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    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: 
 "imageClassificationModelMetadata" : 
 { 
 object(  ImageClassificationModelMetadata 
 
) 
 } 
 , 
 "textClassificationModelMetadata" : 
 { 
 object(  TextClassificationModelMetadata 
 
) 
 } 
 , 
 "translationModelMetadata" : 
 { 
 object(  TranslationModelMetadata 
 
) 
 } 
 // 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. The first character must be 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 this model was created.

    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:
    imageClassificationModelMetadata

    object( ImageClassificationModelMetadata )

    Metadata for image classification models.

    textClassificationModelMetadata

    object( TextClassificationModelMetadata )

    Metadata for text classification models.

    translationModelMetadata

    object( TranslationModelMetadata )

    Metadata for translation models.

    ImageClassificationModelMetadata

    Model metadata for image classification.

    JSON representation 
     { 
 "baseModelId" : 
 string 
 , 
 "trainBudget" : 
 string 
 , 
 "trainCost" : 
 string 
 , 
 "stopReason" : 
 string 
 }
    Fields
    baseModelId

    string

    Optional. The ID of the base model. If it is specified, the new model will be created based on the base model. Otherwise, the new model will be created from scratch. The base model is expected to be in the same project and location as the new model to create.
    trainBudget

    string ( int64 format)

    Required. The train budget of creating this model. The actual trainCost will be equal or less than this value.
    trainCost

    string ( int64 format)

    Output only. The actual train cost of creating this model. If this model is created from a base model, the train cost used to create the base model are not included.
    stopReason

    string

    Output only. The reason that this create model operation stopped, e.g. BUDGET_REACHED, MODEL_CONVERGED.

    TextClassificationModelMetadata

    Model metadata that is specific to text classification.

    TranslationModelMetadata

    Model metadata that is specific to translation.

    JSON representation 
     { 
 "baseModel" : 
 string 
 , 
 "sourceLanguageCode" : 
 string 
 , 
 "targetLanguageCode" : 
 string 
 }
    Fields
    baseModel

    string

    The resource name of the model to use as a baseline to train the custom model. If unset, we use the default base model provided by Google Translate. Format: projects/{project_id}/locations/{locationId}/models/{modelId}

    sourceLanguageCode

    string

    Output only. Inferred from the dataset. The source language (The BCP-47 language code) that is used for training.
    targetLanguageCode

    string

    Output only. The target language (The BCP-47 language code) that is used for training.

    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

    create

    		Creates a model.

    delete

    		Deletes a model.

    get

    		Gets a model.

    getIamPolicy

    		Gets the access control policy for a resource.

    list

    		Lists models.

    predict

    		Perform a prediction.

    setIamPolicy

    		Sets the access control policy on the specified resource.
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