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https://github.com/imjasonh/gcloud-help
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262 lines
12 KiB
Text
262 lines
12 KiB
Text
NAME
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gcloud alpha ai models upload - upload a new model
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SYNOPSIS
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gcloud alpha ai models upload --container-image-uri=CONTAINER_IMAGE_URI
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--display-name=DISPLAY_NAME [--artifact-uri=ARTIFACT_URI]
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[--container-args=[ARG,...]] [--container-command=[COMMAND,...]]
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[--container-deployment-timeout-seconds=CONTAINER_DEPLOYMENT_TIMEOUT_SECONDS]
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[--container-env-vars=[KEY=VALUE,...]]
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[--container-grpc-ports=[PORT,...]]
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[--container-health-probe-exec=[HEALTH_PROBE_EXEC,...]]
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[--container-health-probe-period-seconds=CONTAINER_HEALTH_PROBE_PERIOD_SECONDS]
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[--container-health-probe-timeout-seconds=CONTAINER_HEALTH_PROBE_TIMEOUT_SECONDS]
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[--container-health-route=CONTAINER_HEALTH_ROUTE]
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[--container-ports=[PORT,...]]
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[--container-predict-route=CONTAINER_PREDICT_ROUTE]
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[--container-shared-memory-size-mb=CONTAINER_SHARED_MEMORY_SIZE_MB]
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[--container-startup-probe-exec=[STARTUP_PROBE_EXEC,...]]
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[--container-startup-probe-period-seconds=CONTAINER_STARTUP_PROBE_PERIOD_SECONDS]
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[--container-startup-probe-timeout-seconds=CONTAINER_STARTUP_PROBE_TIMEOUT_SECONDS]
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[--description=DESCRIPTION]
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[--explanation-metadata-file=EXPLANATION_METADATA_FILE]
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[--explanation-method=EXPLANATION_METHOD]
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[--explanation-modality=EXPLANATION_MODALITY;
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default="MODALITY_UNSPECIFIED"]
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[--explanation-nearest-neighbor-search-config-file=EXPLANATION_NEAREST_NEIGHBOR_SEARCH_CONFIG_FILE]
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[--explanation-neighbor-count=EXPLANATION_NEIGHBOR_COUNT]
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[--explanation-path-count=EXPLANATION_PATH_COUNT]
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[--explanation-query=EXPLANATION_QUERY; default="PRECISE"]
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[--explanation-step-count=EXPLANATION_STEP_COUNT]
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[--labels=[KEY=VALUE,...]] [--model-id=MODEL_ID]
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[--parent-model=PARENT_MODEL] [--region=REGION]
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[--smooth-grad-noise-sigma=SMOOTH_GRAD_NOISE_SIGMA]
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[--smooth-grad-noise-sigma-by-feature=[KEY=VALUE,...]]
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[--smooth-grad-noisy-sample-count=SMOOTH_GRAD_NOISY_SAMPLE_COUNT]
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[--uris=[URIS,...]] [--version-aliases=[VERSION_ALIASES,...]]
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[--version-description=VERSION_DESCRIPTION] [GCLOUD_WIDE_FLAG ...]
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EXAMPLES
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To upload a model under project example in region us-central1, run:
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$ gcloud alpha ai models upload \
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--container-image-uri="gcr.io/example/my-image" \
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--description=example-model --display-name=my-model \
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--artifact-uri='gs://bucket/path' --project=example \
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--region=us-central1
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REQUIRED FLAGS
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--container-image-uri=CONTAINER_IMAGE_URI
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URI of the Model serving container file in the Container Registry (e.g.
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gcr.io/myproject/server:latest).
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--display-name=DISPLAY_NAME
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Display name of the model.
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OPTIONAL FLAGS
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--artifact-uri=ARTIFACT_URI
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Path to the directory containing the Model artifact and any of its
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supporting files.
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--container-args=[ARG,...]
