thing called
when the reactor has started to run
"""
def __check_success_failure(result):
"""Make sure the instances started properly"""
for (success, value) in result:
if not success:
LOGGER.error(value.getErrorMessage())
self.stop_reactor()
return result
def __perform_pre_checks(result):
"""Execute the pre-condition checks"""
deferred = self.condition_controller.evaluate_pre_checks()
if deferred is None:
return result
else:
return deferred
def __run_callback(result):
"""Notify the test that we are running"""
for callback in self._start_callbacks:
callback(self.ast)
self.run()
return result
# Call the method that derived objects can override
self.start_asterisk()
# Gather up the deferred objects from each of the instances of Asterisk
# and wait until all are finished before proceeding
start_defers = []
for index, ast in enumerate(self.ast):
LOGGER.info("Starting Asterisk instance %d" % (index + 1))
temp_defer = ast.start(self.test_config.get_deps())
start_defers.append(temp_defer)
deferred = defer.DeferredList(start_defers, consumeErrors=True)
deferred.addCallback(__check_success_failure)
deferred.addCallback(__perform_pre_checks)
deferred.addCallback(__run_callback)
def stop_asterisk(self):
"""This method is called when the reactor is running but immediately
before instances of Asterisk are stopped. Derived classes can override
this method if needed.
"""
pass
def _stop_asterisk(self):
"""Stops the instances of Asterisk.
Returns:
A deferred object that can be used to be notified when all instances
of Asterisk have stopped.
"""
def __check_success_failure(result):
"""Make sure the instances stopped properly"""
for (success, value) in result:
if not success:
LOGGER.warning(value.getErrorMessage())
# This should already be called when the reactor is being
# terminated. If we couldn't stop the instance of Asterisk,
# there isn't much else to do here other then complain
self._stop_deferred.callback(self)
return result
def __stop_instances(result):
"""Stop the instances"""
# Call the overridable method now
self.stop_asterisk()
# Gather up the stopped defers; check success failure of stopping
# when all instances of Asterisk have stopped
stop_defers = []
for index, ast in enumerate(self.ast):
LOGGER.info("Stopping Asterisk instance %d" % (index + 1))
temp_defer = ast.stop()
stop_defers.append(temp_defer)
defer.DeferredList(stop_defers).addCallback(
__check_success_failure)
return result
self._stop_deferred = defer.Deferred()
deferred = self.condition_controller.evaluate_post_checks()
if deferred:
deferred.addCallback(__stop_instances)
else:
__stop_instances(None)
return self._stop_deferred
def stop_reactor(self):
"""Stop the reactor and cancel the test."""
def __stop_reactor(result):
"""Called when the Asterisk instances are stopped"""
LOGGER.info("Stopping Reactor")
if reactor.running:
try:
reactor.stop()
except twisted_error.ReactorNotRunning:
# Something stopped it between our checks - at least we're
# stopped
pass
return result
if not self._stopping:
self._stopping = True
deferred = self._stop_asterisk()
for callback in self._stop_callbacks:
deferred.addCallback(callback)
deferred.addCallback(__stop_reactor)
def _reactor_timeout(self):
"""A wrapper function for stop_reactor(), so we know when a reactor
timeout has occurred.
"""
if not self._stopping:
LOGGER.warning("Reactor timeout: '%s' seconds" % self.reactor_timeout)
self.on_reactor_timeout()
self.stop_reactor()
else:
LOGGER.info("Reactor timeout: '%s' seconds (ignored; already stopping)"
% self.reactor_timeout)
def on_reactor_timeout(self):
"""Virtual method called when reactor times out"""
pass
def _run(self):
"""Private entry point called when the reactor first starts up. This
needs to first ensure that Asterisk is fully up and running before
moving on.
"""
if self.ast:
self._start_asterisk()
else:
# If no instances of Asterisk are needed, go ahead and just run
self.run()
def run(self):
"""Base implementation of the test execution method, run. Derived
classes should override this and start their Asterisk dependent logic
from this method.
Derived classes must call this implementation, as this method provides a
fail out mechanism in case the test hangs.
