def testGetModelMetadataREST(self):
"""Test ModelStatus implementation over REST API with columnar inputs."""
model_path = self._GetSavedModelBundlePath()
host, port = TensorflowModelServerTest.RunServer(
'default', model_path)[2].split(':')
# Prepare request
url = 'http://{}:{}/v1/models/default/metadata'.format(host, port)
# Send request
resp_data = None
try:
resp_data = tensorflow_model_server_test_base.CallREST(url, None)
except Exception as e: # pylint: disable=broad-except
self.fail('Request failed with error: {}'.format(e))
try:
model_metadata_file = self._GetModelMetadataFile()
with open(model_metadata_file) as f:
expected_metadata = json.load(f)
# Verify response
# Note, we sort the JSON object before comparing. Formally JSON lists
# (aka arrays) are considered ordered and general comparison should NOT
# sort. In this case, the "metadata" does not have any ordering making
# the sort OK (and the test robust).
self.assertEqual(
tensorflow_model_server_test_base.SortedObject(
json.loads(resp_data)),
tensorflow_model_server_test_base.SortedObject(
expected_metadata))
except Exception as e: # pylint: disable=broad-except
self.fail('Request failed with error: {}'.format(e))
def testGetStatusREST(self):
"""Test ModelStatus implementation over REST API with columnar inputs."""
model_path = self._GetSavedModelBundlePath()
host, port = TensorflowModelServerTest.RunServer(
'default', model_path)[2].split(':')
# Prepare request
url = 'http://{}:{}/v1/models/default'.format(host, port)
# Send request
resp_data = None
try:
resp_data = tensorflow_model_server_test_base.CallREST(url, None)
except Exception as e: # pylint: disable=broad-except
self.fail('Request failed with error: {}'.format(e))
# Verify response
self.assertEqual(
json.loads(resp_data), {
'model_version_status': [{
'version': '123',
'state': 'AVAILABLE',
'status': {
'error_code': 'OK',
'error_message': ''
}
}]
})
def testRegressREST(self):
"""Test Regress implementation over REST API."""
model_path = self._GetSavedModelBundlePath()
host, port = TensorflowModelServerTest.RunServer(
'default', model_path)[2].split(':')
# Prepare request
url = 'http://{}:{}/v1/models/default:regress'.format(host, port)
json_req = {
'signature_name': 'regress_x_to_y',
'examples': [{
'x': 2.0
}]
}
# Send request
resp_data = None
try:
resp_data = tensorflow_model_server_test_base.CallREST(
url, json_req)
except Exception as e: # pylint: disable=broad-except
self.fail('Request failed with error: {}'.format(e))
# Verify response
self.assertEqual(json.loads(resp_data), {'results': [3.0]})
def testPredictColumnarREST(self):
"""Test Predict implementation over REST API with columnar inputs."""
model_path = self._GetSavedModelBundlePath()
host, port = TensorflowModelServerTest.RunServer('default',
model_path)[2].split(':')
# Prepare request
url = 'http://{}:{}/v1/models/default:predict'.format(host, port)
json_req = {'inputs': [2.0, 3.0, 4.0]}
# Send request
resp_data = None
try:
resp_data = tensorflow_model_server_test_base.CallREST(url, json_req)
except Exception as e: # pylint: disable=broad-except
self.fail('Request failed with error: {}'.format(e))
# Verify response
self.assertEqual(json.loads(resp_data), {'outputs': [3.0, 3.5, 4.0]})
def testPrometheusEndpoint(self):
"""Test ModelStatus implementation over REST API with columnar inputs."""
model_path = self._GetSavedModelBundlePath()
host, port = TensorflowModelServerTest.RunServer(
'default',
model_path,
monitoring_config_file=self._GetMonitoringConfigFile())[2].split(':')
# Prepare request
url = 'http://{}:{}/monitoring/prometheus/metrics'.format(host, port)
# Send request
resp_data = None
try:
resp_data = tensorflow_model_server_test_base.CallREST(url, None)
except Exception as e: # pylint: disable=broad-except
self.fail('Request failed with error: {}'.format(e))
# Verify that there should be some metric type information.
self.assertIn('# TYPE',
resp_data.decode('utf-8') if resp_data is not None else None)
