def testNonRunningPod(self):
ret = _create_pod_list(('tensorflow-abc123', 'Failed', '10.1.2.3'), )
cluster_resolver = KubernetesClusterResolver(
override_client=_mock_kubernetes_client(
{'job-name=tensorflow': ret}))
error_msg = 'Pod "tensorflow-abc123" is not running; phase: "Failed"'
with self.assertRaisesRegexp(RuntimeError, error_msg):
cluster_resolver.cluster_spec()
def testNonRunningPod(self):
ret = _create_pod_list(('tensorflow-abc123', 'Failed', '10.1.2.3'),)
cluster_resolver = KubernetesClusterResolver(
override_client=_mock_kubernetes_client(
{'job-name=tensorflow': ret}))
error_msg = 'Pod "tensorflow-abc123" is not running; phase: "Failed"'
with self.assertRaisesRegexp(RuntimeError, error_msg):
cluster_resolver.cluster_spec()
def testSingleItemSuccessfulRetrieval(self):
ret = _create_pod_list(('tensorflow-abc123', 'Running', '10.1.2.3'),)
cluster_resolver = KubernetesClusterResolver(
override_client=_mock_kubernetes_client(
{'job-name=tensorflow': ret}))
actual_cluster_spec = cluster_resolver.cluster_spec()
expected_proto = """
job {
name: 'worker'
tasks { key: 0 value: '10.1.2.3:8470' }
}
"""
self._verifyClusterSpecEquality(actual_cluster_spec, str(expected_proto))
def testMultiplePodSelectorsAndWorkers(self):
worker1 = _create_pod_list(
('tensorflow-abc123', 'Running', '10.1.2.3'),
('tensorflow-def456', 'Running', '10.1.2.4'),
('tensorflow-999999', 'Running', '10.1.2.5'))
worker2 = _create_pod_list(
('tensorflow-abc124', 'Running', '10.1.2.6'),
('tensorflow-def457', 'Running', '10.1.2.7'),
('tensorflow-999990', 'Running', '10.1.2.8'))
ps = _create_pod_list(('tensorflow-ps-1', 'Running', '10.1.2.1'),
('tensorflow-ps-2', 'Running', '10.1.2.2'))
cluster_resolver = KubernetesClusterResolver(
job_to_label_mapping={
'worker': ['job-name=worker1', 'job-name=worker2'],
'ps': ['job-name=ps']
},
override_client=_mock_kubernetes_client({
'job-name=worker1': worker1,
'job-name=worker2': worker2,
'job-name=ps': ps
}))
actual_cluster_spec = cluster_resolver.cluster_spec()
expected_proto = """
job {
name: 'ps'
tasks { key: 0 value: '10.1.2.1:8470' }
tasks { key: 1 value: '10.1.2.2:8470' }
}
job {
name: 'worker'
tasks { key: 0 value: '10.1.2.5:8470' }
tasks { key: 1 value: '10.1.2.3:8470' }
tasks { key: 2 value: '10.1.2.4:8470' }
tasks { key: 3 value: '10.1.2.8:8470' }
tasks { key: 4 value: '10.1.2.6:8470' }
tasks { key: 5 value: '10.1.2.7:8470' }
}
"""
self._verifyClusterSpecEquality(actual_cluster_spec,
str(expected_proto))
def testMultiplePodSelectorsAndWorkers(self):
worker1 = _create_pod_list(
('tensorflow-abc123', 'Running', '10.1.2.3'),
('tensorflow-def456', 'Running', '10.1.2.4'),
('tensorflow-999999', 'Running', '10.1.2.5'))
worker2 = _create_pod_list(
('tensorflow-abc124', 'Running', '10.1.2.6'),
('tensorflow-def457', 'Running', '10.1.2.7'),
('tensorflow-999990', 'Running', '10.1.2.8'))
ps = _create_pod_list(
('tensorflow-ps-1', 'Running', '10.1.2.1'),
('tensorflow-ps-2', 'Running', '10.1.2.2'))
cluster_resolver = KubernetesClusterResolver(
job_to_label_mapping={
'worker': ['job-name=worker1', 'job-name=worker2'],
'ps': ['job-name=ps']
},
override_client=_mock_kubernetes_client({
'job-name=worker1': worker1,
'job-name=worker2': worker2,
'job-name=ps': ps
}))
actual_cluster_spec = cluster_resolver.cluster_spec()
expected_proto = """
job {
name: 'ps'
tasks { key: 0 value: '10.1.2.1:8470' }
tasks { key: 1 value: '10.1.2.2:8470' }
}
job {
name: 'worker'
tasks { key: 0 value: '10.1.2.5:8470' }
tasks { key: 1 value: '10.1.2.3:8470' }
tasks { key: 2 value: '10.1.2.4:8470' }
tasks { key: 3 value: '10.1.2.8:8470' }
tasks { key: 4 value: '10.1.2.6:8470' }
tasks { key: 5 value: '10.1.2.7:8470' }
}
"""
self._verifyClusterSpecEquality(actual_cluster_spec, str(expected_proto))