"""
if self.reactor_timeout > 0:
self.timeout_id = reactor.callLater(self.reactor_timeout,
self._reactor_timeout)
def ami_login_error(self, reason):
"""Handler for login errors into AMI. This will stop the test.
Keyword arguments:
ami The instance of AMI that raised the login error
"""
LOGGER.error("Error logging into AMI: %s" % reason.getErrorMessage())
LOGGER.error(reason.getTraceback())
self.stop_reactor()
return reason
def ami_connect(self, ami):
"""Virtual method used after create_ami_factory() successfully logs into
the Asterisk AMI.
"""
pass
def _ami_connect(self, ami):
"""Callback when AMI first connects"""
LOGGER.info("AMI Connect instance %s" % (ami.id + 1))
self.ami[ami.id] = ami
try:
for callback in self._ami_callbacks:
callback(ami)
self.ami_connect(ami)
except:
LOGGER.error("Exception raised in ami_connect:")
LOGGER.error(traceback.format_exc())
self.stop_reactor()
return ami
def pcap_callback(self, packet):
"""Virtual method used to receive captured packets."""
pass
def _pcap_callback(self, packet):
"""Packet capture callback"""
self.pcap_callback(packet)
for callback in self._pcap_callbacks:
callback(packet)
def handle_originate_failure(self, reason):
"""Fail the test on an Originate failure
Convenience callback handler for twisted deferred errors for an AMI
originate call. Derived classes can choose to add this handler to
originate calls in order to handle them safely when they fail.
This will stop the test if called.
Keyword arguments:
reason The reason the originate failed
"""
LOGGER.error("Error sending originate: %s" % reason.getErrorMessage())
LOGGER.error(reason.getTraceback())
self.stop_reactor()
return reason
def reset_timeout(self):
"""Resets the reactor timeout"""
if self.timeout_id is not None:
original_time = datetime.fromtimestamp(self.timeout_id.getTime())
self.timeout_id.reset(self.reactor_timeout)
new_time = datetime.fromtimestamp(self.timeout_id.getTime())
msg = ("Reactor timeout originally scheduled for %s, "
"rescheduled for %s" % (str(original_time), str(new_time)))
LOGGER.info(msg)
def handle_condition_failure(self, test_condition):
"""Callback handler for condition failures"""
if test_condition.pass_expected:
msg = ("Test Condition %s failed; setting passed status to False" %
test_condition.get_name())
LOGGER.error(msg)
self.passed = False
else:
msg = ("Test Condition %s failed but expected failure was set; "
"test status not modified" % test_condition.get_name())
LOGGER.info(msg)
def evaluate_results(self):
"""Return whether or not the test has passed"""
while len(self.fail_tokens):
fail_token = self.fail_tokens.pop(0)
LOGGER.error("Fail token present: %s" % fail_token['message'])
self.passed = False
return self.passed
def register_pcap_observer(self, callback):
"""Register an observer that will be called when a packet is received
from a created pcap listener
Keyword Arguments:
callback The callback to receive the packet. The callback function
should take in a single parameter, which will be the packet
received
"""
self._pcap_callbacks.append(callback)
def register_start_observer(self, callback):
"""Register an observer that will be called when all Asterisk instances
have started
Keyword Arguments:
callback The deferred callback function to be called when all instances
of Asterisk have started. The callback should take no
parameters.
"""
self._start_callbacks.append(callback)
def register_stop_observer(self, callback):
"""Register an observer that will be called when Asterisk is stopped
Keyword Arguments:
callback The deferred callback function to be called when Asterisk is
stopped
Note:
This appends a callback to the deferred chain of callbacks executed when
all instances of Asterisk are stopped.
"""
self._stop_callbacks.append(callback)
def register_ami_observer(self, callback):
"""Register an observer that will be called when TestCase connects with
Asterisk over the Manager interface
Parameters:
callback The deferred callback function to be called when AMI connects
"""
self._ami_callbacks.append(callback)
def create_fail_token(self, message):
"""Add a fail token to the test. If any fail tokens exist at the end of
the test, the test will fail.