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Comma-separated arguments passed to the command run by the container
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image. If not specified and no --command is provided, the container
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image's default command is used.
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--container-command=[COMMAND,...]
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Entrypoint for the container image. If not specified, the container
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image's default entrypoint is run.
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--container-deployment-timeout-seconds=CONTAINER_DEPLOYMENT_TIMEOUT_SECONDS
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Deployment timeout in seconds.
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--container-env-vars=[KEY=VALUE,...]
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List of key-value pairs to set as environment variables.
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--container-grpc-ports=[PORT,...]
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Container ports to receive grpc requests at. Must be a number between 1
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and 65535, inclusive.
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--container-health-probe-exec=[HEALTH_PROBE_EXEC,...]
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Exec specifies the action to take. Used by health probe. An example of
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this argument would be ["cat", "/tmp/healthy"].
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--container-health-probe-period-seconds=CONTAINER_HEALTH_PROBE_PERIOD_SECONDS
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How often (in seconds) to perform the health probe. Default to 10
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seconds. Minimum value is 1.
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--container-health-probe-timeout-seconds=CONTAINER_HEALTH_PROBE_TIMEOUT_SECONDS
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Number of seconds after which the health probe times out. Defaults to 1
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second. Minimum value is 1.
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--container-health-route=CONTAINER_HEALTH_ROUTE
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HTTP path to send health checks to inside the container.
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--container-ports=[PORT,...]
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Container ports to receive http requests at. Must be a number between 1
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and 65535, inclusive.
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--container-predict-route=CONTAINER_PREDICT_ROUTE
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HTTP path to send prediction requests to inside the container.
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--container-shared-memory-size-mb=CONTAINER_SHARED_MEMORY_SIZE_MB
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The amount of the VM memory to reserve as the shared memory for the
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model in megabytes.
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--container-startup-probe-exec=[STARTUP_PROBE_EXEC,...]
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Exec specifies the action to take. Used by startup probe. An example of
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this argument would be ["cat", "/tmp/healthy"].
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--container-startup-probe-period-seconds=CONTAINER_STARTUP_PROBE_PERIOD_SECONDS
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How often (in seconds) to perform the startup probe. Default to 10
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seconds. Minimum value is 1.
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--container-startup-probe-timeout-seconds=CONTAINER_STARTUP_PROBE_TIMEOUT_SECONDS
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Number of seconds after which the startup probe times out. Defaults to
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1 second. Minimum value is 1.
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--description=DESCRIPTION
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Description of the model.
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--explanation-metadata-file=EXPLANATION_METADATA_FILE
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Path to a local JSON file that contains the metadata describing the
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Model's input and output for explanation.
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--explanation-method=EXPLANATION_METHOD
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Method used for explanation. Accepted values are integrated-gradients,
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xrai and sampled-shapley.
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--explanation-modality=EXPLANATION_MODALITY; default="MODALITY_UNSPECIFIED"
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Preset option specifying the modality of the uploaded model, which
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automatically configures the distance measurement and feature
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normalization for the underlying example index and queries. Accepted
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values are IMAGE, TEXT and TABULAR. Should be used only when the
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explanation method is examples.
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--explanation-nearest-neighbor-search-config-file=EXPLANATION_NEAREST_NEIGHBOR_SEARCH_CONFIG_FILE
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Path to a local JSON file that contains the configuration for the
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generated index, the semantics are the same as metadata and should
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match NearestNeighborSearchConfig. If you specify this parameter, no
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need to use explanation-modality and explanation-query for preset.
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Should be used only when the explanation method is examples.
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An example of a JSON config file:
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{
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"contentsDeltaUri": "",
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"config": {
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"dimensions": 50,
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"approximateNeighborsCount": 10,
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"distanceMeasureType": "SQUARED_L2_DISTANCE",
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"featureNormType": "NONE",
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"algorithmConfig": {
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"treeAhConfig": {
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"leafNodeEmbeddingCount": 1000,
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"leafNodesToSearchPercent": 100
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}
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}
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}
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}
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--explanation-neighbor-count=EXPLANATION_NEIGHBOR_COUNT
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The number of items to return when querying for examples. Should be
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used only when the explanation method is examples.
