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feat: Support custom containers in CustomJob.from_local_script #1483

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merged 9 commits into from
Jul 23, 2022
Merged

feat: Support custom containers in CustomJob.from_local_script #1483

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5e8c5f8
feat: update from_local_script()
jaycee-li Jul 8, 2022
59c57d8
fix from_local_script()
jaycee-li Jul 8, 2022
4c590c6
fix: update unit tests
jaycee-li Jul 8, 2022
5399cb1
fix lint failed
jaycee-li Jul 8, 2022
0a043ef
fix: add system test
jaycee-li Jul 11, 2022
0e75f2e
fix: from_local_script
jaycee-li Jul 12, 2022
ffc7aa0
fix: from_local_script
jaycee-li Jul 19, 2022
a42fc76
fix: system test
jaycee-li Jul 20, 2022
473e22b
Merge branch 'main' into CustomJob-custom-containers
jaycee-li Jul 22, 2022
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28 changes: 27 additions & 1 deletion google/cloud/aiplatform/jobs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1388,7 +1388,10 @@ def from_local_script(
spec["container_spec"] = {
"image_uri": reduction_server_container_uri,
}
else:
## check if the container is pre-built
elif ("docker.pkg.dev/vertex-ai/" in container_uri) or (
"gcr.io/cloud-aiplatform/" in container_uri
):
spec["python_package_spec"] = {
"executor_image_uri": container_uri,
"python_module": python_packager.module_name,
Expand All @@ -1403,6 +1406,29 @@ def from_local_script(
{"name": key, "value": value}
for key, value in environment_variables.items()
]
else:
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command = [
"sh",
"-c",
"\npip3 install -q --user --upgrade --no-warn-script-location gsutil"
+ f"\ngsutil -q cp {package_gcs_uri} ."
+ f"\npip3 install -q --user {package_gcs_uri[len(staging_bucket)+1:]}"
+ f"\npython3 -m {python_packager.module_name}",
]

spec["container_spec"] = {
"image_uri": container_uri,
"command": command,
}

if args:
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spec["container_spec"]["args"] = args

if environment_variables:
spec["container_spec"]["env"] = [
{"name": key, "value": value}
for key, value in environment_variables.items()
]

return cls(
display_name=display_name,
Expand Down
201 changes: 159 additions & 42 deletions tests/unit/aiplatform/test_custom_job.py
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Original file line number Diff line number Diff line change
Expand Up @@ -50,6 +50,7 @@
_TEST_ENABLE_WEB_ACCESS = True
_TEST_WEB_ACCESS_URIS = {"workerpool0-0": "uri"}
_TEST_TRAINING_CONTAINER_IMAGE = "gcr.io/test-training/container:image"
_TEST_PREBUILT_CONTAINER_IMAGE = "gcr.io/cloud-aiplatform/container:image"
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_TEST_RUN_ARGS = ["-v", "0.1", "--test=arg"]

Expand All @@ -70,6 +71,24 @@
}
]

_TEST_PYTHON_PACKAGE_SPEC = gca_custom_job_compat.PythonPackageSpec(
executor_image_uri=_TEST_PREBUILT_CONTAINER_IMAGE,
package_uris=[test_training_jobs._TEST_OUTPUT_PYTHON_PACKAGE_PATH],
python_module=test_training_jobs._TEST_MODULE_NAME,
)

_TEST_CONTAINER_SPEC = gca_custom_job_compat.ContainerSpec(
image_uri=_TEST_TRAINING_CONTAINER_IMAGE,
command=[
"sh",
"-c",
"\npip3 install -q --user --upgrade --no-warn-script-location gsutil"
+ f"\ngsutil -q cp {test_training_jobs._TEST_OUTPUT_PYTHON_PACKAGE_PATH} ."
+ "\npip3 install -q --user trainer.tar.gz"
+ f"\npython3 -m {test_training_jobs._TEST_MODULE_NAME}",
],
)

_TEST_STAGING_BUCKET = "gs://test-staging-bucket"
_TEST_BASE_OUTPUT_DIR = f"{_TEST_STAGING_BUCKET}/{_TEST_DISPLAY_NAME}"

Expand Down Expand Up @@ -532,7 +551,41 @@ def test_get_custom_job(self, get_custom_job_mock):

@pytest.mark.usefixtures("mock_python_package_to_gcs")
@pytest.mark.parametrize("sync", [True, False])
def test_create_from_local_script(
def test_create_from_local_script_prebuilt_container(
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self, get_custom_job_mock, create_custom_job_mock, sync
):
aiplatform.init(
project=_TEST_PROJECT,
location=_TEST_LOCATION,
staging_bucket=_TEST_STAGING_BUCKET,
encryption_spec_key_name=_TEST_DEFAULT_ENCRYPTION_KEY_NAME,
)

