z  ^SrSSKJr SSKJr SSKJr SSKrSSKrSSKJr SSK J r SSK J r SS K J r SS K Jr SS KJr SS KJr SS KJr SSKJr SSKJr SSKJr SSKJr SSKJr SSKJr SSKJ r \ RB"S\ RD"S\RFSS9SSS9r$\ RB"SSSSS 9r%\ RB"S!SSS"S#9r&\ RB"S$\RN"S%5S&9r(\ RB"S'\RN"S(5S&9r)\ RB"S)\RT"5S\RN"S*5S+9r+\ RB"S,SSS\RN"S-5S.9r,\ RB"S/SSS\RN"S05S.9r-S1r.SS2jr/SS3jr0SS4jr1SS5jr2SS6jr3SS7jr4SS8jr5S9r6S:r7S;r8S<r9S=r:S>r;S?rSBr?SCr@SSDjrASSEjrBSFrCSGrDSHrESSIjrFSJrGSKrHSLrISMrJSNrKSOrLSPrMSQrNSRrOSSrPSTrQSUrRSVrSSWrTSXrUSYrV\R4SZjrXS[\R4S\jrY\R4S]jrZS^r[S_r\\R4S`jr]\R4Sajr^\R4Sbjr_Scr`\R4SdjraSSejrbSfrcSgrdSShjreSSijrfSSjjrgSSkjrhSSljriSSmjrjSn\R4Sojrl\R4SpjrmSqrnSrroSs\R4Stjrp\R4SujrqSvrrSSwjrsSxrtSyruSzrvS{rwS|rxSS}jrySS~jrzSSjr{SSjr|Sr}Sr~SrSrSSjrSSjrSrSrSrSrSrSrSrSrSrSSjrSSjrSSjrSSjrSSjrSSjrSSjrSSjrSSjrSrSrSrSSjrSSjrSSjrSrSSjrg)zFlag definitions for gcloud ai.)absolute_import)division)unicode_literalsN)apis) arg_parsers)base)concepts)deps) constants)errors) region_util)iam_util) resource_args) arg_utils)concept_parsers)presentation_specs) properties) resourcesz--polling-intervalT unlimited<zKNumber of seconds to wait between efforts to fetch the latest log messages.typedefaulthelpz--allow-multiline-logs store_trueFz0Output multiline log messages as single records.)actionrrz --task-namez7If set, display only the logs for this particular task.requiredrr --networkz Full name of the Google Compute Engine network to which the Job is peered with. Private services access must already have been configured. If unspecified, the Job is not peered with any network. r--public-endpoint-enabledzT If true, the deployed index will be accessible through public endpoint. --service-accountz The email address of a service account to use when running the training appplication. You must have the `iam.serviceAccounts.actAs` permission for the specified service account. )rr rz--enable-web-accessao Whether you want Vertex AI to enable [interactive shell access](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) to training containers. If set to ``true'', you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials). rr rrz--enable-dashboard-accessa  Whether you want Vertex AI to enable dashboard built on the training containers. If set to ``true'', you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials). c[RU5 [RU5 [RU5 gN)_POLLING_INTERVAL_FLAG AddToParser _TASK_NAME_ALLOW_MULTILINE_LOGSparsers *lib/googlecloudsdk/command_lib/ai/flags.pyAddStreamLogsFlagsr/us,$$V,  ##F+cL^^UU4SjnURRU5 g)zAdds `--uri` flag to the parser object for list commands. Args: parser: The argparse parser. collection: str, The resource collection name. api_version: str, The API version. cv>[RRURTTS9nUR 5$)N) collection api_version)rREGISTRYParseRelativeNamenameSelfLink)resourceupdatedr4r3s r._GetResourceUri$AddUriFlags.._GetResourceUris:  22 *+3G    r0N) display_info AddUriFunc)r-r3r4r;s `` r. AddUriFlagsr?{s    1r0cU[R:Xa&[R"SSSS9R U5 g[R"SSSS9R U5 g)Nz--modelzID of the uploaded model.Trr zVID of the uploaded model. The alpha and beta tracks also support GDC connected models.)r GA_VERSIONrArgumentr))versionr-s r. AddModelIdArgrEsV $$$MM (k&MM % k&r0c.[R"SSUS9$)Nz--deployed-model-idzId of the deployed model.rArrCr s r.GetDeployedModelIdrI "= r0c,[R"SXS9$)Nz--indexrArGr helper_texts r. GetIndexIdArgrNs y{ FFr0c,[R"SXS9$)Nz--index-endpointrArGrLs r.GetIndexEndpointIdArgrPs ) OOr0c.[R"SSUS9$)Nz--deployed-index-idzId of the deployed index.rArGrHs r.GetDeployedIndexIdrRrJr0cH[R"SUSRUS9S9$)N--display-namezDisplay name of the {noun}.nounr rrrCformatrVr s r.GetDisplayNameArgr[s*  ( / /T / : r0c J[R"SSSSRUS9S9$)N --descriptionFzDescription of the {noun}.rUrrXrUs r.GetDescriptionArgr^-  ' . .D . 9  r0c d[R"SRUS9SSSRUS9S9$)Nz --{noun}-idrUFz User-specified ID of the {noun}.rrXrUs r.GetUserSpecifiedIdArgras; % - 4 4$ 4 ?  r0c0[R"SSSSS9$)Nr!FzZThe full name of the Google Compute Engine network to which the endpoint should be peered.rrGr0r.GetEndpointNetworkArgrds  k  r0c0[R"SSSSS9$)Nz--encryption-kms-key-nameFa3 The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created. rrGrcr0r.GetEncryptionKmsKeyNameArgrfs! !  r0c2[R"SSSSSS9$)N --gdce-zoneFTH The name of the GDCE zone. If set, the endpoint is in GDCE. )r rhiddenrrGrcr0r.GetHiddenGdceZoneArgrks$    r0c0[R"SSSSS9$)NrhFrirrGrcr0r.GetGdceZoneArgrms!   r0c0[R"SSSSS9$)Nz --gdc-zoneFzH The name of the GDC zone. If set, the endpoint is for GDCc. rrGrcr0r. GetGdcZoneArgros!   r0c[R"SSSSSS9RU5 [R"SSS[R"5SS 9RU5 g) Nz --enable-private-service-connectFrz@If true, expose the index endpoint via private service connect. )r rrrz--project-allowlistPROJECTSzTList of projects from which the forwarding rule will target the service attachment. r metavarrr)rrCr)rArgListr,s r.AddPrivateServiceConnectConfigru s]--(   K--      Kr0cN[R"SUSS9RU5 g)z7Add arguments for different types of predict instances.--json-requesta. Path to a local file containing the body of a JSON request. An example of a JSON request: { "instances": [ {"x": [1, 2], "y": [3, 4]}, {"x": [-1, -2], "y": [-3, -4]} ] } This flag accepts "-" for stdin. rWNrrCr)r-r s r.AddPredictInstanceArgrz!%-- "Kr0c.