dZddlmZddlmZddlmZddlmZddlmZddlm Z ddlm Z dd l m Z dd lmZdd lmZdd lmZdd lmZddlmZddlmZddlmZddlmZddlmZddlmZdZdZ ddZ!dZ"dZ#dZ$Gdde%Z&y)z5Utilities for dealing with AI Platform endpoints API.)absolute_import)division)unicode_literals)encoding) exceptions) extra_types) list_pager)utilclient)apis) constants)errors)flags) properties) resources)requests) http_clientctjj||tjj j jddS)z/Parses a model ID into a model resource object.) locationsId projectsIdz$aiplatform.projects.locations.models)params collection)rREGISTRYParserVALUEScoreproject GetOrFail)model_id location_ids 1lib/googlecloudsdk/api_lib/ai/endpoints/client.py _ParseModelr#&sK    ! !$"))..66@@8 " cT|Dcgc]}tj||c}Scc}wN)rPyValueToMessage) message_typevaluesvs r"_ConvertPyListToMessageListr+2s'>D Ef( # #L! 4f EE Es%Nc tj|j|}tj|}|d}|7d|vr2t j dj|jy |jd|dS#tj$r't j d|jzwxYw#t$r |ddcYSwxYw)aGets the deployment resource type of a model. Args: model_ref: a model resource object. client: an apis.GetClientInstance object. shared_resources_ref: str, the shared deployment resource pool the model should use, formatted as the full URI Returns: A string which value must be 'DEDICATED_RESOURCES', 'AUTOMATIC_RESOURCES' or 'SHARED_RESOURCES' Raises: ArgumentError: if the model resource object is not found. r z\There is an error while getting the model information. Please make sure the model %r exists.!supportedDeploymentResourcesTypesSHARED_RESOURCESz,Shared resources not supported for model {}.r) model_client ModelsClientGetapitools_exceptions HttpErrorr ArgumentError RelativeNamerMessageToPyValueformatremove ValueError) model_refr shared_resources_ref model_msgmodel_resource$supported_deployment_resources_typess r"_GetModelDeploymentResourceTyper?6s $))8<q AABs%B;C:C C"!C"ctjjd|||}|j|j|j fS)Makes an http POST request.POST)dataheaders)r GetSessionrequest status_coderDcontent)urlrDbodyresponses r" _DoHttpPostrLhsJ  " * * cg+(   x//1A1A AAr$c#Ktjjd|||d5}|jD]}| dddy#1swYyxYww)rArBT)rCrDstreamN)rrErF iter_lines)rIrDrJresplines r"_DoStreamHttpPostrRpsU$$ cgd% ! j"s)AA AAAc|j|}tj|}|duxrd|vxrd|dvxr|ddS)z2GDC GGS model is only supported for GDC endpoints.N gdcConfigzone)r1rr6)self endpoint_refendpointendpoint_resources r"_CheckIsGdcGgsModelrZysc XXl #(//9t#1 * *1 %k2 21 K ( 0 r$c(eZdZdZddZ ddZ ddZdZdZddZ dd Z dd Z d Z d Z d ZdZdZdZdZdZdZdZ ddZ ddZd dZ d dZy)!EndpointsClientz8High-level client for the AI Platform endpoints surface.Nc|xs5tjtjtj||_|xs|j j |_yr&)r GetClientInstancerAI_PLATFORM_API_NAMEAI_PLATFORM_API_VERSIONr MESSAGES_MODULEmessages)rVr rbversions r"__init__zEndpointsClient.__init__sJD22&&))'2DK; ; ;DMr$c d} |r|jj|} tjdtj ||||| } |_tjdtj d| r| ndtjdtj |  | _|jj|j|| } |jjj| S) apCreates a new endpoint using v1 API. Args: location_ref: Resource, the parsed location to create an endpoint. display_name: str, the display name of the new endpoint. labels: list, the labels to organize the new endpoint. description: str or None, the description of the new endpoint. network: str, the full name of the Google Compute Engine network. endpoint_id: str or None, the id of the new endpoint. encryption_kms_key_name: str or None, the Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. request_response_logging_table: str or None, the BigQuery table uri for request-response logging. request_response_logging_rate: float or None, the sampling