Keyword Arguments:
message A text message describing the failure
Returns:
A token that can be removed from the test at a later time, if the test
should pass
"""
fail_token = {'uuid': uuid.uuid4(), 'message': message}
self.fail_tokens.append(fail_token)
return fail_token
def remove_fail_token(self, fail_token):
"""Remove a fail token from the test.
Keyword Arguments:
fail_token A previously created fail token to be removed from the test
"""
if fail_token not in self.fail_tokens:
LOGGER.warning('Attempted to remove an unknown fail token: %s',
fail_token['message'])
self.passed = False
return
self.fail_tokens.remove(fail_token)
def set_passed(self, value):
"""Accumulate pass/fail value.
If a test module has already claimed that the test has failed, then this
method will ignore any further attempts to change the pass/fail status.
"""
if self.passed is False:
return
self.passed = value
def __init__(self, test_path='', test_config=None):
"""Create a new instance of a TestCase. Must be called by inheriting
classes.
Keyword Arguments:
test_path Optional parameter that specifies the path where this test
resides
test_config Loaded YAML test configuration
"""
if not len(test_path):
self.test_name = os.path.dirname(sys.argv[0])
else:
self.test_name = test_path
# We're not using /tmp//full//test//name because it gets so long that
# it doesn't fit in AF_UNIX paths (limited to around 108 chars) used
# for the rasterisk CLI connection. As a quick fix, we hash the path
# using md5, to make it unique enough.
self.realbase = self.test_name.replace("tests/", "", 1)
self.base = md5(self.realbase).hexdigest()
# We provide a symlink to it from a named path.
named_dir = os.path.join(Asterisk.test_suite_root, self.realbase)
try:
os.makedirs(os.path.dirname(named_dir))
except OSError:
pass
try:
join_path = os.path.relpath(
os.path.join(Asterisk.test_suite_root, self.base),
os.path.dirname(named_dir)
)
os.symlink(join_path, named_dir)
except OSError:
pass
self.ast = []
self.ami = []
self.fastagi = []
self.base_config_path = None
self.reactor_timeout = 30
self.passed = None
self.fail_tokens = []
self.timeout_id = None
self.global_config = TestConfig(os.getcwd())
self.test_config = TestConfig(self.test_name, self.global_config)
self.condition_controller = None
self.pcap = None
self.pcapfilename = None
self.create_pcap = False
self._stopping = False
self.testlogdir = self._set_test_log_directory()
self.ast_version = AsteriskVersion()
self._start_callbacks = []
self._stop_callbacks = []
self._ami_callbacks = []
self._pcap_callbacks = []
self._stop_deferred = None
log_full = True
log_messages = True
if os.getenv("VALGRIND_ENABLE") == "true":
self.reactor_timeout *= 20
# Pull additional configuration from YAML config if possible
if test_config:
if 'config-path' in test_config:
self.base_config_path = test_config['config-path']
if 'reactor-timeout' in test_config:
self.reactor_timeout = test_config['reactor-timeout']
self.ast_conf_options = test_config.get('ast-config-options')
log_full = test_config.get('log-full', True)
log_messages = test_config.get('log-messages', True)
else:
self.ast_conf_options = None
os.makedirs(self.testlogdir)
# Set up logging
setup_logging(self.testlogdir, log_full, log_messages)
LOGGER.info("Executing " + self.test_name)
if PCAP_AVAILABLE and self.create_pcap:
self.pcapfilename = os.path.join(self.testlogdir, "dumpfile.pcap")
self.pcap = self.create_pcap_listener(dumpfile=self.pcapfilename)
self._setup_conditions()
# Enable twisted logging
observer = log.PythonLoggingObserver()
observer.start()
reactor.callWhenRunning(self._run)
def test_validate_const_reward_discounted_env(self):
# config
config = TestConfig()
config.n_global_steps = 50000
config.env_id = 'RandObsConstRewardEnv-v0'
config.discount = .9
config.value_dim = 2