[R"SSSS9$)z(Adds arguments for raw-predict requests.z --requestTa The request to send to the endpoint. If the request starts with the letter '*@*', the rest should be a file name to read the request from, or '*@-*' to read from *stdin*. If the request body actually starts with '*@*', it must be placed in a file. If required, the *Content-Type* header should also be set appropriately, particularly for binary data. rWrGrcr0r.GetRawPredictRequestArgr}7s    r0c\[R"SS[R"[S9SS9$)z,Adds arguments for raw-predict http headers.z--http-headersz HEADER=VALUE value_typez List of header and value pairs to send as part of the request. For example, to set the *Content-Type* and *X-Header*: --http-headers=Content-Type="application/json",X-Header=Value rsrr)rrCrArgDictstrrcr0r.GetRawPredictHeadersArgrIs,    # .  r0cN[R"SUSS9RU5 g)z>Add arguments for different types of direct predict instances.rwa` Path to a local file containing the body of a JSON request. An example of a JSON request: { "inputs": [ {"dtype": "STRING", shape: [1], "string_val": ["hello world"]}, {"dtype": "INT32", shape: [1], "int_val": [42]} ] } This flag accepts "-" for stdin. rWNrxrys r.AddDirectPredictInputsArgrXr{r0cN[R"SUSS9RU5 g)zBAdd arguments for different types of direct raw predict instances.rwa Path to a local file containing the body of a JSON request. An example of a JSON request: { "method_name": "my.method.Predict", "input": "my request bytes" } This flag accepts "-" for stdin. rWNrxrys r.AddDirectRawPredictInputArgrns%-- Kr0cz[R"SS[R"[S9[R SS9$) Add arguments for traffic split.--traffic-splitDEPLOYED_MODEL_ID=VALUErEList of pairs of deployed model id and value to set as traffic split.rsrrr)rrCrrint UpdateActionrcr0r.GetTrafficSplitArgrs5 '   # .  % %   r0cURSS9nURSS[R"[S9[R SS9 URSS S S 9 g ) rFrHrrrrrz--clear-traffic-splitrzkClears the traffic split map. If the map is empty, the endpoint is to not accept any traffic at the moment.)rrN)add_mutually_exclusive_group add_argumentrrrr)r-groups r.AddTrafficSplitGroupArgsrsj  - -u - =%'   # .  % %     8 r0c U[R:Xa[R"S[R "SSS9SS9R U5 [R"S[R "SSS9SS9R U5 [R"S [R"S [RS S 9S S9R U5 gg)z Add arguments for scale to zero.z--min-scaleup-period300s28800s) lower_bound upper_boundzMinimum duration (in seconds) that a deployment will be scaled up before traffic is evaluated for potential scale-down. Defaults to 1 hour if min replica count is 0. rrz--idle-scaledown-periodzDuration (in seconds) without traffic before a deployment is scaled down to zero replicas. Defaults to 1 hour if min replica count is 0. z--initial-replica-countrTrzInitial number of replicas for the deployment resources the model will be scaled up to. Cannot be smaller than min replica count or larger than max replica count. N) r BETA_VERSIONrrCrDurationr) BoundedIntsysmaxsize)r-rDs r.AddScaleToZeroArgsrs &&&MM  ! !f( Kk&MM!  ! !f( Kk&MM!  # #As{{d Ck&9'r0cU(aH[R"S[R"S[R SS9SS9R U5 OG[R"S[R"S[R SS9SS9R U5 [R"S [R"SS S 9S S9R U5 [R"S [R"S[R SS9SS9R U5 [R"SSS9R U5 [R"S[R"[[[R"5S.S/S9SS9R U5 [R"SSSSSS9R U5 U[R:Xaw[R"SSS9R U5 [R"S[SS9R U5 [R"S [SS!S"9R U5 [R"S#[R"[[S$.S%/S9S&RS'R[U5R Vs/sHnS(RU5PM sn55S9R U5 g)s snf)*z'Add arguments for prediction resources.--min-replica-countrTra Minimum number of machine replicas for the deployment resources the model will be deployed on. If specified, the value must be equal to or larger than 1. If not specified and the uploaded models use dedicated resources, the default value is 1. rra Minimum number of machine replicas for the deployment resources the model will be deployed on. For normal deployments, the value must be equal to or larger than 1. If the value is 0, the deployment will be enrolled in the scale-to-zero feature. If not specified and the uploaded models use dedicated resources, the default value is 1. NOTE: DeploymentResourcePools (model-cohosting) is currently not supported for scale-to-zero deployments. --max-replica-counti)rz_Maximum number of machine replicas for the deployment resources the model will be deployed on. z--required-replica-countz Required number of machine replicas for the deployment resources the model will be considered successfully deployed. This value must be greater than or equal to 1 and less than or equal to min-replica-count. --machine-typeThe machine resources to be used for each node of this deployment. For available machine types, see https://cloud.google.com/ai-platform-unified/docs/predictions/machine-types. r"z--reservation-affinity)reservation-affinity-typekeyvaluesrspec required_keyszA ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. z--spotrFz7If true, schedule the deployment workload on Spot VMs. rrr rz--tpu-topologyzCloudTPU topology to use for this deployment. Required for multihost CloudTPU deployments: https://cloud.google.com/kubernetes-engine/docs/concepts/tpus#topology. z--multihost-gpu-node-countzgThe number of nodes per replica for multihost GPU deployments. Required for multihost GPU deployments. z--gpu-partition-sizezThe partition size of the GPU accelerator. This can be used to partition a single GPU into multiple smaller GPU instances. See https://cloud.google.com/kubernetes-engine/docs/how-to/gpus-multi#multi-instance_gpu_partitions for more details. )rrjrz --accelerator)rcountraManage the accelerator config for GPU serving. When deploying a model with Compute Engine Machine Types, a GPU accelerator may also be selected. *type*::: The type of the accelerator. Choices are {}. *count*::: The number of accelerators to attach to each machine running the job. This is usually 1. If not specified, the default value is 1. For example: `--accelerator=type=nvidia-tesla-k80,count=1`, '{}'N)rrCrrrrr)rrrtr rrrYjoinGetAcceleratorTypeMapperchoices)r-rDdrpcs r.AddPredictionResourcesArgsrsr MM  # #As{{d C k&MM  # #As{{d C  k&--  ! !! 6 K--  ! !!S[[D A K-- K--   +.