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fix: allow setting max_wait_duration to 0 for indefinite waiting with DWS #6705

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Merged
copybara-service merged 1 commit into from
Apr 29, 2026
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Merged

fix: allow setting max_wait_duration to 0 for indefinite waiting with DWS #6705

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8 changes: 4 additions & 4 deletions google/cloud/aiplatform/jobs.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2604,12 +2604,12 @@ def submit(
or restart_job_on_worker_restart
or disable_retries
or scheduling_strategy
or max_wait_duration
or max_wait_duration is not None # 0 is a valid value
):
timeout = duration_pb2.Duration(seconds=timeout) if timeout else None
max_wait_duration = (
duration_pb2.Duration(seconds=max_wait_duration)
if max_wait_duration
if max_wait_duration is not None
else None
)
self._gca_resource.job_spec.scheduling = gca_custom_job_compat.Scheduling(
Expand Down Expand Up @@ -3133,13 +3133,13 @@ def _run(
timeout
or restart_job_on_worker_restart
or disable_retries
or max_wait_duration
or max_wait_duration is not None # 0 is a valid value
or scheduling_strategy
):
timeout = duration_pb2.Duration(seconds=timeout) if timeout else None
max_wait_duration = (
duration_pb2.Duration(seconds=max_wait_duration)
if max_wait_duration
if max_wait_duration is not None
else None
)
self._gca_resource.trial_job_spec.scheduling = (
Expand Down
96 changes: 96 additions & 0 deletions tests/unit/aiplatform/test_custom_job.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,7 @@
# limitations under the License.
#

import datetime
import pytest
import logging

Expand Down Expand Up @@ -730,6 +731,101 @@ def test_submit_custom_job(self, create_custom_job_mock, get_custom_job_mock):
)
assert job.network == _TEST_NETWORK

def test_submit_custom_job_with_zero_max_wait_duration(
self, create_custom_job_mock, get_custom_job_mock
):

aiplatform.init(
project=_TEST_PROJECT,
location=_TEST_LOCATION,
staging_bucket=_TEST_STAGING_BUCKET,
encryption_spec_key_name=_TEST_DEFAULT_ENCRYPTION_KEY_NAME,
)

job = aiplatform.CustomJob(
display_name=_TEST_DISPLAY_NAME,
worker_pool_specs=_TEST_WORKER_POOL_SPEC,
base_output_dir=_TEST_BASE_OUTPUT_DIR,
labels=_TEST_LABELS,
)

job.submit(
service_account=_TEST_SERVICE_ACCOUNT,
network=_TEST_NETWORK,
timeout=_TEST_TIMEOUT,
restart_job_on_worker_restart=_TEST_RESTART_JOB_ON_WORKER_RESTART,
create_request_timeout=None,
disable_retries=_TEST_DISABLE_RETRIES,
max_wait_duration=0,
)

job.wait_for_resource_creation()

assert job.resource_name == _TEST_CUSTOM_JOB_NAME

job.wait()

expected_custom_job = _get_custom_job_proto()
expected_custom_job.job_spec.scheduling.max_wait_duration = datetime.timedelta(
seconds=0
)

create_custom_job_mock.assert_called_once_with(
parent=_TEST_PARENT,
custom_job=expected_custom_job,
timeout=None,
)
assert (
job._gca_resource.state == gca_job_state_compat.JobState.JOB_STATE_PENDING
)

def test_submit_custom_job_with_default_max_wait_duration(
self, create_custom_job_mock, get_custom_job_mock
):

aiplatform.init(
project=_TEST_PROJECT,
location=_TEST_LOCATION,
staging_bucket=_TEST_STAGING_BUCKET,
encryption_spec_key_name=_TEST_DEFAULT_ENCRYPTION_KEY_NAME,
)

job = aiplatform.CustomJob(
display_name=_TEST_DISPLAY_NAME,
worker_pool_specs=_TEST_WORKER_POOL_SPEC,
base_output_dir=_TEST_BASE_OUTPUT_DIR,
labels=_TEST_LABELS,
)

