File: //snap/google-cloud-cli/396/lib/surface/ai/hp_tuning_jobs/create.py
# -*- coding: utf-8 -*- #
# Copyright 2020 Google LLC. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Command to create a hyperparameter tuning job in Vertex AI."""
from __future__ import absolute_import
from __future__ import division
from __future__ import unicode_literals
from googlecloudsdk.api_lib.ai import util as api_util
from googlecloudsdk.api_lib.ai.hp_tuning_jobs import client
from googlecloudsdk.calliope import base
from googlecloudsdk.command_lib.ai import constants
from googlecloudsdk.command_lib.ai import endpoint_util
from googlecloudsdk.command_lib.ai import validation
from googlecloudsdk.command_lib.ai.hp_tuning_jobs import flags
from googlecloudsdk.command_lib.ai.hp_tuning_jobs import hp_tuning_jobs_util
from googlecloudsdk.command_lib.util.apis import arg_utils
from googlecloudsdk.command_lib.util.args import labels_util
from googlecloudsdk.core import log
_HPTUNING_JOB_CREATION_DISPLAY_MESSAGE = """\
Hyperparameter tuning job [{id}] submitted successfully.
Your job is still active. You may view the status of your job with the command
$ gcloud{command_version} ai hp-tuning-jobs describe {id} --region={region}
Job State: {state}\
"""
@base.ReleaseTracks(base.ReleaseTrack.GA)
class CreateGa(base.CreateCommand):
"""Create a hyperparameter tuning job."""
_api_version = constants.GA_VERSION
detailed_help = {
'EXAMPLES':
"""\
To create a job named ``test'' under project ``example'' in region
``us-central1'', run:
$ {command} --region=us-central1 --project=example --config=config.yaml --display-name=test
"""
}
@classmethod
def Args(cls, parser):
flags.AddCreateHpTuningJobFlags(
parser,
api_util.GetMessage('StudySpec',
version=cls._api_version).AlgorithmValueValuesEnum)
def Run(self, args):
region_ref = args.CONCEPTS.region.Parse()
region = region_ref.AsDict()['locationsId']
validation.ValidateRegion(
region, available_regions=constants.SUPPORTED_TRAINING_REGIONS)
with endpoint_util.AiplatformEndpointOverrides(
version=self._api_version, region=region):
api_client = client.HpTuningJobsClient(version=self._api_version)
algorithm = arg_utils.ChoiceToEnum(args.algorithm,
api_client.AlgorithmEnum())
labels = labels_util.ParseCreateArgs(
args,
api_client.HyperparameterTuningJobMessage().LabelsValue)
response = api_client.Create(
parent=region_ref.RelativeName(),
config_path=args.config,
display_name=args.display_name,
max_trial_count=args.max_trial_count,
parallel_trial_count=args.parallel_trial_count,
algorithm=algorithm,
kms_key_name=validation.GetAndValidateKmsKey(args),
network=args.network,
service_account=args.service_account,
enable_web_access=args.enable_web_access,
enable_dashboard_access=args.enable_dashboard_access,
labels=labels)
log.status.Print(
_HPTUNING_JOB_CREATION_DISPLAY_MESSAGE.format(
id=hp_tuning_jobs_util.ParseJobName(response.name),
command_version=hp_tuning_jobs_util.OutputCommandVersion(
self.ReleaseTrack()),
region=region,
state=response.state))
return response
@base.ReleaseTracks(base.ReleaseTrack.BETA, base.ReleaseTrack.ALPHA)
class CreatePreGa(CreateGa):
"""Create a hyperparameter tuning job."""
_api_version = constants.BETA_VERSION