#++- 55   K--   K &&&MMk&MM$ k&MM  k&--        128 ))/8@@ @!mmA@  2)4K  s"KcT[R"SS[R"[[ S9[R SRSR[[RR55Vs/sHnSRU5PM sn55S9$s snf)z+Add arguments for autoscaling metric specs.z--autoscaling-metric-specszMETRIC-NAME=TARGET)key_typera?Metric specifications that control autoscaling behavior. At most one entry is allowed per metric. *METRIC-NAME*::: Resource metric name. Choices are {}. *TARGET*::: Target value for the given metric. For `cpu-usage` and `gpu-duty-cycle`, the target is the target resource utilization in percentage (1% - 100%). For `request-counts-per-minute`, the target is the number of requests per minute per replica. For example, to set target CPU usage to 70% and target requests to 600 per minute per replica: `--autoscaling-metric-specs=cpu-usage=70,request-counts-per-minute=600` rrr) rrCrrrrrrYrsortedr !OP_AUTOSCALING_METRIC_NAME_MAPPERkeys)rs r.GetAutoscalingMetricSpecsArgr[s ""    <  % %  F ))==BBD !mmA  ' ( s=B%c h[R"S[R"S[R SS9SR U5S9RU5 [R"S[SR U5S9RU5 [R"S S S 9RU5 g ) z+Add arguments for the deployment resources.rrTrzMinimum number of machine replicas the {} will be always deployed on. If specified, the value must be equal to or larger than 1. rrzEMaximum number of machine replicas the {} will be always deployed on.rrr"N) rrCrrrrrYr)rr- resource_types r.AddDeploymentResourcesArgsr{s--  ! !!S[[D A  F= K--  &} 5 K-- Kr0c[R"SS[R"5SR U5S9R U5 g)z)Add arguments for the reserved IP ranges.z--reserved-ip-rangesRESERVED_IP_RANGESz2List of reserved IP ranges {} will be deployed to.rNrrCrrtrYr)rs r.AddReservedIpRangesArgsrs=--"    > E E Kr0ct[R"S[SRU5S9R U5 g)z&Add arguments for the encryption spec.--kms-key-nameaCloud KMS resource identifier of the customer managed encryption key used to protect a {}. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. Key needs to be in the same region as where the compute resource is created rN)rrCrrYr)rs r.AddEncryptionSpecArgrs1--    F= Kr0cX[R"SS[SS9RU5 g)z#Add arguments for deployment group.z--deployment-groupDEPLOYMENT_GROUPabDeployment group can be no longer than 64 characters (eg:`test`, `prod`). If not set, we will use the `default` deployment group. Creating deployment_groups with `reserved_ip_ranges` is a recommended practice when the peered network has multiple peering ranges.This creates your deployments from predictable IP spaces for easier traffic administration. rN)rrCrr)r,s r.AddDeploymentGroupArgrs(--   Kr0c$[R"SS[R"5SR U5S9R U5 [R"SS[R"5SR U5S9R U5 g) z Add arguments for auth provider.z --audiences AUDIENCESzList of JWT audiences that are allowed to access a {}. JWT containing any of these audiences (https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32#section -4.1.3) will be accepted. rz--allowed-issuersALLOWED_ISSUERSzList of allowed JWT issuers for a {}. Each entry must be a valid Google service account, in the following format: `service-account-name@project-id.iam.gserviceaccount.com` Nrrs r.AddAuthConfigArgsrsx--       VM K--       VM Kr0c[R"S[R"[[S.SS/S9SSSS 9R U5 g ) z(Add arguments for PSC automation config.z--psc-automation-configs) project-idnetworkrrrappendFaTA pair of `project-id` and `network` the PSC index will be deployed to. For example: `--psc-automation-configs=project-id=my-project,network=my-network`. For multiple networks, this flag can be repeated: `--psc-automation-configs=project-id=my-project,network=my-network --psc-automation-configs=project-id=my-project2,network=my-network2` )rrr rN)rrCrrrr)r,s r.AddPscAutomationConfigsArgsrsH--   !c2%y1  Kr0c2[R"SSSSSS9$)Nz--enable-access-loggingrFzIf true, online prediction access logs are sent to Cloud Logging. These logs are standard server access logs, containing information like timestamp and latency for each prediction request. rrGrcr0r.GetEnableAccessLoggingArgrs$     r0c2[R"SSSSSS9$)Nz--enable-container-loggingrFzIf true, the container of the deployed model instances will send `stderr` and `stdout` streams to Cloud Logging. Currently, only supported for custom-trained Models and AutoML Tabular Models. rrGrcr0r.GetEnableContainerLoggingArgrs$ "    r0c2[R"SSSSSS9$)Nz--disable-container-loggingrFalFor custom-trained Models and AutoML Tabular Models, the container of the deployed model instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/stackdriver/pricing). User can disable container logging by setting this flag to true. rrGrcr0r.GetDisableContainerLoggingArgrs$ #    r0c0[R"SSSSS9$)Nz --request-response-logging-tableFzBigQuery table uri for prediction request & response logging. You can provide table uri that does not exist, it will be created for you. Value should be provided in format: bq://``PROJECT_ID''/``DATASET''/``TABLE'' rrGrcr0r.!GetRequestResponseLoggingTableArgr%s! (   r0c:[R"SSS[SS9$)Nz--request-response-logging-rateFzJPrediction request & response sampling rate for logging to BigQuery table.)r rrrrrCfloatrcr0r. GetRequestResponseLoggingRateArgr4s" '  [  r0c2[R"SSSSSS9$)Nz"--disable-request-response-loggingrFz.Disable prediction request & response logging.r%rGrcr0r.#GetDisableRequestResponseLoggingArgr>s" *  ?  r0cURSS9n[5RU5 [5RU5 g)z:Adds arguments for request-response logging configuration.FrHN) add_grouprr)r)r-logging_config_groups r.(AddRequestResponseLoggingConfigGroupArgsrHs:))5)9#%112FG"$001EFr0cjURSS9n[5RU5 [U5 g)zAAdds arguments for update request-response logging configuration.FrHN)rrr)r)r-logging_update_groups r..AddRequestResponseLoggingConfigUpdateGroupArgsrOs1<#> ?   "K   r0modelc \[R"SU[R[US9SS9$)Nz$aiplatform.projects.locations.modelsrF resource_name projectsId locationsIddisable_auto_completers)r ResourceSpec DEFAULT_PROJECT_ATTRIBUTE_CONFIGrrrs r.GetModelResourceSpecrrs1   ,!::'K@#  r0c[R"SS[US9[RS9n[R R SUSRU5SS9RU5 g ) auAdd a resource argument for a Vertex AI region. NOTE: Must be used only if it's the only resource arg in the command. Args: parser: the parser for the command. verb: str, the verb to describe the resource, such as 'to update'. prompt_func: function, the function to prompt a list of available regions and return a string of the region that is selected by user. zaiplatform.projects.locationsrr)rrrrzCloud region {}.TrHN) r rrrr ConceptParser ForResourcerYr))r-verbrregion_resource_specs r.AddRegionResourceArgr ~sj"..%'K@:: ++% , Kr0cz[R"[RS[R[ 5SS9$)N operationFr)r rr DEFAULT_OPERATION_COLLECTIONrrrcr0r.GetDefaultOperationResourceSpecrs3   ,,::')#  r0cvSn[RRU[5SSS9R U5 g)z2Add a resource argument for a Vertex AI operation.rzThe ID of the operation.TrHN)rrr rr))r-rs r.AddOperationResourceArgrs;-++%'  , Kr0cSn[RRU[US9SR U5SS9R U5 g)aAdd a resource argument for a Vertex AI model. NOTE: Must be used only if it's the only resource arg in the command. Args: parser: the parser for the command. verb: str, the verb to describe the resource, such as 'to update'. prompt_func: function, the function to prompt for region from list of available regions which returns a string for the region selected. Default is region_util.PromptForRegion which contains three regions, 'us-central1', 'europe-west4', and 'asia-east1'. rrz Model {}.TrHNrrr rrYr)r-r rr7s r.AddModelResourceArgrsJ $++ {3 , Kr0cSn[RRU[US9SR U5SS9R U5 g)aAdd a resource argument for a Vertex AI model version. NOTE: Must be used only if it's the only resource arg in the command. Args: parser: the parser for the command. verb: str, the verb to describe the resource, such as 'to update'. prompt_func: function, the function to prompt for region from list of available regions which returns a string for the region selected. Default is region_util.PromptForRegion which contains three regions, 'us-central1', 'europe-west4', and 'asia-east1'. model_versionrzModel version {}.TrHNrrs r.AddModelVersionResourceArgrsJ $++ {3  & , Kr0c [USUS9 [R"SSSS9RU5 [R"SSS S9RU5 [R"S SS S9RU5 [R"S SS S9RU5 [R"SSS9RU5 UR SS[ R "5[ RSS9 UR S[ R"5S[ RSS9 UR SS[ R"5SS9 UR SS[ R"[ R"SS 5S!9[ RS"S9 UR S#S[ R"[ R"SS 5S!9[ RS$S9 UR S%S&S9 UR S'S(S9 UR S)[S*S+9 UR S,[S-S+9 UR S.[ R"5S/S0S19 UR S2[S3S+9 UR S4[S5S+9 UR S6[ R"5S7S8S19 UR S9[S:S+9 UR S;[SS9 UR S?S@S9 UR SA[SBS+9 UR SC[SDS+9 UR SE[SFS+9 UR SG[SHS+9 UR SIS[ R "5[ RSJS9 UR SK[SLS+9 UR SM[SNS+9 UR SOSP[ R"5[ RSQS9 UR SRS[ R "5[ RSSS9 gT)UaUAdds flags for UploadModel. Args: parser: the parser for the command. prompt_func: function, the function to prompt for region from list of available regions which returns a string for the region selected. Default is region_util.PromptForRegion which contains three regions, 'us-central1', 'europe-west4', and 'asia-east1'. zto upload modelrrTTzDisplay name of the model.rWr]FzDescription of the model.z--version-descriptionz!Description of the model version.z--container-image-uriziURI of the Model serving container file in the Container Registry (e.g. gcr.io/myproject/server:latest). z--artifact-urizUPath to the directory containing the Model artifact and any of its supporting files. r"z--container-env-vars KEY=VALUEz8List of key-value pairs to set as environment variables.rz--container-commandCOMMANDzgEntrypoint for the container image. If not specified, the container image's default entrypoint is run. )rrsrrz--container-argsARGzComma-separated arguments passed to the command run by the container image. If not specified and no `--command` is provided, the container image's default command is used. rz--container-portsPORTri) element_typez^Container ports to receive http requests at. Must be a number between 1 and 65535, inclusive. z--container-grpc-portsz^Container ports to receive grpc requests at. Must be a number between 1 and 65535, inclusive. z--container-predict-routez>HTTP path to send prediction requests to inside the container.z--container-health-routez8HTTP path to send health checks to inside the container.z&--container-deployment-timeout-secondszDeployment timeout in seconds.rz!--container-shared-memory-size-mbzZThe amount of the VM memory to reserve as the shared memory for the model in megabytes. z--container-startup-probe-execSTARTUP_PROBE_EXECzzExec specifies the action to take. Used by startup probe. An example of this argument would be ["cat", "/tmp/healthy"]. )rrsrz(--container-startup-probe-period-secondszbHow often (in seconds) to perform the startup probe. Default to 10 seconds. Minimum value is 1. z)--container-startup-probe-timeout-secondszgNumber of seconds after which the startup probe times out. Defaults to 1 second. Minimum value is 1. z--container-health-probe-execHEALTH_PROBE_EXECzyExec specifies the action to take. Used by health probe. An example of this argument would be ["cat", "/tmp/healthy"]. z'--container-health-probe-period-secondszaHow often (in seconds) to perform the health probe. Default to 10 seconds. Minimum value is 1. z(--container-health-probe-timeout-secondszfNumber of seconds after which the health probe times out. Defaults to 1 second. Minimum value is 1. z--explanation-methodzfMethod used for explanation. Accepted values are `integrated-gradients`, `xrai` and `sampled-shapley`.z--explanation-metadata-filezmPath to a local JSON file that contains the metadata describing the Model's input and output for explanation.z--explanation-step-countzANumber of steps to approximate the path integral for explanation.z--explanation-path-countzaNumber of feature permutations to consider when approximating the Shapley values for explanation.z --smooth-grad-noisy-sample-countzNumber of gradient samples used for approximation at explanation. Only applicable to explanation method `integrated-gradients` or `xrai`.z--smooth-grad-noise-sigmazSingle float value used to add noise to all the features for explanation. Only applicable to explanation method `integrated-gradients` or `xrai`.z$--smooth-grad-noise-sigma-by-featurea Noise sigma by features for explanation. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients. Only applicable to explanation method `integrated-gradients` or `xrai`.z--parent-modelzResource name of the model into which to upload the version. Only specify this field when uploading a new version. Value should be provided in format: projects/``PROJECT_ID''/locations/``REGION''/models/``PARENT_MODEL_ID'' z --model-idzcID to use for the uploaded Model, which will become the final component of the model resource name.z--version-aliasesVERSION_ALIASESzAliases used to reference a model version instead of auto-generated version ID. The aliases mentioned in the flag will replace the aliases set in the model.z--labelsaJLabels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. N) r rrCr)rrrrrtrrrr)r-rs r.AddUploadModelFlagsr#sv0kJ--,HK--,GK-- .K-- K--  K     % % E        % %               K,B,B1e,L M  % %       K,B,B1e,L M  % %    ! K  E .  +  )   &    "   0   1   %    !   /   0    C # 7   N    -  (    !  /  ,     % % P        3       % % '        % %  r0c[R"SS[R"5SS9R U5 UR S[ SS9 UR S[S S S 9 UR S [S SS 9 UR SSS9 g)zgAdds flags for example-based explanation for UploadModel. Args: parser: the parser for the command. z--urisURISzyCloud Storage bucket paths where training data is stored. Should be used only when the explanation method is `examples`. rz--explanation-neighbor-countzxThe number of items to return when querying for examples. Should be used only when the explanation method is `examples`.rz--explanation-modalityMODALITY_UNSPECIFIEDa.Preset option specifying the modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. Accepted values are `IMAGE`, `TEXT` and `TABULAR`. Should be used only when the explanation method is `examples`.rz--explanation-queryPRECISEzPreset option controlling parameters for query speed-precision trade-off. Accepted values are `PRECISE` and `FAST`. Should be used only when the explanation method is `examples`.z1--explanation-nearest-neighbor-search-config-fileaPath to a local JSON file that contains the configuration for the generated index, the semantics are the same as metadata and should match NearestNeighborSearchConfig. If you specify this parameter, no need to use `explanation-modality` and `explanation-query` for preset. Should be used only when the explanation method is `examples`. An example of a JSON config file: { "contentsDeltaUri": "", "config": { "dimensions": 50, "approximateNeighborsCount": 10, "distanceMeasureType": "SQUARED_L2_DISTANCE", "featureNormType": "NONE", "algorithmConfig": { "treeAhConfig": { "leafNodeEmbeddingCount": 1000, "leafNodesToSearchPercent": 100 } } } } r"N)rrCrrtr)rrrr,s r. AddUploadModelFlagsForSimilarityr(s --      K$  B   $ =     =   9 r0c[USUS9 [R"SSSS9RU5 [R"SSS 9RU5 UR S S 9nUR S [ S S9 UR S[ SS9 g)zAdds flags for AddCopyModelFlags. Args: parser: the parser for the command. prompt_func: function, the function to prompt a list of available regions and return a string of the region that is selected by user. zto copy the model intorz--source-modelTzThe resource name of the Model to copy. That Model must be in the same Project. Format: `projects/{project}/locations/{location}/models/{model}`. rWraThe Cloud KMS resource identifier of the customer managed encryption key used to protect the resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as the destination region of the model to be copied. r"FrHz--destination-model-idzCopy source_model into a new Model with this ID. The ID will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen. rz--destination-parent-modelzSpecify this field to copy source_model into this existing Model as a new version. Format: `projects/{project}/locations/{location}/models/{model}`. N)r rrCr)rrr)r-rrs r.AddCopyModelFlagsr*(s &K-- K--  K  - -u - =%  "  r0cH[R"SUSRUS9S9$)Nz--metadata-filez]Path to a local JSON file that contains the additional metadata information about the {noun}.rUrWrXrZs r.GetMetadataFilePathArgr,[s*  ++16t6+<  r0cH[R"SSSRUS9S9$)Nz--metadata-schema-uriFzdPoints to a YAML file stored on Google Cloud Storage describing additional information about {noun}.rUrWrXrUs r.GetMetadataSchemaUriArgr.fs*  228&d&2C  r0c[RRS[5SR U5SS9R U5 g)zAdd a resource argument for a Vertex AI index. NOTE: Must be used only if it's the only resource arg in the command. Args: parser: the parser for the command. verb: str, the verb to describe the resource, such as 'to update'. indexz Index {}.TrHN)rrr GetIndexResourceSpecrYr)r-r s r.AddIndexResourceArgr3qs?++ #%{'9'9$'?