NAME
    gcloud beta ai models upload - upload a new model

SYNOPSIS
    gcloud beta ai models upload --container-image-uri=CONTAINER_IMAGE_URI
        --display-name=DISPLAY_NAME [--artifact-uri=ARTIFACT_URI]
        [--container-args=[ARG,...]] [--container-command=[COMMAND,...]]
        [--container-deployment-timeout-seconds=CONTAINER_DEPLOYMENT_TIMEOUT_SECONDS]
        [--container-env-vars=[KEY=VALUE,...]]
        [--container-grpc-ports=[PORT,...]]
        [--container-health-probe-exec=[HEALTH_PROBE_EXEC,...]]
        [--container-health-probe-period-seconds=CONTAINER_HEALTH_PROBE_PERIOD_SECONDS]
        [--container-health-probe-timeout-seconds=CONTAINER_HEALTH_PROBE_TIMEOUT_SECONDS]
        [--container-health-route=CONTAINER_HEALTH_ROUTE]
        [--container-ports=[PORT,...]]
        [--container-predict-route=CONTAINER_PREDICT_ROUTE]
        [--container-shared-memory-size-mb=CONTAINER_SHARED_MEMORY_SIZE_MB]
        [--container-startup-probe-exec=[STARTUP_PROBE_EXEC,...]]
        [--container-startup-probe-period-seconds=CONTAINER_STARTUP_PROBE_PERIOD_SECONDS]
        [--container-startup-probe-timeout-seconds=CONTAINER_STARTUP_PROBE_TIMEOUT_SECONDS]
        [--description=DESCRIPTION]
        [--explanation-metadata-file=EXPLANATION_METADATA_FILE]
        [--explanation-method=EXPLANATION_METHOD]
        [--explanation-modality=EXPLANATION_MODALITY;
          default="MODALITY_UNSPECIFIED"]
        [--explanation-nearest-neighbor-search-config-file=EXPLANATION_NEAREST_NEIGHBOR_SEARCH_CONFIG_FILE]
        [--explanation-neighbor-count=EXPLANATION_NEIGHBOR_COUNT]
        [--explanation-path-count=EXPLANATION_PATH_COUNT]
        [--explanation-query=EXPLANATION_QUERY; default="PRECISE"]
        [--explanation-step-count=EXPLANATION_STEP_COUNT]
        [--labels=[KEY=VALUE,...]] [--model-id=MODEL_ID]
        [--parent-model=PARENT_MODEL] [--region=REGION]
        [--smooth-grad-noise-sigma=SMOOTH_GRAD_NOISE_SIGMA]
        [--smooth-grad-noise-sigma-by-feature=[KEY=VALUE,...]]
        [--smooth-grad-noisy-sample-count=SMOOTH_GRAD_NOISY_SAMPLE_COUNT]
        [--uris=[URIS,...]] [--version-aliases=[VERSION_ALIASES,...]]
        [--version-description=VERSION_DESCRIPTION] [GCLOUD_WIDE_FLAG ...]

EXAMPLES
    To upload a model under project example in region us-central1, run:

        $ gcloud beta ai models upload \
            --container-image-uri="gcr.io/example/my-image" \
            --description=example-model --display-name=my-model \
            --artifact-uri='gs://bucket/path' --project=example \
            --region=us-central1

REQUIRED FLAGS
     --container-image-uri=CONTAINER_IMAGE_URI
        URI of the Model serving container file in the Container Registry (e.g.
        gcr.io/myproject/server:latest).

     --display-name=DISPLAY_NAME
        Display name of the model.

OPTIONAL FLAGS
     --artifact-uri=ARTIFACT_URI
        Path to the directory containing the Model artifact and any of its
        supporting files.

     --container-args=[ARG,...]
        Comma-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.

     --container-command=[COMMAND,...]
        Entrypoint for the container image. If not specified, the container
        image's default entrypoint is run.

     --container-deployment-timeout-seconds=CONTAINER_DEPLOYMENT_TIMEOUT_SECONDS
        Deployment timeout in seconds.

     --container-env-vars=[KEY=VALUE,...]
        List of key-value pairs to set as environment variables.

     --container-grpc-ports=[PORT,...]
        Container ports to receive grpc requests at. Must be a number between 1
        and 65535, inclusive.

     --container-health-probe-exec=[HEALTH_PROBE_EXEC,...]
        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=CONTAINER_HEALTH_PROBE_PERIOD_SECONDS
        How often (in seconds) to perform the health probe. Default to 10
        seconds. Minimum value is 1.

