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gcloud-help/gcloud/ai/models/upload

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NAME
gcloud ai models upload - upload a new model
SYNOPSIS
gcloud ai models upload --container-image-uri=CONTAINER_IMAGE_URI
--display-name=DISPLAY_NAME [--artifact-uri=ARTIFACT_URI]
[--container-args=[ARG,...]] [--container-command=[COMMAND,...]]
[--container-env-vars=[KEY=VALUE,...]]
[--container-health-route=CONTAINER_HEALTH_ROUTE]
[--container-ports=[PORT,...]]
[--container-predict-route=CONTAINER_PREDICT_ROUTE]
[--description=DESCRIPTION]
[--explanation-metadata-file=EXPLANATION_METADATA_FILE]
[--explanation-method=EXPLANATION_METHOD]
[--explanation-path-count=EXPLANATION_PATH_COUNT]
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[--explanation-step-count=EXPLANATION_STEP_COUNT]
[--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]
[--smooth-grad-noise-sigma-by-feature=[KEY=VALUE,...]]
[--smooth-grad-noisy-sample-count=SMOOTH_GRAD_NOISY_SAMPLE_COUNT]
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[--version-aliases=[VERSION_ALIASES,...]]
[--version-description=VERSION_DESCRIPTION] [GCLOUD_WIDE_FLAG ...]
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EXAMPLES
To upload a model under project example in region us-central1, run:
$ gcloud ai models upload \
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--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
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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-env-vars=[KEY=VALUE,...]
List of key-value pairs to set as environment variables.
--container-health-route=CONTAINER_HEALTH_ROUTE
HTTP path to send health checks to inside the container.
--container-ports=[PORT,...]
Container ports to receive 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.
--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-path-count=EXPLANATION_PATH_COUNT
Number of feature permutations to consider when approximating the
Shapley values for explanation.
--explanation-step-count=EXPLANATION_STEP_COUNT
Number of steps to approximate the path integral for explanation.
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--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.
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--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.
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Value should be provided in format:
projects/PROJECT_ID/locations/REGION/models/PARENT_MODEL_ID
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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.
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--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.
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--version-description=VERSION_DESCRIPTION
Description of the model version.
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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
These variants are also available:
$ gcloud alpha ai models upload
$ gcloud beta ai models upload