config.adam_beta1 = .9
config.local_steps_per_update = 1000
config.hidden_layer_sizes = [256]
config.learning_rate = 1e-3
config.learning_rate_end = 1e-5
config.loss_type = 'mse'
config.target_loss_index = None
# build env
const_reward = .01
horizon = 10000000
rand_obs = False
env = debug_envs.RandObsConstRewardEnv(horizon=horizon,
reward=const_reward,
value_dim=config.value_dim,
rand_obs=rand_obs)
env.spec = gym.envs.registration.EnvSpec(
id='RandObsConstRewardEnv-v0',
tags={'wrapper_config.TimeLimit.max_episode_steps': horizon + 1})
n_samples = 2
n_timesteps = 10 # predict after seeing this many timesteps
n_prediction_timesteps = 10 # determines discount
input_dim = 1
obs_gen = np.random.randn if rand_obs else np.ones
x = obs_gen(np.prod((n_samples, n_timesteps, input_dim))).reshape(
(n_samples, n_timesteps, input_dim))
y = (const_reward * np.ones(
(n_samples, config.value_dim)) * n_prediction_timesteps)
w = np.ones((n_samples, 1))
dataset = validation.Dataset(x, y, w)
# run it
summary_writer = tf.summary.FileWriter('/tmp/test')
avg_loss = -1
with tf.Session() as sess:
trainer = async_td.AsyncTD(env, 0, config)
sess.run(tf.global_variables_initializer())
sess.run(trainer.sync)
trainer.start(sess, summary_writer)
global_step = sess.run(trainer.global_step)
while global_step < config.n_global_steps:
trainer.process(sess)
if global_step % 10 == 0:
avg_loss = trainer.validate(sess, dataset)
global_step = sess.run(trainer.global_step)
'order: 5',
'Goal accepted with ID:',
'Result:',
'sequence:',
'0',
'1',
'2',
'3',
'5',
'Goal finished with status: SUCCEEDED',
]
configs = [
TestConfig(
command='action',
arguments=['info', '/fibonacci'],
actions=[get_action_server_node_action()],
expected_output=common_info_output + ['/fibonacci_action_server'],
),
TestConfig(
command='action',
arguments=['info', '-t', '/fibonacci'],
actions=[get_action_server_node_action()],
expected_output=common_info_output + [
'/fibonacci_action_server [action_tutorials_interfaces/action/Fibonacci]'
],
),
TestConfig(
command='action',
arguments=['info', '-c', '/fibonacci'],
actions=[get_action_server_node_action()],
expected_output=common_info_output,
def pytest_configure(config):
""" configure webdriver based on cmd-line arguments """
# load config (ini and cmd-line)
test_config = TestConfig(config)
TestLog.configure()
log.debug("pytest_configure")
log.debug(test_config)
# download drivers (if using Local drivers)
if not (test_config.use_browserstack or test_config.use_selenoid):
LocalDriverFactory.download_drivers(test_config.browsers_list)
class DriverPlugin:
""" Driver plugin class """
@pytest.fixture(autouse=True,
params=test_config.browsers_list,
scope="function")
def driver(self, request):
""" web driver fixture """
# init browser options
options = BrowserOptions()
options.browser_type = Browser[request.param]
options.headless = test_config.headless
options.window_size = test_config.win_size
options.timeout = test_config.timeout
options.use_browserstack = test_config.use_browserstack
options.use_selenoid = test_config.use_selenoid
options.hub_url = test_config.hub_url
log.debug("Create 'driver' fixture: {}".format(options))
# get webdriver instance
if options.use_browserstack:
d = BsDriverFactory.get_driver(options)
elif options.use_selenoid:
d = SelenoidDriverFactory.get_driver(options)
else:
d = LocalDriverFactory.get_driver(options)
yield d
try:
if request.node.rep_call.failed:
log.error("Test '{}' failed!".format(
request.function.__name__))
try:
allure.attach(
d.get_screenshot_as_png(),
name='screenshot on fail',
attachment_type=allure.attachment_type.PNG)
except:
log.warn("Unable to attch screenshot to allure report")
pass
finally:
# finalization
d.quit()
log.debug("'driver' fixture finalized")
# register plugin
config.pluginmanager.register(DriverPlugin())