rate for request-response logging. Returns: A long-running operation for Create. N kmsKeyNameEndpoint) displayName descriptionlabelsnetworkencryptionSpec#PredictRequestResponseLoggingConfigTBigQueryDestination outputUrienabled samplingRatebigqueryDestination)parent endpointIdgoogleCloudAiplatformV1Endpoint) rb%GoogleCloudAiplatformV1EncryptionSpecapi_util GetMessager GA_VERSION#predictRequestResponseLoggingConfig1AiplatformProjectsLocationsEndpointsCreateRequestr5r projects_locations_endpointsCreate) rV location_ref display_namerkrjrl endpoint_idencryption_kms_key_namerequest_response_logging_tablerequest_response_logging_rateencryption_specrXreqs r"rzEndpointsClient.Creates >O KK,LoEx"":y/C/CD & H&16X5H5H /1E1E6 *5 h11#Y%9%9 46 6h2 -- I I((*(0 J C ;; 3 3 : :3 ??r$c d} |r|jj|} d} |r|jj|} d}| r|jj| }t j dt j||||| | |}| _t j dt jd| r| ndt j d t j|  |_|jj|j|| }|jjj|S) aCreates a new endpoint using v1beta1 API. Args: location_ref: Resource, the parsed location to create an endpoint. display_name: str, the display name of the new endpoint. labels: list, the labels to organize the new endpoint. description: str or None, the description of the new endpoint. network: str, the full name of the Google Compute Engine network. endpoint_id: str or None, the id of the new endpoint. encryption_kms_key_name: str or None, the Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. gdce_zone: str or None, the name of the GDCE zone. gdc_zone: str or None, the name of the GDC zone. request_response_logging_table: str or None, the BigQuery table uri for request-response logging. request_response_logging_rate: float or None, the sampling rate for request-response logging. Returns: A long-running operation for Create. Nrf)rUrh)rirjrkrlrm gdceConfigrTrnTrorprqrs)rwrx$googleCloudAiplatformV1beta1Endpoint)rb*GoogleCloudAiplatformV1beta1EncryptionSpec&GoogleCloudAiplatformV1beta1GdceConfig%GoogleCloudAiplatformV1beta1GdcConfigr{r|r BETA_VERSIONr~rr5r rr)rVrrrkrjrlrr gdce_zonegdc_zonerrr gdce_config gdc_configrXrs r" CreateBetazEndpointsClient.CreateBetasaFO -- B B0 C  KMMHHIkJ==FFGjGx"":y/E/EF &H&16X5H5H /1G1G6 *5 h11#Y%;%; 46 6h2 -- I I((*-5 J C ;; 3 3 : :3 ??r$c|jj|j}|jjj |S)zDeletes an existing endpoint.name)rb1AiplatformProjectsLocationsEndpointsDeleteRequestr5r rDeleterVrWrs r"rzEndpointsClient.Delete!sE -- I I  & & ( J C ;; 3 3 : :3 ??r$c|jj|j}|jjj |S)zGets details about an endpoint.r)rb.AiplatformProjectsLocationsEndpointsGetRequestr5r rr1rs r"r1zEndpointsClient.Get(sE -- F F  & & ( G C ;; 3 3 7 7 <>r$c |jj} g} |jr"|j| _| j d||| _| j d|{g} t |jD]5\} }| j | jj| |7| j| | _ | j d|rd| _ | j d||| _ | j d|||j|j}|s)tjdt j"}d |_|0tjd t j"| |_|||_|| _ | j d | r<|j|j}|rd |_|| _ | j d | st+j,d|jj/|j1| dj3| }|j4j6j9|S)aUpdates an endpoint using v1beta1 API. Args: endpoint_ref: Resource, the parsed endpoint to be updated. labels_update: UpdateResult, the result of applying the label diff constructed from args. display_name: str or None, the new display name of the endpoint. description: str or None, the new description of the endpoint. traffic_split: dict or None, the new traffic split of the endpoint. clear_traffic_split: bool, whether or not clear traffic split of the endpoint. request_response_logging_table: str or None, the BigQuery table uri for request-response logging. request_response_logging_rate: float or None, the sampling rate for request-response logging. disable_request_response_logging: bool, whether or not disable request-response logging of the endpoint. Returns: The response message of Patch. Raises: NoFieldsSpecifiedError: An error if no updates requested. rkNrrrrrjrnTrprqrFrr)rrr)rb$GoogleCloudAiplatformV1beta1Endpointrrkrrirrrrrrjr1r~r{r|rrrtrvrurrrr5rr rrrs r" PatchBetazEndpointsClient.PatchBetasH}}AACHK!!