$,Kr0c [R"[RU[R[ [ R"[R5S9SS9$NrFr) r rr INDEXES_COLLECTIONrrr GetPromptForRegionFuncSUPPORTED_OP_REGIONSrs r.r1r1sN   ""!::'!88,,  $  r0cURUS9n[U5RU5 [U5RU5 g)z>Add datapoint source group to the parser for StreamUpdate API.rHN)rGetDatapointsFilePathArgr)GetIndexDatapointIdsArg)rVr-r datapoint_source_groups r.&AddDatapointSourceGroupForStreamUpdater>sE!>>?4 ,,-CD$++,BCr0cH[R"SUSRUS9S9$)Nz--datapoints-from-filez\Path to a local JSON file that contains the data points that need to be added to the {noun}.rUrWrXrZs r.r;r;s*  %%+VV%6  r0cX[R"SUS[R"5SS9$)Nz --update-maskUPDATE_MASK_PATHa=Update mask is used to specify the fields to be overwritten in the datapoints by the update. The fields specified in the update_mask are relative to each IndexDatapoint inside datapoints, not the full request. Updatable fields: * Use --update-mask=`all_restricts` to update both `restricts` and `numeric_restricts`. rrrrCrrtrHs r.GetDynamicMetadataUpdateMaskArgrCs-        r0c r[R"SUS[R"5SR US9S9$)Nz--datapoint-ids DATAPOINT_IDSz:List of index datapoint ids to be removed from the {noun}.rUrr)rrCrrtrYrZs r.r<r<s?     G N N O   r0c6[R"SUSSS.SS9$)Nz--index-update-methodzkcan update datapoints with `upsert-datapoints` and`delete-datapoints` and will be applied nearly real-time.zXcan update index with `gcloud ai indexes update` usingdatapoints files on Cloud Storage.)z stream-updatez batch-updatezThe update method to use with this index. Choose `stream-update` or `batch-update` (case insensitive). If not set, batch update will be used by default. )r rhelp_str)rChoiceArgumentrHs r.GetIndexUpdateMethodrIs0  J3  r0deployment_resource_poolc x[R"[RU[R[ US9SS9$r5)r rr $DEPLOYMENT_RESOURCE_POOLS_COLLECTIONrrrs r.%GetDeploymentResourcePoolResourceSpecrMs7   44!::'K@#  r0c[RRS[US9SR U5SS9R U5 g)aAdd a resource argument for a Vertex AI deployment resource pool. NOTE: Must be used only if it's the only resource arg in the command. Args: parser: the parser for the command. verb: str, the verb to describe the resource, such as 'to update'. prompt_func: function, the function to prompt for region from list of available regions. Default is region_util.PromptForDeploymentResourcePoolSupportedRegion rJr The deployment resource pool {}.TrHN)rrr rMrYr)r-r rs r.AddDeploymentResourcePoolArgrQsE ++ + D(//5 , Kr0c [R"[R"S[ 5SR U5SS9/5R U5 g)Nz--shared-resourcesrOT)prefixes)rrrResourcePresentationSpecrMrYr)r2s r.AddSharedResourcesArgrUsI11  / 1 , 3 3D 9 ![r0c,[R"SSS9$)Nr7zThe endpoint's id.r"rGrcr0r. GetEndpointIdrWs v$8 99r0endpointc x[R"[RU[R[ US9SS9$r5)r rr ENDPOINTS_COLLECTIONrrrs r.GetEndpointResourceSpecr[s7   $$!::'K@#  r0c[RRS[US9SR U5SS9R U5 g)aAdd a resource argument for a Vertex AI endpoint. NOTE: Must be used only if it's the only resource arg in the command. Args: parser: the parser for the command. verb: str, the verb to describe the resource, such as 'to update'. prompt_func: function, the function to prompt for region from list of available regions. Default is region_util.PromptForRegion which contains three regions, 'us-central1', 'europe-west4', and 'asia-east1'. rXrzThe endpoint {}.TrHN)rrr r[rYr)rPs r.AddEndpointResourceArgr]sE+++6% , Kr0c[RRS[5SR U5SS9R U5 g)zAdd a resource argument for a Vertex AI index endpoint. NOTE: Must be used only if it's the only resource arg in the command. Args: parser: the parser for the command. verb: str, the verb to describe the resource, such as 'to update'. index_endpointzThe index endpoint {}.TrHN)rrr GetIndexEndpointResourceSpecrYr)r2s r.AddIndexEndpointResourceArgra*sC++"$%%d+ , Kr0c [R"[RU[R[ [ R"[R5S9SS9$r5) r rr INDEX_ENDPOINTS_COLLECTIONrrr r7r8r9s r.r`r`;sN   **!::'!88,,  $  r0c,[R"SSS9$)zAdd arguments for VPC network.r!za The Google Compute Engine network name to which the IndexEndpoint should be peered. r"rGrcr0r. GetNetworkArgreJs   r0c2[R"SSSSSS9$)z*Add arguments for public endpoint enabled.r#rFzU If true, the deployed index will be accessible through public endpoint. r%rGrcr0r.GetPublicEndpointEnabledArgrgTs$ !   r0c,[R"SSS9$)Nztensorboard-run-idz-ID of the tensorboard run for the {resource}.r7rr rrcr0r.TensorboardRunAttributeConfigrkas  2 2 ? r0c,[R"SSS9$)Nztensorboard-experiment-idz4ID of the tensorboard experiment for the {resource}.rirjrcr0r.$TensorboardExperimentAttributeConfigrmhs  2 2 &F r0c,[R"SSS9$)Nztensorboard-idz)ID of the tensorboard for the {resource}.rirjrcr0r.TensorboardAttributeConfigroos  2 2 ; r0c [R"[RU[ 5[ 5[ 5[R[5SS9$)NF)rtensorboardsId experimentsIdrunsIdrrr) r rr "TENSORBOARD_TIME_SERIES_COLLECTIONrormrkrrr9s r.$GetTensorboardTimeSeriesResourceSpecruvsG   22!/18: * ,::')#  r0c [R"[RU[ 5[ 5[R [5SS9$)NF)rrqrrrrr)r rr TENSORBOARD_RUNS_COLLECTIONrormrrr9s r.GetTensorboardRunResourceSpecrxs?   ++!/18:::')# r0c [R"[RU[ 5[R [ 5SS9$)NF)rrqrrr)r rr "TENSORBOARD_EXPERIMENTS_COLLECTIONrorrr9s r.$GetTensorboardExperimentResourceSpecr{s;   22!/1::')#  r0cz[R"[RU[R[ 5SS9$)NFr)r rr TENSORBOARDS_COLLECTIONrrr9s r.GetTensorboardResourceSpecr~s3   ''!::')#  r0c[RRS[5SR U5SS9R U5 g)zAdd a resource argument for a Vertex AI Tensorboard time series. NOTE: Must be used only if it's the only resource arg in the command. Args: parser: the parser for the command. verb: str, the verb to describe the resource, such as 'to update'. tensorboard_time_serieszThe Tensorboard time series {}.TrHN)rrr rurYr)r2s r.