# configuration on this is tested in test_training_jobs.py
job = aiplatform.CustomJob.from_local_script(
display_name=_TEST_DISPLAY_NAME,
script_path=test_training_jobs._TEST_LOCAL_SCRIPT_FILE_NAME,
container_uri=_TEST_PREBUILT_CONTAINER_IMAGE,
base_output_dir=_TEST_BASE_OUTPUT_DIR,
labels=_TEST_LABELS,
)

assert (
job.job_spec.worker_pool_specs[0].python_package_spec
== _TEST_PYTHON_PACKAGE_SPEC
)

job.run(sync=sync)

job.wait()

assert (
job._gca_resource.state == gca_job_state_compat.JobState.JOB_STATE_SUCCEEDED
)

@pytest.mark.usefixtures("mock_python_package_to_gcs")
@pytest.mark.parametrize("sync", [True, False])
def test_create_from_local_script_custom_container(
self, get_custom_job_mock, create_custom_job_mock, sync
):
aiplatform.init(
Expand All @@ -551,6 +604,8 @@ def test_create_from_local_script(
labels=_TEST_LABELS,
)

assert job.job_spec.worker_pool_specs[0].container_spec == _TEST_CONTAINER_SPEC

job.run(sync=sync)

job.wait()
Expand Down Expand Up @@ -579,6 +634,109 @@ def test_create_from_local_script_raises_with_no_staging_bucket(
container_uri=_TEST_TRAINING_CONTAINER_IMAGE,
)

@pytest.mark.usefixtures("mock_python_package_to_gcs")
@pytest.mark.parametrize("sync", [True, False])
def test_create_from_local_script_prebuilt_container_with_all_args(
self, get_custom_job_mock, create_custom_job_mock, sync
):
aiplatform.init(
project=_TEST_PROJECT,
location=_TEST_LOCATION,
staging_bucket=_TEST_STAGING_BUCKET,
encryption_spec_key_name=_TEST_DEFAULT_ENCRYPTION_KEY_NAME,
)

# configuration on this is tested in test_training_jobs.py
job = aiplatform.CustomJob.from_local_script(
display_name=_TEST_DISPLAY_NAME,
script_path=test_training_jobs._TEST_LOCAL_SCRIPT_FILE_NAME,
container_uri=_TEST_PREBUILT_CONTAINER_IMAGE,
args=_TEST_RUN_ARGS,
requirements=test_training_jobs._TEST_REQUIREMENTS,
environment_variables=test_training_jobs._TEST_ENVIRONMENT_VARIABLES,
replica_count=test_training_jobs._TEST_REPLICA_COUNT,
machine_type=test_training_jobs._TEST_MACHINE_TYPE,
accelerator_type=test_training_jobs._TEST_ACCELERATOR_TYPE,
accelerator_count=test_training_jobs._TEST_ACCELERATOR_COUNT,
boot_disk_type=test_training_jobs._TEST_BOOT_DISK_TYPE,
boot_disk_size_gb=test_training_jobs._TEST_BOOT_DISK_SIZE_GB,
reduction_server_replica_count=test_training_jobs._TEST_REDUCTION_SERVER_REPLICA_COUNT,
reduction_server_machine_type=test_training_jobs._TEST_REDUCTION_SERVER_MACHINE_TYPE,
reduction_server_container_uri=test_training_jobs._TEST_REDUCTION_SERVER_CONTAINER_URI,
base_output_dir=_TEST_BASE_OUTPUT_DIR,
labels=_TEST_LABELS,
)

expected_python_package_spec = _TEST_PYTHON_PACKAGE_SPEC
expected_python_package_spec.args = _TEST_RUN_ARGS
expected_python_package_spec.env = [
{"name": key, "value": value}
for key, value in test_training_jobs._TEST_ENVIRONMENT_VARIABLES.items()
]

assert (
job.job_spec.worker_pool_specs[0].python_package_spec
== expected_python_package_spec
)
job.run(sync=sync)

job.wait()

assert (
job._gca_resource.state == gca_job_state_compat.JobState.JOB_STATE_SUCCEEDED
)

@pytest.mark.usefixtures("mock_python_package_to_gcs")
@pytest.mark.parametrize("sync", [True, False])
def test_create_from_local_script_custom_container_with_all_args(
self, get_custom_job_mock, create_custom_job_mock, sync
):
aiplatform.init(
project=_TEST_PROJECT,
location=_TEST_LOCATION,
staging_bucket=_TEST_STAGING_BUCKET,
encryption_spec_key_name=_TEST_DEFAULT_ENCRYPTION_KEY_NAME,
)