%,,ho")h(  }2245*#u$$  & & ( ; ;u <  6 '8849h)"h)(h' '2 ( 4(, )++&-+ (*=*= 193I3I+ + '15%- ' 3 NH   5y7M7M N8  (; ' 2 ) (4 *2BC'(, )++& )27'/ )2BC   ) )*A BB -- H H  & & (-588K( I C ;; 3 3 9 9# >>r$cp|jjttj|d}d|vr,t j tj|d|_|jj|j|}|jjj|S)z+#> JO ~%#+#<#<    !=$o  -- J J**,.= K C ;; 3 3 ; ;C @@r$cp|jjttj|d}d|vr,t j tj|d|_|jj|j|}|jjj|S)zASends online prediction request to an endpoint using v1beta1 API.rrr)rX*googleCloudAiplatformV1beta1PredictRequest) rb*GoogleCloudAiplatformV1beta1PredictRequestr+rrrr'rrr5r rrrs r" PredictBetazEndpointsClient.PredictBeta7smmNN-  ! !>+#> OO ~%#+#<#<    !=$o  -- J J**,3B K C ;; 3 3 ; ;C @@r$c0dj|jjt|jd|j }t |||\}}}|t jk7r&tjd|jz||fS)3Sends online raw prediction request to an endpoint.z{}{}/{}:rawPredict_VERSIONzHTTP request failed. Response: ) r7r rIgetattrr5rLrOKcore_exceptionsErrordecode)rVrWrDrFrIstatusresponse_headersrKs r" RawPredictzEndpointsClient.RawPredictIs  % %  Z(!!# C *5S'7)K&F h   ! ! ,x/@ @  X %%r$c#Kdj|jjt|jd|j }t |||D]}|yw)rz{}{}/{}:streamRawPredictrN)r7r rIrr5rR)rVrWrDrFrIrPs r"StreamRawPredictz EndpointsClient.StreamRawPredictYsU $ + +  Z(!!# C "#w8 j9sA!A#c|jjt|jj|d}d|vr2t j |jj|d|_|jj|j|}|jjj|S)zCSends online direct prediction request to an endpoint using v1 API.inputsrr)rX+googleCloudAiplatformV1DirectPredictRequest) rb+GoogleCloudAiplatformV1DirectPredictRequestr+GoogleCloudAiplatformV1Tensorrr'r8AiplatformProjectsLocationsEndpointsDirectPredictRequestr5r r DirectPredictrVrW inputs_jsondirect_predict_requestrs r"rzEndpointsClient.DirectPredictds AA. ;;H% B {"*2*C*C -- 5 5{<7P+' NN!..08N O  ;; 3 3 A A# FFr$c|jjt|jj|d}d|vr2t j |jj|d|_|jj|j|}|jjj|S)zHSends online direct prediction request to an endpoint using v1beta1 API.rrr)rX0googleCloudAiplatformV1beta1DirectPredictRequest) rb0GoogleCloudAiplatformV1beta1DirectPredictRequestr+"GoogleCloudAiplatformV1beta1Tensorrr'rrr5r rrrs r"DirectPredictBetaz!EndpointsClient.DirectPredictBeta{s FF. @@H% G {"*2*C*C -- : : l #+' -- P P**,9O Q C ;; 3 3 A A# FFr$c 4|jjt|dd|jd|jd}|jj |j |}|j jj|S)zGSends online direct raw prediction request to an endpoint using v1 API.inpututf-8 methodName method_namerr)rX.googleCloudAiplatformV1DirectRawPredictRequest) rb.GoogleCloudAiplatformV1DirectRawPredictRequestbytesget;AiplatformProjectsLocationsEndpointsDirectRawPredictRequestr5r rDirectRawPredictrVrW input_jsondirect_raw_predict_requestrs r"rz EndpointsClient.DirectRawPredicts!%!]!]Jw'1>>, }0MN"^" -- S S**,7Q T C ;; 3 3 D DS IIr$c 4|jjt|dd|jd|jd}|jj |j |}|j jj|S)zLSends online direct raw prediction request to an endpoint using v1beta1 API.rrrrr)rX3googleCloudAiplatformV1beta1DirectRawPredictRequest) rb3GoogleCloudAiplatformV1beta1DirectRawPredictRequestrrrr5r rrrs r"DirectRawPredictBetaz$EndpointsClient.DirectRawPredictBetas!%!b!bJw'1>>, }0MN"c" -- S S**,+#> JO ~%#+#<#<    !=$o  )(,(>(>o% -- J J**,.= K C ;; 3 3 ; ;C @@r$c|jjttj|d}d|vr,t j tj|d|_d|vr2t j |jj|d|_ |j|j|_ |jj|j|}|jjj!