#AddTensorboardTimeSeriesResourceArgrsC++*,'..t4 , Kr0c[RRS[5SR U5SS9R U5 g)zAdd a resource argument for a Vertex AI Tensorboard run. NOTE: Must be used only if it's the only resource arg in the command. Args: parser: the parser for the command. verb: str, the verb to describe the resource, such as 'to update'. tensorboard_runzThe Tensorboard run {}.TrHN)rrr rxrYr)r2s r.AddTensorboardRunResourceArgrsC++#%&&t, , Kr0c[RRS[5SR U5SS9R U5 g)zAdd a resource argument for a Vertex AI Tensorboard experiment. NOTE: Must be used only if it's the only resource arg in the command. Args: parser: the parser for the command. verb: str, the verb to describe the resource, such as 'to update'. tensorboard_experimentzThe Tensorboard experiment {}.TrHN)rrr r{rYr)r2s r.#AddTensorboardExperimentResourceArgrsC++*,&--d3 , Kr0c[RRS[5SR U5SS9R U5 g)zAdd a resource argument for a Vertex AI Tensorboard. NOTE: Must be used only if it's the only resource arg in the command. Args: parser: the parser for the command. verb: str, the verb to describe the resource, such as 'to update'. tensorboardzThe tensorboard {}.TrHN)rrr r~rYr)r2s r.AddTensorboardResourceArgrsC++ """4( , Kr0c.[R"SSUS9$)Nz--tensorboard-experiment-idz!Id of the Tensorboard experiment.rArGrHs r.GetTensorboardExperimentIdArgrs # . r0c.[R"SSUS9$)Nz--tensorboard-run-idzID of the Tensorboard run.rArGrHs r.GetTensorboardRunIdArgrs  ' r0c J[R"SSSSRUS9S9$)Nz --plugin-nameFzPlugin name of the {noun}.rUrrXrUs r.GetPluginNameArgrr_r0c J[R"SSSSRUS9S9$)Nz --plugin-dataFzPlugin data of the {noun}.rUrrXrUs r.GetPluginDataArgrr_r0c6[R"S[SS9$)Nz--max-data-pointsz8Max data points to read from the Tensorboard time seriesrrrCrrcr0r.(AddTensorboardTimeSeriesMaxDataPointsArgrs   E r0cH[R"SSSRUS9S9$)Nz--filterzFilter for the {noun}.rU)rrrXrUs r. AddFilterArgrs) $%=%D%D$%D%O r0c Ucg[S[U5R55nURSS5nX2;aT[R "SR SRUVs/sHnSR U5PM sn555eURSS5nUS ::a[R "S 5eU[R:XaA[R"[R[RU5RnO@[R"[R[RU5Rn[ R""X6R$5nU"XWS 9$s snf) z;Validates and returns an accelerator config message object.Nc3$# UHov M g7fr'rc.0rs r. 'ParseAcceleratorFlag.. sDCQqCrzBThe type of the accelerator can only be one of the following: {}. rrrrrz5The count of the accelerator must be greater than 0. )acceleratorCountacceleratorType)listrrgetr ArgumentErrorrYrr rrGetMessagesModuleAI_PLATFORM_API_NAMEAI_PLATFORM_API_VERSION'GoogleCloudAiplatformV1beta1MachineSpec"GoogleCloudAiplatformV1MachineSpecr ChoiceToEnumAcceleratorTypeValueValuesEnum) acceleratorrDtypesraw_typeraccelerator_countaccelerator_msgaccelerator_types r.ParseAcceleratorFlagrs\  D27;CCD D% __VT *(      F49961fmmA&6 78 ::"oogq1!      &&&,,&&))'2.- ,,&&))'2)(++>> ( '7s+E>cU[R:Xaa[R"S[R "[R [RU5RRSSSS9$[R"S[R "[R [RU5RRSSSS9$)z0Get a mapper for accelerator type to enum value.zgeneric-acceleratorz$The available types of accelerators.c$URS5$NNVIDIA startswithxs r.*GetAcceleratorTypeMapper..Gs h!7r0F)rGinclude_filterr c$URS5$rrrs r.rrQs q||H5r0) r rrChoiceEnumMapperrrrrrrr)rDs r.rr=s &&&  % %   * *  - -g 6  2 12P2P77    # #   ( (  + +G 4 +*+I+I55  r0cUcg[S[5R55nURSS5nX2;a;[R "SR SRSU5555eU[R:XaA[R"[R[RU5RnO@[R"[R[RU5RnU"[ R""UUR$5S9nURSS5bURS5UlURS S5bURS 5UlU$) zCValidates and returns a reservation affinity config message object.Nc3$# UHov M g7fr'rcrs r.r/ParseReservationAffinityFlag..ZsEDQqDrrzKThe type of the reservation affinity can only be one of the following: {}. rc3D# UHnSRU5v M g7f)rN)rYrs r.rr_s5u!V]]1%%us )reservationAffinityTyperr)r GetReservationAffinityTypeMapperrrr rrYrr rrrrr/GoogleCloudAiplatformV1beta1ReservationAffinity*GoogleCloudAiplatformV1ReservationAffinityrr&ReservationAffinityTypeValueValuesEnumrr)reservation_affinityrDrrreservation_affinity_msgs r.ParseReservationAffinityFlagrVsb!  E:<DDE E% ! % %&A4 H(      F4995u5 56 88 &&&#55&&))'2 65 $55&&))'2 106'44  " I I h-9&:&>&>x&H#eT*6#7#;#;E#B !!r0c[R"S[R"[R [R [R5RRSSS9$)z9Get a mapper for reservation affinity type to enum value.rz,The available types of reservation affinity.F)rGr ) rrrrr rrrBrrrcr0r.rrwsW  # #!   ( (  + +I,@,@ A 323Y3Y= r0c2Sn[R"XUS9 g)z3Add the --kms-key resource arg to the given parser.zlThe 'Vertex AI Service Agent' service account must hold permission 'Cloud KMS CryptoKey Encrypter/Decrypter')permission_infoN)kms_resource_argsAddKmsKeyResourceArg)r-r9rs r.rrs!>(( r0c.[R"SSUS9$)Nz --endpointzId of the endpoint.rArGrHs r.GetEndpointIdArgrs . r0cX[R"SS[R"5SUS9$)Nz--emailsEMAILSzIComma-separated email address list. e.g. --emails=a@gmail.com,b@gmail.com)rsrrr rBrHs r. GetEmailsArgrs/      .  r0c Z[R"SS[R"5/SUS9$)Nz--notification-channelsNOTIFICATION_CHANNELSzComma-separated notification channel list. e.g. --notification-channels=projects/fake-project/notificationChannels/123,projects/fake-project/notificationChannels/456)rsrrrr rBrHs r.GetNotificationChannelsArgrs3 %     C  r0c:[R"S[USUS9$)Nz--prediction-sampling-ratezPrediction sampling rate.rrrr rr rs r.GetPredictionSamplingRateArgrs" "  &  r0c:[R"S[USUS9$)Nz--monitoring-frequencyz%Monitoring frequency, unit is 1 hour.rrrs r.GetMonitoringFrequencyArgrs"   2  r0c.[R"SSUS9$)Nz--predict-instance-schemaz YAML schema file uri(Google Cloud Storage) describing the format of a single instance, which are given to format this Endpoint's prediction. If not set, predict schema will be generated from collected predict requests. rArGrHs r.GetPredictInstanceSchemaArgrs !  r0c0[R"SSUUS9$)Nz--analysis-instance-schemaz YAML schema file uri(Google Cloud Storage) describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. )rrjr rG)r rjs r.GetAnalysisInstanceSchemaArgrs# "  r0c.