     --container-health-probe-timeout-seconds=CONTAINER_HEALTH_PROBE_TIMEOUT_SECONDS
        Number of seconds after which the health probe times out. Defaults to 1
        second. Minimum value is 1.

     --container-health-route=CONTAINER_HEALTH_ROUTE
        HTTP path to send health checks to inside the container.

     --container-ports=[PORT,...]
        Container ports to receive http requests at. Must be a number between 1
        and 65535, inclusive.

     --container-predict-route=CONTAINER_PREDICT_ROUTE
        HTTP path to send prediction requests to inside the container.

     --container-shared-memory-size-mb=CONTAINER_SHARED_MEMORY_SIZE_MB
        The amount of the VM memory to reserve as the shared memory for the
        model in megabytes.

     --container-startup-probe-exec=[STARTUP_PROBE_EXEC,...]
        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=CONTAINER_STARTUP_PROBE_PERIOD_SECONDS
        How often (in seconds) to perform the startup probe. Default to 10
        seconds. Minimum value is 1.

     --container-startup-probe-timeout-seconds=CONTAINER_STARTUP_PROBE_TIMEOUT_SECONDS
        Number of seconds after which the startup probe times out. Defaults to
        1 second. Minimum value is 1.

     --description=DESCRIPTION
        Description of the model.

     --explanation-metadata-file=EXPLANATION_METADATA_FILE
        Path to a local JSON file that contains the metadata describing the
        Model's input and output for explanation.

     --explanation-method=EXPLANATION_METHOD
        Method used for explanation. Accepted values are integrated-gradients,
        xrai and sampled-shapley.

     --explanation-modality=EXPLANATION_MODALITY; default="MODALITY_UNSPECIFIED"
        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.

     --explanation-nearest-neighbor-search-config-file=EXPLANATION_NEAREST_NEIGHBOR_SEARCH_CONFIG_FILE
        Path 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
                    }
                }
              }
            }

     --explanation-neighbor-count=EXPLANATION_NEIGHBOR_COUNT
        The number of items to return when querying for examples. Should be
        used only when the explanation method is examples.

     --explanation-path-count=EXPLANATION_PATH_COUNT
        Number of feature permutations to consider when approximating the
        Shapley values for explanation.

     --explanation-query=EXPLANATION_QUERY; default="PRECISE"
        Preset 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.

     --explanation-step-count=EXPLANATION_STEP_COUNT
        Number of steps to approximate the path integral for explanation.

     --labels=[KEY=VALUE,...]
        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.

     --model-id=MODEL_ID
        ID to use for the uploaded Model, which will become the final component
        of the model resource name.

     --parent-model=PARENT_MODEL
        Resource 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

     Region resource - Cloud region to upload model. This represents a Cloud
     resource. (NOTE) Some attributes are not given arguments in this group but
     can be set in other ways.

     To set the project attribute:
      ◆ provide the argument --region on the command line with a fully
        specified name;
      ◆ set the property ai/region with a fully specified name;
      ◆ choose one from the prompted list of available regions with a fully
        specified name;
      ◆ provide the argument --project on the command line;
      ◆ set the property core/project.

     --region=REGION
        ID of the region or fully qualified identifier for the region.

        To set the region attribute:
        ◆ provide the argument --region on the command line;
        ◆ set the property ai/region;
        ◆ choose one from the prompted list of available regions.

     --smooth-grad-noise-sigma=SMOOTH_GRAD_NOISE_SIGMA
        Single float value used to add noise to all the features for
        explanation. Only applicable to explanation method integrated-gradients
        or xrai.

     --smooth-grad-noise-sigma-by-feature=[KEY=VALUE,...]
        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.

     --smooth-grad-noisy-sample-count=SMOOTH_GRAD_NOISY_SAMPLE_COUNT
        Number of gradient samples used for approximation at explanation. Only
        applicable to explanation method integrated-gradients or xrai.

     --uris=[URIS,...]
        Cloud Storage bucket paths where training data is stored. Should be
        used only when the explanation method is examples.

     --version-aliases=[VERSION_ALIASES,...]
        Aliases 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.

     --version-description=VERSION_DESCRIPTION
        Description of the model version.

GCLOUD WIDE FLAGS
    These flags are available to all commands: --access-token-file, --account,
    --billing-project, --configuration, --flags-file, --flatten, --format,
    --help, --impersonate-service-account, --log-http, --project, --quiet,
    --trace-token, --user-output-enabled, --verbosity.

    Run $ gcloud help for details.

NOTES
    This command is currently in beta and might change without notice. These
    variants are also available:

        $ gcloud ai models upload

        $ gcloud alpha ai models upload