|S)r rrrexplanation_spec_override)rX*googleCloudAiplatformV1beta1ExplainRequest)rb*GoogleCloudAiplatformV1beta1ExplainRequestr+rrrr'r3GoogleCloudAiplatformV1beta1ExplanationSpecOverrideexplanationSpecOverrider rrr5r rrrs r" ExplainBetazEndpointsClient.ExplainBetasmmNN-  ! !>+#> OO ~%#+#<#<    !=$o #n4080I0I -- K K 4 51o- )(,(>(>o% -- J J**,3B K C ;; 3 3 ; ;C @@r$ct||}t||j}|dk(rx|jj }|||_|||_|||_tj|tj}|"|j|_ |j|_ | )tj| tj|_|jj!||}| xsd|_| | |_| | |_| gg}t)| j+D]B\}}|j-|jj/tj0||D||_|jj5|||j7}nX|jj9}| | |_| | |_|jj5|||j7}||_||_|||_|||_ |jjC|}|jg}t)|j+D]5\} }!|j-|jEjG| |!7|jE| |_$|jjK|j7| }"|jjLjO|"S) aDeploys a model to an existing endpoint using v1 API. Args: endpoint_ref: Resource, the parsed endpoint that the model is deployed to. model: str, Id of the uploaded model to be deployed. region: str, the location of the endpoint and the model. display_name: str, the display name of the new deployed model. machine_type: str or None, the type of the machine to serve the model. tpu_topology: str or None, the topology of the TPU to serve the model. multihost_gpu_node_count: int or None, the number of nodes per replica for multihost GPU deployments. accelerator_dict: dict or None, the accelerator attached to the deployed model from args. min_replica_count: int or None, the minimum number of replicas the deployed model will be always deployed on. max_replica_count: int or None, the maximum number of replicas the deployed model may be deployed on. required_replica_count: int or None, the required number of replicas the deployed model will be considered successfully deployed. reservation_affinity: dict or None, the reservation affinity of the deployed model which specifies which reservations the deployed model can use. autoscaling_metric_specs: dict or None, the metric specification that defines the target resource utilization for calculating the desired replica count. spot: bool, whether or not deploy the model on spot resources. enable_access_logging: bool, whether or not enable access logs. disable_container_logging: bool, whether or not disable container logging. service_account: str or None, the service account that the deployed model runs as. traffic_split: dict or None, the new traffic split of the endpoint. deployed_model_id: str or None, id of the deployed model. Returns: A long-running operation for DeployModel. DEDICATED_RESOURCES machineSpecspot metricNametargetdedicatedResourcesrimodelautomaticResourcesrir& deployedModelrr)rX)googleCloudAiplatformV1DeployModelRequest)(r#r?r rb"GoogleCloudAiplatformV1MachineSpec machineType tpuTopologymultihostGpuNodeCountrParseAcceleratorFlagrr}acceleratorTypeacceleratorCountParseReservationAffinityFlagreservationAffinity)GoogleCloudAiplatformV1DedicatedResourcesminReplicaCountmaxReplicaCountrequiredReplicaCountrrr,GoogleCloudAiplatformV1AutoscalingMetricSpec!OP_AUTOSCALING_METRIC_NAME_MAPPERautoscalingMetricSpecs$GoogleCloudAiplatformV1DeployedModelr5)GoogleCloudAiplatformV1AutomaticResourcesenableAccessLoggingdisableContainerLoggingserviceAccountid)GoogleCloudAiplatformV1DeployModelRequestrrr6AiplatformProjectsLocationsEndpointsDeployModelRequestr DeployModel)#rVrWr&regionr machine_type tpu_topologymultihost_gpu_node_countaccelerator_dictmin_replica_countmax_replica_countrequired_replica_countreservation_affinityautoscaling_metric_specsrenable_access_loggingdisable_container_loggingservice_accountrr r: resource_type machine_spec accelerator dedicatedautoscaling_metric_specs_listrr#deployed_model automaticdeployed_model_reqrrrrs# r"rDzEndpointsClient.DeployModelstE6*I3It{{KM--]]EEGl  !