[R"SSUS9$)Nz--sample-predict-requestaW Path to a local file containing the body of a JSON object. Same format as [PredictRequest.instances][], this can be set as a replacement of predict-instance-schema. If not set, predict schema will be generated from collected predict requests. An example of a JSON request: {"x": [1, 2], "y": [3, 4]} rArGrHs r.GetSamplingPredictRequestArgrs     r0c8[R"S[SUS9$)Nz --log-ttlzL TTL of BigQuery tables in user projects which stores logs(Day-based unit). )rrr rrHs r.GetMonitoringLogTtlArgrs#     r0c,[R"SSS9$)Nz--monitoring-config-from-filea~ Path to the model monitoring objective config file. This file should be a YAML document containing a `ModelDeploymentMonitoringJob`(https://cloud.google.com/vertex-ai/docs/reference/rest/v1beta1/projects.locations.modelDeploymentMonitoringJobs#ModelDeploymentMonitoringJob), but only the ModelDeploymentMonitoringObjectiveConfig needs to be configured. Note: Only one of --monitoring-config-from-file and other objective config set, like --feature-thresholds, --feature-attribution-thresholds needs to be set. Example(YAML): modelDeploymentMonitoringObjectiveConfigs: - deployedModelId: '5251549009234886656' objectiveConfig: trainingDataset: dataFormat: csv gcsSource: uris: - gs://fake-bucket/training_data.csv targetField: price trainingPredictionSkewDetectionConfig: skewThresholds: feat1: value: 0.9 feat2: value: 0.8 - deployedModelId: '2945706000021192704' objectiveConfig: predictionDriftDetectionConfig: driftThresholds: feat1: value: 0.3 feat2: value: 0.4 r"rGrcr0r.GetMonitoringConfigFromFilers %! $ $r0cr[R"SS[R"SS9[RSS9$)Nz--feature-thresholdsrTallow_key_onlyaq List of feature-threshold value pairs(Apply for all the deployed models under the endpoint, if you want to specify different thresholds for different deployed model, please use flag --monitoring-config-from-file or call API directly). If only feature name is set, the default threshold value would be 0.3. For example: `--feature-thresholds=feat1=0.1,feat2,feat3=0.2`rrrCrrrrcr0r.GetFeatureThresholdsr s6    d 3  % % A  r0cr[R"SS[R"SS9[RSS9$)Nz --feature-attribution-thresholdsrTra List of feature-attribution score threshold value pairs(Apply for all the deployed models under the endpoint, if you want to specify different thresholds for different deployed model, please use flag --monitoring-config-from-file or call API directly). If only feature name is set, the default threshold value would be 0.3. For example: `feature-attribution-thresholds=feat1=0.1,feat2,feat3=0.2`rrrcr0r.GetFeatureAttributionThresholdsr0s6 (   d 3  % % K  r0cURUS9nURSS9n[5RU5 [ 5RU5 [ 5RU5 g)zQAdd model monitoring objective config related flags to the parser for Update API.rHFmutexN)rrrr)rr)r-r objective_config_groupthresholds_groups r. AddObjectiveConfigGroupForUpdaterAsg!>>?,55E5B$$%56!#//0@A++,BCr0cURUS9nURSS9n[5RU5 [ 5RU5 UR S[ SSS9 UR SS S 9 URS S9nUR S S S 9 UR SSS 9 URSS9nUR SSS 9 UR SS[R"5SS9 [5RU5 g)zRAdd model monitoring objective config related flags to the parser for Create API..rHFrz--training-sampling-rate?zTraining Dataset sampling rate.rz--target-fieldzu Target field name the model is to predict. Must be provided if you'd like to do training-prediction skew detection. r"Tz --datasetz1Id of Vertex AI Dataset used to train this Model.z--bigquery-urizw BigQuery table of the unmanaged Dataset used to train this Model. For example: `bq://projectId.bqDatasetId.bqTableId`.z --data-formatz Data format of the dataset, must be provided if the input is from Google Cloud Storage. The possible formats are: tf-record, csvz --gcs-urisGCS_URISz^ Comma-separated Google Cloud Storage uris of the unmanaged Datasets used to train this Model.rN) rrrr)rrrrrtr)r-r rrtraining_data_groupgcs_data_source_groups r. AddObjectiveConfigGroupForCreaterLsO!>>?,55E5B$$%56!#//0@A  ,     )222>""K#"" 8# .77e7D$$ ,% $$     a %++,BCr0c [R"[RU[R[ [ R"[R5S9SS9$r5) r rr MODEL_MONITORING_JOBS_COLLECTIONrrr r7'SUPPORTED_MODEL_MONITORING_JOBS_REGIONSr9s r.GetMonitoringJobResourceSpecr|sN   00!::'!88??  $  r0c[RRS[5SR U5SS9R U5 g)aAdd a resource argument for a Vertex AI model deployment monitoring job. NOTE: Must be used only if it's the only resource arg in the command. Args: parser: the parser for the command. verb: str, the verb to describe the resource, such as 'to update'. monitoring_jobz'The model deployment monitoring job {}.TrHN)rrr rrYr)r2s r. AddModelMonitoringJobResourceArgrsC++"$/66t< , Kr0cL[R"S[RSUS9$)Nz--anomaly-cloud-loggingz/If true, anomaly will be sent to Cloud Logging.)rrr )rrCrStoreTrueFalseActionrHs r.GetAnomalyCloudLoggingArgrs%   - - @  r0r')NN)T)TzID of the index.)TzID of the index endpoint.)F)r0)r_)r)r)r)r)Tr)F)FF)r)__doc__ __future__rrrrtextwrapgooglecloudsdk.api_lib.utilrgooglecloudsdk.callioperr googlecloudsdk.calliope.conceptsr r googlecloudsdk.command_lib.air r r googlecloudsdk.command_lib.iamr core_iam_utilgooglecloudsdk.command_lib.kmsrr$googlecloudsdk.command_lib.util.apisr(googlecloudsdk.command_lib.util.conceptsrrgooglecloudsdk.corerrrCrrr(r+r*dedentNETWORKPUBLIC_ENDPOINT_ENABLEDGetIamAccountFormatValidatorTRAINING_SERVICE_ACCOUNTENABLE_WEB_ACCESSENABLE_DASHBOARD_ACCESSr/r?rErIrNrPrRr[r^rardrfrkrmrorurzr}rrrrrrrrrrrrrrrrrrrrrrrPromptForRegionrrr rrrrr#r(r*r,r.r3r1r>r;rCr<rI.PromptForDeploymentResourcePoolSupportedRegionrMrQrUrWr[r]rar`rergrkrmrorurxr{r~rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrcr0r.rsL&&' ,/(51305DM:DG*)   3;;$ ?       ; ]]   B   --    --    ==  3 3 5    MM      --      , 2$$ G ;P    .,$ ,( 0BOd@<  "8&  $ GA '2&A&A  {'B'B 4?3N3N43>2M2M.*990-8,G,G@FGT+6*E*E0f  D$ ,-JJ  JJ0: +*E*E *99,"  ,  + """" B2"B     "%P  "D-D` "r0