# configuration on this is tested in test_training_jobs.py
job = aiplatform.CustomJob.from_local_script(
display_name=_TEST_DISPLAY_NAME,
script_path=test_training_jobs._TEST_LOCAL_SCRIPT_FILE_NAME,
container_uri=_TEST_TRAINING_CONTAINER_IMAGE,
args=_TEST_RUN_ARGS,
requirements=test_training_jobs._TEST_REQUIREMENTS,
environment_variables=test_training_jobs._TEST_ENVIRONMENT_VARIABLES,
replica_count=test_training_jobs._TEST_REPLICA_COUNT,
machine_type=test_training_jobs._TEST_MACHINE_TYPE,
accelerator_type=test_training_jobs._TEST_ACCELERATOR_TYPE,
accelerator_count=test_training_jobs._TEST_ACCELERATOR_COUNT,
boot_disk_type=test_training_jobs._TEST_BOOT_DISK_TYPE,
boot_disk_size_gb=test_training_jobs._TEST_BOOT_DISK_SIZE_GB,
reduction_server_replica_count=test_training_jobs._TEST_REDUCTION_SERVER_REPLICA_COUNT,
reduction_server_machine_type=test_training_jobs._TEST_REDUCTION_SERVER_MACHINE_TYPE,
reduction_server_container_uri=test_training_jobs._TEST_REDUCTION_SERVER_CONTAINER_URI,
base_output_dir=_TEST_BASE_OUTPUT_DIR,
labels=_TEST_LABELS,
)

expected_container_spec = _TEST_CONTAINER_SPEC
expected_container_spec.args = _TEST_RUN_ARGS
expected_container_spec.env = [
{"name": key, "value": value}
for key, value in test_training_jobs._TEST_ENVIRONMENT_VARIABLES.items()
]

assert (
job.job_spec.worker_pool_specs[0].container_spec == expected_container_spec
)
job.run(sync=sync)

job.wait()

assert (
job._gca_resource.state == gca_job_state_compat.JobState.JOB_STATE_SUCCEEDED
)

@pytest.mark.parametrize("sync", [True, False])
def test_create_custom_job_with_enable_web_access(
self,
Expand Down Expand Up @@ -722,47 +880,6 @@ def test_create_custom_job_without_base_output_dir(
f"{_TEST_STAGING_BUCKET}/aiplatform-custom-job"
)

@pytest.mark.usefixtures("mock_python_package_to_gcs")
@pytest.mark.parametrize("sync", [True, False])
def test_create_from_local_script_with_all_args(
self, get_custom_job_mock, create_custom_job_mock, sync
):
aiplatform.init(
project=_TEST_PROJECT,
location=_TEST_LOCATION,
staging_bucket=_TEST_STAGING_BUCKET,
encryption_spec_key_name=_TEST_DEFAULT_ENCRYPTION_KEY_NAME,
)

# configuration on this is tested in test_training_jobs.py
job = aiplatform.CustomJob.from_local_script(
display_name=_TEST_DISPLAY_NAME,
script_path=test_training_jobs._TEST_LOCAL_SCRIPT_FILE_NAME,
container_uri=_TEST_TRAINING_CONTAINER_IMAGE,
args=_TEST_RUN_ARGS,
requirements=test_training_jobs._TEST_REQUIREMENTS,
environment_variables=test_training_jobs._TEST_ENVIRONMENT_VARIABLES,
replica_count=test_training_jobs._TEST_REPLICA_COUNT,
machine_type=test_training_jobs._TEST_MACHINE_TYPE,
accelerator_type=test_training_jobs._TEST_ACCELERATOR_TYPE,
accelerator_count=test_training_jobs._TEST_ACCELERATOR_COUNT,
boot_disk_type=test_training_jobs._TEST_BOOT_DISK_TYPE,
boot_disk_size_gb=test_training_jobs._TEST_BOOT_DISK_SIZE_GB,
reduction_server_replica_count=test_training_jobs._TEST_REDUCTION_SERVER_REPLICA_COUNT,
reduction_server_machine_type=test_training_jobs._TEST_REDUCTION_SERVER_MACHINE_TYPE,
reduction_server_container_uri=test_training_jobs._TEST_REDUCTION_SERVER_CONTAINER_URI,
base_output_dir=_TEST_BASE_OUTPUT_DIR,
labels=_TEST_LABELS,
)

job.run(sync=sync)

job.wait()

assert (
job._gca_resource.state == gca_job_state_compat.JobState.JOB_STATE_SUCCEEDED
)

@pytest.mark.usefixtures("get_custom_job_mock", "create_custom_job_mock")
def test_check_custom_job_availability(self):
aiplatform.init(
Expand Down
2 changes: 1 addition & 1 deletion tests/unit/aiplatform/test_training_jobs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -159,7 +159,7 @@
_TEST_MODEL_SERVING_CONTAINER_PORTS = [8888, 10000]
_TEST_MODEL_DESCRIPTION = "test description"

_TEST_OUTPUT_PYTHON_PACKAGE_PATH = "gs://test/ouput/python/trainer.tar.gz"
_TEST_OUTPUT_PYTHON_PACKAGE_PATH = "gs://test-staging-bucket/trainer.tar.gz"
_TEST_PYTHON_MODULE_NAME = "aiplatform.task"

_TEST_MODEL_NAME = f"projects/{_TEST_PROJECT}/locations/us-central1/models/{_TEST_ID}"
Expand Down