#/   !#/  ! --E *.. I00k  '2'B'B $(3(D(D %  )+0+M+M )"6"6, (--II"Ji #4"8qi  &$5 !  +)? & ! -(*%"#;#A#A#CDLD& ' . .mmHH&HHNI E,I (}}II&"&&(Jn--IIKi  &$5 !  &$5 !}}II&"&&(Jn *?N&-FN*"&5n#$+n ??( @    }2245*#u$$  0 0 2 E Eu F  6 );(L(L4)M)% -- N N**,2D O C ;; 3 3 ? ? DDr$ct||}|r|jjd|jjjjd}|jj |dd}|jj |||}nt||}t||j|}|dk(r|jj}|||_ |||_ |||_ tj|tj }|"|j"|_|j$|_| )tj&| tj |_|||_|jj ||}| dn| |_| |j,dk(rd|_n | | |_| | |_||j,dk(rd|_n |||_| gg} t5| j7D]B\}!}"| j9|jj;tj<|!|" D| |_|jjA}#d }$|d jC||#_"d }$|d jC||#_#d }$|$r|#|_$|jj |||jK }n|dk(rY|jjM}%| | |%_| | |%_|jj |%||jK}n:|jj ||jK|jK}||_'||_(|||_)|||_*|jjW|}&|jg}'t5|j7D]5\}(})|'j9|&jYj[|(|)7|&jY|'|&_.|jj_|jK|&}*|jj`jc|*S)a Deploys a model to an existing endpoint using v1beta1 API. Args: endpoint_ref: Resource, the parsed endpoint that the model is deployed to. model: str, Id of the uploaded model to be deployed. region: str, the location of the endpoint and the model. display_name: str, the display name of the new deployed model. machine_type: str or None, the type of the machine to serve the model. tpu_topology: str or None, the topology of the TPU to serve the model. multihost_gpu_node_count: int or None, the number of nodes per replica for multihost GPU deployments. accelerator_dict: dict or None, the accelerator attached to the deployed model from args. min_replica_count: int or None, the minimum number of replicas the deployed model will be always deployed on. max_replica_count: int or None, the maximum number of replicas the deployed model may be deployed on. required_replica_count: int or None, the required number of replicas the deployed model will be considered successfully deployed. reservation_affinity: dict or None, the reservation affinity of the deployed model which specifies which reservations the deployed model can use. autoscaling_metric_specs: dict or None, the metric specification that defines the target resource utilization for calculating the desired replica count. spot: bool, whether or not deploy the model on spot resources. enable_access_logging: bool, whether or not enable access logs. enable_container_logging: bool, whether or not enable container logging. service_account: str or None, the service account that the deployed model runs as. traffic_split: dict or None, the new traffic split of the endpoint. deployed_model_id: str or None, id of the deployed model. shared_resources_ref: str or None, the shared deployment resource pool the model should use min_scaleup_period: str or None, the minimum 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. idle_scaledown_period: str or None, the duration after which the deployment is scaled down if no traffic is received. This only applies to deployments enrolled in scale-to-zero. initial_replica_count: int or None, the initial number of replicas the deployment will be scaled up to. This only applies to deployments enrolled in scale-to-zero. gpu_partition_size: str or None, the partition size of the GPU accelerator. Returns: A long-running operation for DeployModel. z n1-standard-2r )r-r1r2)rr6r7)r%rigdcConnectedModelrrrr!Fz{}sTr$AUTOMATIC_RESOURCESr')rir&sharedResourcesr)rr)rX.googleCloudAiplatformV1beta1DeployModelRequest)2rZrb'GoogleCloudAiplatformV1beta1MachineSpecAcceleratorTypeValueValuesEnumNVIDIA_TESLA_T4.GoogleCloudAiplatformV1beta1DedicatedResources)GoogleCloudAiplatformV1beta1DeployedModelr#r?r r-r.r/rr0rrr1r2r3r4gpuPartitionSizer6r7r8initialReplicaCountrrr1GoogleCloudAiplatformV1beta1AutoscalingMetricSpecr:r;=GoogleCloudAiplatformV1beta1DedicatedResourcesScaleToZeroSpecr7minScaleupPeriodidleScaledownPeriodscaleToZeroSpecr5.GoogleCloudAiplatformV1beta1AutomaticResourcesr>enableContainerLoggingr@rA.GoogleCloudAiplatformV1beta1DeployModelRequestrrrrCrrD)+rVrWr&rErrFrGrHrIrJrKrLrMrNrrOenable_container_loggingrQrr r;min_scaleup_periodidle_scaledown_periodinitial_replica_countgpu_partition_sizeis_gdc_ggs_modelrSrUrWr:rRrTrVrr#stz_specstz_spec_modifiedrXrYrrrrs+ r"DeployModelBetazEndpointsClient.DeployModelBetausX+4>]]JJ%--OOnn~~Kl --NN"AqOi}}NN&"!On eV,i5 T[["6m / /}}LLN  #%1, "  #%1, " # //G, ,00 i44   ")4)D)D, &*5*F*F, '  +-2-O-O"I$:$:. , *  )*<, ' MM H H(t I  #*A0A !  $)B)Ba)G&') #  *(9I % ! -+A) ( ! (Y-F-F!-K*+) ' " .,AI ) # /*, '$%=%C%C%EFldF ) 0 0 OO(JJ " P G.K) * MM W W Y "  )&+ll3E&F( #"  ,).6K)L( &"  &.) # MM C C#,(,,. D   1 1 MM H H J   (&7) #  (&7) # MM C C#,(,,. D   MM C C(,,. 4 A A C D  *?N&,DN)"&5n#$+n DD( E    }2245*#u$$  0 0 2 E Eu F  6 );(L(L4)M)% -- N N**,7I O C ;; 3 3 ? ? DDr$c|jj|}|jg}t|jD]5\}}|j |j j ||7|j ||_|jj|j|}|jjj|S)apUndeploys a model from an endpoint using v1 API. Args: endpoint_ref: Resource, the parsed endpoint that the model is undeployed from. deployed_model_id: str, Id of the deployed model to be undeployed. traffic_split: dict or None, the new traffic split of the endpoint. Returns: A long-running operation for UndeployModel. rrr)rX+googleCloudAiplatformV1UndeployModelRequest) rb+GoogleCloudAiplatformV1UndeployModelRequestrrrrrr8AiplatformProjectsLocationsEndpointsUndeployModelRequestr5r r UndeployModel rVrWr rundeployed_model_reqrrrrs r"r|zEndpointsClient.UndeployModelfs AA- B    }2245*#u$$ 2 2 4 G Gu H  6  0 0#8 1 ' NN!..08L O  ;; 3 3 A A# FFr$c|jj|}|jg}t|jD]5\}}|j |j j ||7|j ||_|jj|j|}|jjj|S)auUndeploys a model from an endpoint using v1beta1 API. Args: endpoint_ref: Resource, the parsed endpoint that the model is undeployed from. deployed_model_id: str, Id of the deployed model to be undeployed. traffic_split: dict or None, the new traffic split of the endpoint. Returns: A long-running operation for UndeployModel. rxrr)rX0googleCloudAiplatformV1beta1UndeployModelRequest) rb0GoogleCloudAiplatformV1beta1UndeployModelRequestrrrrrrr{r5r rr|r}s r"UndeployModelBetaz!EndpointsClient.UndeployModelBetas FF- G    }2245*#u$$ 2 2 4 G Gu H  6  0 0#8 1 ' -- P P**,9M Q C ;; 3 3 A A# FFr$)NNN)NNNNNN)NNNNNNNN)NN)NNNFNNF)NNNNNNNNNFFFNNN)NNNNNNNNNFFFNNNNNNNNr&)__name__ __module__ __qualname____doc__rdrrrr1rrrrrrrrrrrrrrDrvr|rr$r"r\r\s]@<"%)$(=@H"%)$(Q@f@= $%)$(',r?p%)$(',r?hA$A$& G.G, J JA(A>#!# ! %)YEB#!# !$  3oEb&GR<@&Gr$r\r&)'r __future__rrrapitools.base.pyrrr2rr googlecloudsdk.api_lib.air r{ googlecloudsdk.api_lib.ai.modelsr r/googlecloudsdk.api_lib.utilr googlecloudsdk.command_lib.airrrgooglecloudsdk.corerrrgooglecloudsdk.core.credentialsr six.movesrr#r+r?rLrRrZobjectr\rr$r"rsw<&'%>('6C,30/=*)4! F -1/BdB oGfoGr$