def Run(self, args):
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
client = versions_api.VersionsClient()
labels = versions_util.ParseCreateLabels(client, args)
framework = flags.FRAMEWORK_MAPPER.GetEnumForChoice(args.framework)
accelerator = flags.ParseAcceleratorFlag(args.accelerator)
return versions_util.Create(client,
operations.OperationsClient(),
args.version,
model=args.model,
origin=args.origin,
staging_bucket=args.staging_bucket,
runtime_version=args.runtime_version,
config_file=args.config,
asyncronous=args.async_,
description=args.description,
labels=labels,
machine_type=args.machine_type,
framework=framework,
python_version=args.python_version,
accelerator_config=accelerator,
min_nodes=args.min_nodes,
max_nodes=args.max_nodes,
metrics=args.metric_targets,
autoscaling_hidden=False)
def _Run(args):
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
models_client = models.ModelsClient()
operations_client = operations.OperationsClient()
models_util.Update(models_client, operations_client, args)
log.UpdatedResource(args.model, kind='ai platform model')
def Run(self, args):
"""This is what gets called when the user runs this command.
Args:
args: an argparse namespace. All the arguments that were provided to this
command invocation.
Returns:
Some value that we want to have printed later.
"""
instances = predict_utilities.ReadInstancesFromArgs(
args.json_request,
args.json_instances,
args.text_instances,
limit=INPUT_INSTANCES_LIMIT)
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
model_or_version_ref = predict_utilities.ParseModelOrVersionRef(
args.model, args.version)
results = predict.Explain(model_or_version_ref, instances)
if not args.IsSpecified('format'):
# default format is based on the response.
args.format = predict_utilities.GetDefaultFormat(
results.get('predictions'))
return results
def _Run(args):
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
client = versions_api.VersionsClient()
return versions_util.Delete(client,
operations.OperationsClient(),
args.version,
model=args.model)
def _Run(args):
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
versions_client = versions_api.VersionsClient()
operations_client = operations.OperationsClient()
version_ref = args.CONCEPTS.version.Parse()
versions_util.Update(versions_client, operations_client, version_ref,
args)
log.UpdatedResource(args.version, kind='AI Platform version')
def Run(self, args):
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
condition = iam_util.ValidateAndExtractCondition(args)
iam_util.ValidateMutexConditionAndPrimitiveRoles(condition, args.role)
return models_util.AddIamPolicyBindingWithCondition(
models.ModelsClient(),
args.model,
args.member,
args.role,
condition)
def Run(self, args):
"""This is what gets called when the user runs this command.
Args:
args: an argparse namespace. All the arguments that were provided to this
command invocation.
Returns:
The specified function with its description and configured filter.
"""
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
condition = iam_util.ValidateAndExtractCondition(args)
iam_util.ValidateMutexConditionAndPrimitiveRoles(
condition, args.role)
return models_util.RemoveIamPolicyBindingWithCondition(
models.ModelsClient(), args.model, args.member, args.role,
condition)
def Run(self, args):
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
client = versions_api.VersionsClient()
labels = versions_util.ParseCreateLabels(client, args)
framework = flags.FRAMEWORK_MAPPER.GetEnumForChoice(args.framework)
accelerator = flags.ParseAcceleratorFlag(args.accelerator)
return versions_util.Create(
client,
operations.OperationsClient(),
args.version,
model=args.model,
origin=args.origin,
staging_bucket=args.staging_bucket,
runtime_version=args.runtime_version,
config_file=args.config,
asyncronous=args.async_,
labels=labels,
description=args.description,
machine_type=args.machine_type,
framework=framework,
python_version=args.python_version,
prediction_class=args.prediction_class,
package_uris=args.package_uris,
service_account=args.service_account,
accelerator_config=accelerator,
explanation_method=args.explanation_method,
num_integral_steps=args.num_integral_steps,
num_paths=args.num_paths,
image=args.image,
command=args.command,
container_args=args.args,
env_vars=args.env_vars,
ports=args.ports,
predict_route=args.predict_route,
health_route=args.health_route,
min_nodes=args.min_nodes,
max_nodes=args.max_nodes,
metrics=args.metric_targets,
containers_hidden=False,
autoscaling_hidden=False)
def GetModelRegion(args):
"""Extract the region from the command line args.
Args:
args: arguments from parser.
Returns:
region, model_regions
region: str, regional endpoint or global endpoint.
model_regions: list, region where the model will be deployed.
Raises:
RegionArgError: if both --region and --regions are specified.
"""
if args.IsSpecified('region') and args.IsSpecified('regions'):
raise RegionArgError(
'Only one of --region or --regions can be specified.')
if args.IsSpecified('regions'):
return 'global', args.regions
if args.IsSpecified('region') and args.region != 'global':
return args.region, [args.region]
region = region_util.GetRegion(args)
if region != 'global':
return region, [region]
log.warning(
'To specify a region where the model will deployed on the global '
'endpoint, please use `--regions` and do not specify `--region`. '
'Using [us-central1] by default on https://ml.googleapis.com. '
'Please note that your model will be inaccessible from '
'https://us-central1-ml.googelapis.com\n'
'\n'
'Learn more about regional endpoints and see a list of available '
'regions: https://cloud.google.com/ai-platform/prediction/docs/'
'regional-endpoints')
return 'global', ['us-central1']
def _Run(args):
"""This is what gets called when the user runs this command.
Args:
args: an argparse namespace. All the arguments that were provided to this
command invocation.
Returns:
A json object that contains predictions.
"""
instances = predict_utilities.ReadInstancesFromArgs(
args.json_request,
args.json_instances,
args.text_instances,
limit=INPUT_INSTANCES_LIMIT)
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
model_or_version_ref = predict_utilities.ParseModelOrVersionRef(
args.model, args.version)
if (args.signature_name is None and
predict_utilities.CheckRuntimeVersion(args.model, args.version)):
log.status.Print(
'You are running on a runtime version >= 1.8. '
'If the signature defined in the model is '
'not serving_default then you must specify it via '
'--signature-name flag, otherwise the command may fail.')
results = predict.Predict(
model_or_version_ref, instances, signature_name=args.signature_name)
if not args.IsSpecified('format'):
# default format is based on the response.
args.format = predict_utilities.GetDefaultFormat(
results.get('predictions'))
return results
def _Run(args):
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
models_client = models.ModelsClient()
operations_client = operations.OperationsClient()
return models_util.Delete(models_client, operations_client, args.model)
def _Run(args):
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
return models.ModelsClient().Get(args.model)
def _Run(args):
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
client = models.ModelsClient()
return models_util.RemoveIamPolicyBinding(client, args.model,
args.member, args.role)
def _Run(args):
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
client = versions_api.VersionsClient()
return versions_util.List(client, model=args.model)
def _Run(args):
region = region_util.GetRegion(args)
with endpoint_util.MlEndpointOverrides(region=region):
return models_util.SetIamPolicy(models.ModelsClient(), args.model,
args.policy_file)