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--explanation-path-count=EXPLANATION_PATH_COUNT
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Number of feature permutations to consider when approximating the
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Shapley values for explanation.
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--explanation-query=EXPLANATION_QUERY; default="PRECISE"
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Preset option controlling parameters for query speed-precision
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trade-off. Accepted values are PRECISE and FAST. Should be used only
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when the explanation method is examples.
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--explanation-step-count=EXPLANATION_STEP_COUNT
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Number of steps to approximate the path integral for explanation.
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--labels=[KEY=VALUE,...]
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Labels with user-defined metadata to organize your Models.
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Label keys and values can be no longer than 64 characters (Unicode
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codepoints), can only contain lowercase letters, numeric characters,
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underscores and dashes. International characters are allowed.
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See https://goo.gl/xmQnxf for more information and examples of labels.
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--model-id=MODEL_ID
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ID to use for the uploaded Model, which will become the final component
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of the model resource name.
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--parent-model=PARENT_MODEL
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Resource name of the model into which to upload the version. Only
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specify this field when uploading a new version.
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Value should be provided in format:
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projects/PROJECT_ID/locations/REGION/models/PARENT_MODEL_ID
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Region resource - Cloud region to upload model. This represents a Cloud
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resource. (NOTE) Some attributes are not given arguments in this group but
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can be set in other ways.
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To set the project attribute:
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◆ provide the argument --region on the command line with a fully
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specified name;
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◆ set the property ai/region with a fully specified name;
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◆ choose one from the prompted list of available regions with a fully
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specified name;
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◆ provide the argument --project on the command line;
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◆ set the property core/project.
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--region=REGION
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ID of the region or fully qualified identifier for the region.
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To set the region attribute:
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▸ provide the argument --region on the command line;
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▸ set the property ai/region;
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▸ choose one from the prompted list of available regions.
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--smooth-grad-noise-sigma=SMOOTH_GRAD_NOISE_SIGMA
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Single float value used to add noise to all the features for
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explanation. Only applicable to explanation method integrated-gradients
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or xrai.
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--smooth-grad-noise-sigma-by-feature=[KEY=VALUE,...]
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Noise sigma by features for explanation. Noise sigma represents the
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standard deviation of the gaussian kernel that will be used to add
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noise to interpolated inputs prior to computing gradients. Only
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applicable to explanation method integrated-gradients or xrai.
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--smooth-grad-noisy-sample-count=SMOOTH_GRAD_NOISY_SAMPLE_COUNT
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Number of gradient samples used for approximation at explanation. Only
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applicable to explanation method integrated-gradients or xrai.
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--uris=[URIS,...]
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Cloud Storage bucket paths where training data is stored. Should be
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used only when the explanation method is examples.
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--version-aliases=[VERSION_ALIASES,...]
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Aliases used to reference a model version instead of auto-generated
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version ID. The aliases mentioned in the flag will replace the aliases
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set in the model.
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--version-description=VERSION_DESCRIPTION
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Description of the model version.
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GCLOUD WIDE FLAGS
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These flags are available to all commands: --access-token-file, --account,
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--billing-project, --configuration, --flags-file, --flatten, --format,
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--help, --impersonate-service-account, --log-http, --project, --quiet,
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--trace-token, --user-output-enabled, --verbosity.
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Run $ gcloud help for details.
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NOTES
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This command is currently in alpha and might change without notice. If this
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command fails with API permission errors despite specifying the correct
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project, you might be trying to access an API with an invitation-only early
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access allowlist. These variants are also available:
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$ gcloud ai models upload
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$ gcloud beta ai models upload
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