job.submit(
service_account=_TEST_SERVICE_ACCOUNT,
network=_TEST_NETWORK,
timeout=_TEST_TIMEOUT,
restart_job_on_worker_restart=_TEST_RESTART_JOB_ON_WORKER_RESTART,
create_request_timeout=None,
disable_retries=_TEST_DISABLE_RETRIES,
)

job.wait_for_resource_creation()

assert job.resource_name == _TEST_CUSTOM_JOB_NAME

job.wait()

expected_custom_job = _get_custom_job_proto()
expected_custom_job.job_spec.scheduling.max_wait_duration = None

create_custom_job_mock.assert_called_once_with(
parent=_TEST_PARENT,
custom_job=expected_custom_job,
timeout=None,
)

assert "max_wait_duration" not in expected_custom_job.job_spec.scheduling
assert (
job._gca_resource.state == gca_job_state_compat.JobState.JOB_STATE_PENDING
)

@pytest.mark.usefixtures(
"get_experiment_run_mock", "get_tensorboard_run_artifact_not_found_mock"
)
Expand Down
149 changes: 148 additions & 1 deletion tests/unit/aiplatform/test_hyperparameter_tuning_job.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -14,9 +14,10 @@
# limitations under the License.
#

import copy
import datetime
import pytest

import copy
from importlib import reload
from unittest import mock
from unittest.mock import patch
Expand Down Expand Up @@ -523,6 +524,152 @@ def test_create_hyperparameter_tuning_job(
assert job.network == _TEST_NETWORK
assert job.trials == []

def test_create_hyperparameter_tuning_job_with_zero_max_wait_duration(
self,
create_hyperparameter_tuning_job_mock,
get_hyperparameter_tuning_job_mock,
):

aiplatform.init(
project=_TEST_PROJECT,
location=_TEST_LOCATION,
staging_bucket=_TEST_STAGING_BUCKET,
encryption_spec_key_name=_TEST_DEFAULT_ENCRYPTION_KEY_NAME,
)

custom_job = aiplatform.CustomJob(
display_name=test_constants.TrainingJobConstants._TEST_DISPLAY_NAME,
worker_pool_specs=test_constants.TrainingJobConstants._TEST_WORKER_POOL_SPEC,
base_output_dir=test_constants.TrainingJobConstants._TEST_BASE_OUTPUT_DIR,
)

job = aiplatform.HyperparameterTuningJob(
display_name=_TEST_DISPLAY_NAME,
custom_job=custom_job,
metric_spec={_TEST_METRIC_SPEC_KEY: _TEST_METRIC_SPEC_VALUE},
parameter_spec={
"lr": hpt.DoubleParameterSpec(min=0.001, max=0.1, scale="log"),
"units": hpt.IntegerParameterSpec(min=4, max=1028, scale="linear"),
"activation": hpt.CategoricalParameterSpec(
values=["relu", "sigmoid", "elu", "selu", "tanh"]
),
"batch_size": hpt.DiscreteParameterSpec(
values=[4, 8, 16, 32, 64],
scale="linear",
conditional_parameter_spec={
"decay": _TEST_CONDITIONAL_PARAMETER_DECAY,
"learning_rate": _TEST_CONDITIONAL_PARAMETER_LR,
},
),
},
parallel_trial_count=_TEST_PARALLEL_TRIAL_COUNT,
max_trial_count=_TEST_MAX_TRIAL_COUNT,
max_failed_trial_count=_TEST_MAX_FAILED_TRIAL_COUNT,
search_algorithm=_TEST_SEARCH_ALGORITHM,
measurement_selection=_TEST_MEASUREMENT_SELECTION,
labels=_TEST_LABELS,
)

job.run(
service_account=_TEST_SERVICE_ACCOUNT,
network=_TEST_NETWORK,
timeout=_TEST_TIMEOUT,
restart_job_on_worker_restart=_TEST_RESTART_JOB_ON_WORKER_RESTART,
sync=True,
create_request_timeout=None,
disable_retries=_TEST_DISABLE_RETRIES,
max_wait_duration=0,
)

