gcloud alpha ai models upload

NAME
gcloud alpha ai models upload - upload a new model
SYNOPSIS
gcloud alpha 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 alpha 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 alpha and might change without notice. If this command fails with API permission errors despite specifying the correct project, you might be trying to access an API with an invitation-only early access allowlist. These variants are also available: 
gcloud ai models upload
 
gcloud beta ai models upload