fSrSSKJr SSKJr SSKJr SSKJr SSKJr SSK J r "SS \ 5r g ) z%Utilities for AI Platform models API.)absolute_import)division)unicode_literals) list_pager)apis) constantsc\rSrSrSrSSjrSSjrSSjrSrSr S r SS jr SS jr SS jr SS jrSrg) ModelsClientaHigh-level client for the AI Platform models surface. Attributes: client: An instance of the given client, or the API client aiplatform of Beta version. messages: The messages module for the given client, or the API client aiplatform of Beta version. Nc&U=(dD [R"[R[R[R 5UlU=(d UR RUlUR RUl g)N) rGetClientInstancerAI_PLATFORM_API_NAMEAI_PLATFORM_API_VERSION BETA_VERSIONclientMESSAGES_MODULEmessagesprojects_locations_models_service)selfrrs .lib/googlecloudsdk/api_lib/ai/models/client.py__init__ModelsClient.__init__$scCD22&&)))*@*@ACDK; ; ;DMKK99DMc nURRU UU S9nU(aUUlU(aUUlU (a3U Vs/sH nURR UU US9PM" snUlU (a/U Vs/sHnURR US9PM snUlU (a/U Vs/sHnURR US9PM snUlU(a[U5S-Ul U(aUUl U(dU(dU(aBSnU(aURRUS9nURRUUUS9UlU(dU(dU(aBSn U(aURRUS9n URRU UUS9UlURR!UUUUUUUS9n!U(aUU!lU(af/n"[%UR'55H3un#n$U"R)U!R+5R-U#U$S 95 M5 U!R+U"S 9U!lUR0R3URR5UR75URR9U!UUS 9S 95$s snfs snfs snf) a8Constructs, sends an UploadModel request and returns the LRO to be done. Args: region_ref: The resource reference for a given region. None if the region reference is not provided. display_name: The display name of the Model. The name can be up to 128 characters long and can be consist of any UTF-8 characters. description: The description of the Model. version_description: The description of the Model version. artifact_uri: The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models. container_image_uri: Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex- ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex- ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre- built-containers) in this field. container_command: Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker. com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand- how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define- command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom- container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes- api/v1.23/#container-v1-core). container_args: Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data- application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand- how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom- container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes- api/v1.23/#container-v1-core).. container_env_vars: List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ```json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ] ``` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes- api/v1.23/#container-v1-core). container_ports: List of ports to expose from the container. Vertex AI sends any http prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom- container-requirements#liveness) to this port. If you do not specify this field, it defaults to following value: ```json [ { "containerPort": 8080 } ] ``` Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes- api/v1.23/#container-v1-core). container_grpc_ports: List of ports to expose from the container. Vertex AI sends any grpc prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom- container-requirements#liveness) to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes- api/v1.23/#container-v1-core). container_predict_route: HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom- container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex- ai/docs/predictions/custom-container-requirements#aip-variables).) container_health_route: HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex- ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom- container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex- ai/docs/predictions/custom-container-requirements#aip-variables).) container_deployment_timeout_seconds (int): Deployment timeout in seconds. container_shared_memory_size_mb (int): The amount of the VM memory to reserve as the shared memory for the model in megabytes. container_startup_probe_exec (Sequence[str]): Exec specifies the action to take. Used by startup probe. An example of this argument would be ["cat", "/tmp/healthy"] container_startup_probe_period_seconds (int): How often (in seconds) to