job.wait()

expected_hyperparameter_tuning_job = _get_hyperparameter_tuning_job_proto()
expected_hyperparameter_tuning_job.trial_job_spec.scheduling.max_wait_duration = datetime.timedelta(
seconds=0
)

create_hyperparameter_tuning_job_mock.assert_called_once_with(
parent=_TEST_PARENT,
hyperparameter_tuning_job=expected_hyperparameter_tuning_job,
timeout=None,
)
assert job.state == gca_job_state_compat.JobState.JOB_STATE_SUCCEEDED

def test_create_hyperparameter_tuning_job_with_default_max_wait_duration(
self,
create_hyperparameter_tuning_job_mock,
get_hyperparameter_tuning_job_mock,
):

aiplatform.init(
project=_TEST_PROJECT,
location=_TEST_LOCATION,
staging_bucket=_TEST_STAGING_BUCKET,
encryption_spec_key_name=_TEST_DEFAULT_ENCRYPTION_KEY_NAME,
)

custom_job = aiplatform.CustomJob(
display_name=test_constants.TrainingJobConstants._TEST_DISPLAY_NAME,
worker_pool_specs=test_constants.TrainingJobConstants._TEST_WORKER_POOL_SPEC,
base_output_dir=test_constants.TrainingJobConstants._TEST_BASE_OUTPUT_DIR,
)

job = aiplatform.HyperparameterTuningJob(
display_name=_TEST_DISPLAY_NAME,
custom_job=custom_job,
metric_spec={_TEST_METRIC_SPEC_KEY: _TEST_METRIC_SPEC_VALUE},
parameter_spec={
"lr": hpt.DoubleParameterSpec(min=0.001, max=0.1, scale="log"),
"units": hpt.IntegerParameterSpec(min=4, max=1028, scale="linear"),
"activation": hpt.CategoricalParameterSpec(
values=["relu", "sigmoid", "elu", "selu", "tanh"]
),
"batch_size": hpt.DiscreteParameterSpec(
values=[4, 8, 16, 32, 64],
scale="linear",
conditional_parameter_spec={
"decay": _TEST_CONDITIONAL_PARAMETER_DECAY,
"learning_rate": _TEST_CONDITIONAL_PARAMETER_LR,
},
),
},
parallel_trial_count=_TEST_PARALLEL_TRIAL_COUNT,
max_trial_count=_TEST_MAX_TRIAL_COUNT,
max_failed_trial_count=_TEST_MAX_FAILED_TRIAL_COUNT,
search_algorithm=_TEST_SEARCH_ALGORITHM,
measurement_selection=_TEST_MEASUREMENT_SELECTION,
labels=_TEST_LABELS,
)

job.run(
service_account=_TEST_SERVICE_ACCOUNT,
network=_TEST_NETWORK,
timeout=_TEST_TIMEOUT,
restart_job_on_worker_restart=_TEST_RESTART_JOB_ON_WORKER_RESTART,
sync=True,
create_request_timeout=None,
disable_retries=_TEST_DISABLE_RETRIES,
)

job.wait()

expected_hyperparameter_tuning_job = _get_hyperparameter_tuning_job_proto()
expected_hyperparameter_tuning_job.trial_job_spec.scheduling.max_wait_duration = (
None
)

create_hyperparameter_tuning_job_mock.assert_called_once_with(
parent=_TEST_PARENT,
hyperparameter_tuning_job=expected_hyperparameter_tuning_job,
timeout=None,
)

assert (
"max_wait_duration"
not in expected_hyperparameter_tuning_job.trial_job_spec.scheduling
)
assert job.state == gca_job_state_compat.JobState.JOB_STATE_SUCCEEDED

@pytest.mark.parametrize("sync", [True, False])
def test_create_hyperparameter_tuning_job_with_timeout(
self,
Expand Down
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