def test_healthy_tpuvm_cluster(self):
# Using TPUVM flavor of metadata.
mock.patch.object(ClusterResolver, 'get_instance_metadata',
mock_request_tpuvm_metadata).start()
noop_compute_service = build_mock_compute_service({}, {})
self.mock_discovery.side_effect = build_mock_services_fn(
noop_compute_service)
tpu_map = {
'fake-pod': {
'state':
'READY',
'health':
'HEALTHY',
'runtime_version':
'v2-nightly',
'accelerator_type':
'v3-32',
'api_version':
'V2_ALPHA1',
'network_endpoints': [{
'ipAddress': f'10.1.0.{index}',
'port': '8470',
} for index in range(4)],
}
}
self.mock_ctc.side_effect = build_mock_cloud_tpu_client_library(
tpu_map)
tpus = list(tpu_map.keys())
cr = ClusterResolver(tpus)
cluster = cr.get_cluster()
expected_client_workers = [
ClientWorker(internal_ip=f'10.1.0.{index}',
machine_type='v3-32',
zone='fake-zone',
hostname=f'{TPUVM_HOSTNAME_PREFIX}{index}')
for index in range(4)
]
expected_service_workers = [
ServiceWorker(internal_ip=f'10.1.0.{ip}',
port='8470',
machine_type='v3-32',
zone='fake-zone',
runtime_version='v2-nightly',
tpu='fake-pod') for ip in range(4)
]
expected = Cluster(expected_client_workers,
expected_service_workers,
client_master_ip='10.1.0.0')
self.assertEqual(expected, cluster)
mock.patch.object(ClusterResolver, 'get_instance_metadata',
mock_request_metadata).start()
type=str,
help='The python command to launch training including model parameters.'
)
FLAGS = parser.parse_args()
tpuvm_mode = False
accel_type = ClusterResolver.get_instance_metadata(
'instance/attributes/accelerator-type')
if re.match(r'v[0-9]+-[0-9]+', accel_type):
# Only TPUVM will carry the accelerator-type metadata
tpuvm_mode = True
if (FLAGS.docker_container or FLAGS.docker_image
or FLAGS.docker_run_flag) and FLAGS.conda_env:
raise ValueError('Docker Setup arguments and Conda Setup'
' arguments are mutually exclusive.')
# Resolve VM and TPU clusters.
cluster_resolver = ClusterResolver(FLAGS.tpu,
vms=FLAGS.vm,
tpuvm_mode=tpuvm_mode)
cluster = cluster_resolver.get_cluster()
executor = DistributedExecutor(cluster,
docker_container=FLAGS.docker_container,
docker_image=FLAGS.docker_image,
docker_run_flags=FLAGS.docker_run_flag,
conda_env=FLAGS.conda_env,
env_vars=FLAGS.env,
tpuvm_mode=tpuvm_mode)
executor.run(FLAGS.positional)
def test_healthy_cluster(self):
list_instances_map = {
'fake-ig': {
'kind':
'compute#instanceGroupsListInstances',
'items': [
gen_fake_ig_list_instances_entry('fake-ig-' + c, 'RUNNING')
for c in 'abcd'
],
},
}
instance_resp_map = {
'fake-ig-' + c:
gen_fake_instances_get_entry('fake-ig-' + c, 'n1-standard-16',
'10.0.0.' + ip, 'RUNNING')
for c, ip in zip('abcd', '0123')
}
compute_service = build_mock_compute_service(instance_resp_map,
list_instances_map)
self.mock_discovery.side_effect = build_mock_services_fn(
compute_service)
tpu_map = {
'fake-pod': {
'state':
'READY',
'health':
'HEALTHY',
'runtime_version':
'pytorch-nightly',
'accelerator_type':
'v3-32',
'network_endpoints': [{
'ipAddress': f'10.0.0.{ip}',
'port': '8470'
} for ip in range(4)],
}
}
self.mock_ctc.side_effect = build_mock_cloud_tpu_client_library(
tpu_map)
tpus = list(tpu_map.keys())
cr = ClusterResolver(tpus)
cluster = cr.get_cluster()
expected_client_workers = [
ClientWorker(internal_ip='10.0.0.' + ip,
machine_type='n1-standard-16',
zone='fake-zone',
hostname='fake-ig-' + c)
for c, ip in zip('abcd', '0123')
]
expected_service_workers = [
ServiceWorker(internal_ip=f'10.0.0.{ip}',
port='8470',
machine_type='v3-32',
zone='fake-zone',
runtime_version='pytorch-nightly',
tpu='fake-pod') for ip in range(4)
]
expected = Cluster(expected_client_workers, expected_service_workers)
self.assertEqual(expected, cluster)