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) with endpoint_util.MlEndpointOverrides(region=args.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): with endpoint_util.MlEndpointOverrides(region=args.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(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): with endpoint_util.MlEndpointOverrides(region=args.region): client = versions_api.VersionsClient() return versions_util.Delete(client, operations.OperationsClient(), args.version, model=args.model)
def testConnectToRegion(self): existing_override = properties.VALUES.api_endpoint_overrides.ml.Get() with util.MlEndpointOverrides('us-central1'): self.assertEqual(properties.VALUES.api_endpoint_overrides.ml.Get(), 'https://us-central1-ml.googleapis.com/') self.assertEqual(properties.VALUES.api_endpoint_overrides.ml.Get(), existing_override)
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(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) with endpoint_util.MlEndpointOverrides(region=args.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(self, args): with endpoint_util.MlEndpointOverrides(region=args.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)
def Run(self, args): with endpoint_util.MlEndpointOverrides(region=args.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(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(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. """ with endpoint_util.MlEndpointOverrides(region=args.region): client = models.ModelsClient() return models_util.RemoveIamPolicyBinding(client, args.model, args.member, args.role)
def _Run(self, args, support_console_logging=False): with endpoint_util.MlEndpointOverrides(region=args.region): models_client = models.ModelsClient() labels = models_util.ParseCreateLabels(models_client, args) enable_console_logging = (support_console_logging and args.enable_console_logging) model = models_util.Create( models_client, args.model, args, enable_logging=args.enable_logging, enable_console_logging=enable_console_logging, labels=labels, description=args.description) log.CreatedResource(model.name, kind='ml engine 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: The specified function with its description and configured filter. """ with endpoint_util.MlEndpointOverrides(region=args.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): with endpoint_util.MlEndpointOverrides(region=args.region): client = versions_api.VersionsClient() labels = versions_util.ParseCreateLabels(client, args) framework = flags.FRAMEWORK_MAPPER.GetEnumForChoice(args.framework) 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, framework=framework, python_version=args.python_version)
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 Run(self, args): with endpoint_util.MlEndpointOverrides(region=args.region): models_client = models.ModelsClient() operations_client = operations.OperationsClient() models_util.Update(models_client, operations_client, args) log.UpdatedResource(args.model, kind='ml engine model')
def _Run(args): with endpoint_util.MlEndpointOverrides(region=args.region): client = versions_api.VersionsClient() return versions_util.SetDefault(client, args.version, model=args.model)
def _Run(args): with endpoint_util.MlEndpointOverrides(region=args.region): return models.ModelsClient().Get(args.model)
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(self, args): with endpoint_util.MlEndpointOverrides(region=args.region): client = versions_api.VersionsClient() return versions_util.List(client, model=args.model)
def _Run(args): with endpoint_util.MlEndpointOverrides(region=args.region): return locations.LocationsClient().Get(args.location)
def _Run(args): region = region_util.GetRegion(args) with endpoint_util.MlEndpointOverrides(region=region): return models_util.GetIamPolicy(models.ModelsClient(), args.model)
def _Run(args): with endpoint_util.MlEndpointOverrides(region=args.region): return models_util.SetIamPolicy(models.ModelsClient(), args.model, args.policy_file)
def Run(self, args): with endpoint_util.MlEndpointOverrides(region=args.region): client = operations.OperationsClient() return operations_util.Wait(client, args.operation)
def _Run(args): region = region_util.GetRegion(args) with endpoint_util.MlEndpointOverrides(region=region): return models_util.List(models.ModelsClient())
def Run(self, args): with endpoint_util.MlEndpointOverrides(region=args.region): models_client = models.ModelsClient() operations_client = operations.OperationsClient() return models_util.Delete(models_client, operations_client, args.model)
def Run(self, args): with endpoint_util.MlEndpointOverrides(region=args.region): return models_util.GetIamPolicy(models.ModelsClient(), 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): with endpoint_util.MlEndpointOverrides(region=args.region): client = operations.OperationsClient() return operations_util.Describe(client, args.operation)