REST Resource: projects.locations.models

Resource: Model

API proto representing a trained machine learning model.

JSON representation
{
  "name": string,
  "displayName": string,
  "datasetId": string,
  "createTime": string,
  "updateTime": string,
  "deploymentState": enum(DeploymentState),

  // Union field model_metadata can be only one of the following:
  "textClassificationModelMetadata": {
    object(TextClassificationModelMetadata)
  },
  "textExtractionModelMetadata": {
    object(TextExtractionModelMetadata)
  },
  "textSentimentModelMetadata": {
    object(TextSentimentModelMetadata)
  }
  // End of list of possible types for union field model_metadata.
}
Fields
name

string

Output only. Resource name of the model. Format: projects/{project_id}/locations/{locationId}/models/{modelId}

displayName

string

Required. The name of the model to show in the interface. The name can be up to 32 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscores (_), and ASCII digits 0-9. It must start with a letter.

datasetId

string

Required. The resource ID of the dataset used to create the model. The dataset must come from the same ancestor project and location.

createTime

string (Timestamp format)

Output only. Timestamp when the model training finished and can be used for prediction.

A timestamp in RFC3339 UTC "Zulu" format, accurate to nanoseconds. Example: "2014-10-02T15:01:23.045123456Z".

updateTime

string (Timestamp format)

Output only. Timestamp when this model was last updated.

A timestamp in RFC3339 UTC "Zulu" format, accurate to nanoseconds. Example: "2014-10-02T15:01:23.045123456Z".

deploymentState

enum(DeploymentState)

Output only. Deployment state of the model. A model can only serve prediction requests after it gets deployed.

Union field model_metadata. Required. The model metadata that is specific to the problem type. Must match the metadata type of the dataset used to train the model. model_metadata can be only one of the following:
textClassificationModelMetadata

object(TextClassificationModelMetadata)

Metadata for text classification models.

textExtractionModelMetadata

object(TextExtractionModelMetadata)

Metadata for text extraction models.

textSentimentModelMetadata

object(TextSentimentModelMetadata)

Metadata for text extraction models.

TextClassificationModelMetadata

Model metadata that is specific to text classification.

TextExtractionModelMetadata

Model metadata that is specific to text extraction.

TextSentimentModelMetadata

Model metadata that is specific to text classification.

DeploymentState

Deployment state of the model.

Enums
DEPLOYMENT_STATE_UNSPECIFIED Should not be used, an un-set enum has this value by default.
DEPLOYED Model is deployed.
UNDEPLOYED Model is not deployed.

Methods

batchPredict

Perform a batch prediction and return the id of a long-running operation.

create

Creates a model.

delete

Deletes a model.

deploy

Deploys a model.

get

Gets a model.

getIamPolicy

Gets the access control policy for a resource.

list

Lists models.

predict

Perform an online prediction.

setIamPolicy

Sets the access control policy on the specified resource.

undeploy

Removes a deployed model.
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