def handle_connection(self, cl_socket):
"""
Handle socket connection.
:param cl_socket:
:return:
"""
service = None
while True:
if BENCHMARK:
pr.disable()
pr.dump_stats('/tmp/tsPythonProfile.prof')
cmd, msg = retrieve_msg(cl_socket)
if BENCHMARK:
pr.enable()
if cmd == b'I':
resp = service.predict(msg)
cl_socket.sendall(resp)
elif cmd == b'L':
service, result, code = self.load_model(msg)
resp = bytearray()
resp += create_load_model_response(code, result)
cl_socket.sendall(resp)
if code != 200:
raise RuntimeError("{} - {}".format(code, result))
else:
raise ValueError("Received unknown command: {}".format(cmd))
if service is not None and service.context is not None and service.context.metrics is not None:
emit_metrics(service.context.metrics.store)
def test_emit_metrics(self, caplog):
caplog.set_level(logging.INFO)
metrics = {'test_emit_metrics': True}
emit_metrics(metrics)
assert "[METRICS]" in caplog.text
def test_metrics(caplog):
"""
Test if metric classes methods behave as expected
Also checks global metric service methods
"""
# Create a batch of request ids
request_ids = {0: 'abcd', 1: "xyz", 2: "qwerty", 3: "hjshfj"}
all_req_ids = ','.join(request_ids.values())
model_name = "dummy model"
# Create a metrics objects
metrics = MetricsStore(request_ids, model_name)
# Counter tests
metrics.add_counter('CorrectCounter', 1, 1)
test_metric = metrics.cache[get_model_key('CorrectCounter', 'count', 'xyz',
model_name)]
assert 'CorrectCounter' == test_metric.name
metrics.add_counter('CorrectCounter', 1, 1)
metrics.add_counter('CorrectCounter', 1, 3)
metrics.add_counter('CorrectCounter', 1)
test_metric = metrics.cache[get_model_key('CorrectCounter', 'count',
all_req_ids, model_name)]
assert 'CorrectCounter' == test_metric.name
metrics.add_counter('CorrectCounter', 3)
test_metric = metrics.cache[get_model_key('CorrectCounter', 'count', 'xyz',
model_name)]
assert test_metric.value == 2
test_metric = metrics.cache[get_model_key('CorrectCounter', 'count',
'hjshfj', model_name)]
assert test_metric.value == 1
test_metric = metrics.cache[get_model_key('CorrectCounter', 'count',
all_req_ids, model_name)]
assert test_metric.value == 4
# Check what is emitted is correct
emit_metrics(metrics.store)
assert "hjshfj" in caplog.text
assert "ModelName:dummy model" in caplog.text
# Adding other types of metrics
# Check for time metric
with pytest.raises(Exception) as e_info:
metrics.add_time('WrongTime', 20, 1, 'ns')
assert "the unit for a timed metric should be one of ['ms', 's']" == e_info.value.args[
0]
metrics.add_time('CorrectTime', 20, 2, 's')
metrics.add_time('CorrectTime', 20, 0)
test_metric = metrics.cache[get_model_key('CorrectTime', 'ms', 'abcd',
model_name)]
assert test_metric.value == 20
assert test_metric.unit == 'Milliseconds'
test_metric = metrics.cache[get_model_key('CorrectTime', 's', 'qwerty',
model_name)]
assert test_metric.value == 20
assert test_metric.unit == 'Seconds'
# Size based metrics
with pytest.raises(Exception) as e_info:
metrics.add_size('WrongSize', 20, 1, 'TB')
assert "The unit for size based metric is one of ['MB','kB', 'GB', 'B']" == e_info.value.args[
0]
metrics.add_size('CorrectSize', 200, 0, 'GB')
metrics.add_size('CorrectSize', 10, 2)
test_metric = metrics.cache[get_model_key('CorrectSize', 'GB', 'abcd',
model_name)]
assert test_metric.value == 200
assert test_metric.unit == 'Gigabytes'
test_metric = metrics.cache[get_model_key('CorrectSize', 'MB', 'qwerty',
model_name)]
assert test_metric.value == 10
assert test_metric.unit == 'Megabytes'
# Check a percentage metric
metrics.add_percent('CorrectPercent', 20.0, 3)
test_metric = metrics.cache[get_model_key('CorrectPercent', 'percent',
'hjshfj', model_name)]
assert test_metric.value == 20.0
assert test_metric.unit == 'Percent'
# Check a error metric
metrics.add_error('CorrectError', 'Wrong values')
test_metric = metrics.cache[get_error_key('CorrectError', '')]
assert test_metric.value == 'Wrong values'
def test_emit_metrics(self, caplog):
metrics = {'test_emit_metrics': True}
emit_metrics(metrics)
assert "[METRICS]" in caplog.text