perform the startup probe. Default to 10 seconds. Minimum value is 1. container_startup_probe_timeout_seconds (int): Number of seconds after which the startup probe times out. Defaults to 1 second. Minimum value is 1. container_health_probe_exec (Sequence[str]): Exec specifies the action to take. Used by health probe. An example of this argument would be ["cat", "/tmp/healthy"] container_health_probe_period_seconds (int): How often (in seconds) to perform the health probe. Default to 10 seconds. Minimum value is 1. container_health_probe_timeout_seconds (int): Number of seconds after which the health probe times out. Defaults to 1 second. Minimum value is 1. explanation_spec: The default explanation specification for this Model. The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated. All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob. If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob. parent_model: The resource name of the model into which to upload the version. Only specify this field when uploading a new version. model_id: The ID to use for the uploaded Model, which 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.. version_aliases: User provided version aliases so that a model version can be referenced via alias (i.e. projects/{project}/locations/{location}/mo dels/{model_id}@{version_alias} instead of auto-generated version id (i.e. projects/{project}/locations/{location}/models/{model_id}@{version_id}). The format is a-z{0,126}[a-z0-9] to distinguish from version_id. A default version alias will be created for the first version of the model, and there must be exactly one default version alias for a model. labels: The labels 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. base_model_source: A GoogleCloudAiplatformV1beta1ModelBaseModelSource object that indicates the source of the model. Currently it only supports specifying the Model Garden models and Generative AI Studio models. Returns: Response from calling upload model with given request arguments.  healthRouteimageUri predictRoutenamevalue containerPortsNcommandexec_ periodSecondstimeoutSeconds) artifactUri containerSpec descriptionversionDescription displayNameexplanationSpecbaseModelSourcekeyr"additionalPropertiesmodel parentModelmodelId)parent.googleCloudAiplatformV1beta1UploadModelRequest)r.GoogleCloudAiplatformV1beta1ModelContainerSpecr'args"GoogleCloudAiplatformV1beta1EnvVarenv GoogleCloudAiplatformV1beta1Portports grpcPortsstrdeploymentTimeoutsharedMemorySizeMb+GoogleCloudAiplatformV1beta1ProbeExecAction!GoogleCloudAiplatformV1beta1Probe startupProbe healthProbe!GoogleCloudAiplatformV1beta1ModelversionAliasessorteditemsappend LabelsValueAdditionalPropertylabelsrUpload.AiplatformProjectsLocationsModelsUploadRequest RelativeName.GoogleCloudAiplatformV1beta1UploadModelRequest)%r region_ref display_namer.version_description artifact_uricontainer_image_uricontainer_commandcontainer_argscontainer_env_varscontainer_portscontainer_grpc_portscontainer_predict_routecontainer_health_route$container_deployment_timeout_secondscontainer_shared_memory_size_mbcontainer_startup_probe_exec&container_startup_probe_period_seconds'container_startup_probe_timeout_secondscontainer_health_probe_exec%container_health_probe_period_seconds&container_health_probe_timeout_secondsexplanation_spec parent_modelmodel_idversion_aliasesrRbase_model_sourcecontainer_speckportstartup_probe_exechealth_probe_execr8additional_propertiesr4r"s% r UploadV1Beta1ModelsClient.UploadV1Beta1+sr DD.(0 E 0n*n=OGoogleCloudAiplatformV1EnvVarr@GoogleCloudAiplatformV1PortrBrCrDrErF&GoogleCloudAiplatformV1ProbeExecActionGoogleCloudAiplatformV1ProberIrJGoogleCloudAiplatformV1ModelrLrMrNrOrPrQrRrrSrTrU)GoogleCloudAiplatformV1UploadModelRequest)$rrWrXr.rYrZr[r\r]r^r_r`rarbrcrdrerfrgrhrirjrkrlrmrnrRrprqrrrsrtr8rur4r"s$ rUploadV1ModelsClient.UploadV1sb]]LL*$,M.N0n*n=O  mmHH%22404 0 0$*0( 1 *I+G ==  g &&r)rrr)NN)NNNNNNNNNNNNNNNNNNNNNNNNNNN)NNNNNNNNNNNNNNNNNNNNNNNNNN)NNNNN)__name__ __module__ __qualname____firstlineno____doc__rrvrrrrrrrr__static_attributes__rrr r s:"!+/&*#'-1.2"&,0-1 9Y$x  #' #'!%""&#$('+&*48/3,06:7;+/596: $ #5M$^ & )0"*.*.##'++/ ''T%)"&&* )'rr N) r __future__rrrapitools.base.pyrgooglecloudsdk.api_lib.utilrgooglecloudsdk.command_lib.airobjectr rrrrs*,&'',3e '6e 'r