GoogleCloudMlV1Model (AI Platform Training & Prediction API v1-rev20210212-1.31.0)

java.lang.Object
- java.util.AbstractMap<String,Object>
- - com.google.api.client.util.GenericData
  - - com.google.api.client.json.GenericJson
    - - com.google.api.services.ml.v1.model.GoogleCloudMlV1Model

All Implemented Interfaces:

Cloneable, Map<String,Object>
```
public final class GoogleCloudMlV1Model
extends GenericJson
```
Represents a machine learning solution. A model can have multiple versions, each of which is a deployed, trained model ready to receive prediction requests. The model itself is just a container.
This is the Java data model class that specifies how to parse/serialize into the JSON that is transmitted over HTTP when working with the AI Platform Training & Prediction API. For a detailed explanation see: https://developers.google.com/api-client-library/java/google-http-java-client/json

Author:

Google, Inc.

Nested Class Summary
- Nested classes/interfaces inherited from class com.google.api.client.util.GenericData
  GenericData.Flags
- Nested classes/interfaces inherited from class java.util.AbstractMap
  AbstractMap.SimpleEntry<K,V>, AbstractMap.SimpleImmutableEntry<K,V>
- Nested classes/interfaces inherited from interface java.util.Map
  Map.Entry<K,V>

Constructor Summary

Constructors
Constructor and Description

GoogleCloudMlV1Model()

Constructors
Constructor and Description
`GoogleCloudMlV1Model()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`GoogleCloudMlV1Model`	`clone()`
`byte[]`	`decodeEtag()` `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other.
`GoogleCloudMlV1Model`	`encodeEtag(byte[] etag)` `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other.
`GoogleCloudMlV1Version`	`getDefaultVersion()` Output only.
`String`	`getDescription()` Optional.
`String`	`getEtag()` `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other.
`Map<String,String>`	`getLabels()` Optional.
`String`	`getName()` Required.
`Boolean`	`getOnlinePredictionConsoleLogging()` Optional.
`Boolean`	`getOnlinePredictionLogging()` Optional.
`List<String>`	`getRegions()` Optional.
`GoogleCloudMlV1Model`	`set(String fieldName, Object value)`
`GoogleCloudMlV1Model`	`setDefaultVersion(GoogleCloudMlV1Version defaultVersion)` Output only.
`GoogleCloudMlV1Model`	`setDescription(String description)` Optional.
`GoogleCloudMlV1Model`	`setEtag(String etag)` `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other.
`GoogleCloudMlV1Model`	`setLabels(Map<String,String> labels)` Optional.
`GoogleCloudMlV1Model`	`setName(String name)` Required.
`GoogleCloudMlV1Model`	`setOnlinePredictionConsoleLogging(Boolean onlinePredictionConsoleLogging)` Optional.
`GoogleCloudMlV1Model`	`setOnlinePredictionLogging(Boolean onlinePredictionLogging)` Optional.
`GoogleCloudMlV1Model`	`setRegions(List<String> regions)` Optional.

Methods inherited from class com.google.api.client.json.GenericJson
getFactory, setFactory, toPrettyString, toString

Methods inherited from class com.google.api.client.util.GenericData
entrySet, equals, get, getClassInfo, getUnknownKeys, hashCode, put, putAll, remove, setUnknownKeys

Methods inherited from class java.util.AbstractMap
clear, containsKey, containsValue, isEmpty, keySet, size, values

Methods inherited from class java.lang.Object
finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.Map
compute, computeIfAbsent, computeIfPresent, forEach, getOrDefault, merge, putIfAbsent, remove, replace, replace, replaceAll

- Constructor Detail
  - GoogleCloudMlV1Model
```
public GoogleCloudMlV1Model()
```
- Method Detail
  - getDefaultVersion
```
public GoogleCloudMlV1Version getDefaultVersion()
```
    Output only. The default version of the model. This version will be used to handle prediction requests that do not specify a version. You can change the default version by calling projects.models.versions.setDefault.
    
    Returns:
    
    value or null for none
  - setDefaultVersion
```
public GoogleCloudMlV1Model setDefaultVersion(GoogleCloudMlV1Version defaultVersion)
```
    Output only. The default version of the model. This version will be used to handle prediction requests that do not specify a version. You can change the default version by calling projects.models.versions.setDefault.
    
    Parameters:
    
    defaultVersion - defaultVersion or null for none
  - getDescription
```
public String getDescription()
```
    Optional. The description specified for the model when it was created.
    
    Returns:
    
    value or null for none
  - setDescription
```
public GoogleCloudMlV1Model setDescription(String description)
```
    Optional. The description specified for the model when it was created.
    
    Parameters:
    
    description - description or null for none
  - getEtag
```
public String getEtag()
```
    `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetModel`, and systems are expected to put that etag in the request to `UpdateModel` to ensure that their change will be applied to the model as intended.
    
    Returns:
    
    value or null for none
    
    See Also:
    
    decodeEtag()
  - decodeEtag
```
public byte[] decodeEtag()
```
    `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetModel`, and systems are expected to put that etag in the request to `UpdateModel` to ensure that their change will be applied to the model as intended.
    
    Returns:
    
    Base64 decoded value or null for none
    
    Since:
    
    1.14
    
    See Also:
    
    getEtag()
  - setEtag
```
public GoogleCloudMlV1Model setEtag(String etag)
```
    `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetModel`, and systems are expected to put that etag in the request to `UpdateModel` to ensure that their change will be applied to the model as intended.
    
    Parameters:
    
    etag - etag or null for none
    
    See Also:
    
    #encodeEtag()
  - encodeEtag
```
public GoogleCloudMlV1Model encodeEtag(byte[] etag)
```
    `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetModel`, and systems are expected to put that etag in the request to `UpdateModel` to ensure that their change will be applied to the model as intended.
    
    Since:
    
    1.14
    
    See Also:
    
    The value is encoded Base64 or {@code null} for none.
  - getLabels
```
public Map<String,String> getLabels()
```
    Optional. One or more labels that you can add, to organize your models. Each label is a key- value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
    
    Returns:
    
    value or null for none
  - setLabels
```
public GoogleCloudMlV1Model setLabels(Map<String,String> labels)
```
    Optional. One or more labels that you can add, to organize your models. Each label is a key- value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
    
    Parameters:
    
    labels - labels or null for none
  - getName
```
public String getName()
```
    Required. The name specified for the model when it was created. The model name must be unique within the project it is created in.
    
    Returns:
    
    value or null for none
  - setName
```
public GoogleCloudMlV1Model setName(String name)
```
    Required. The name specified for the model when it was created. The model name must be unique within the project it is created in.
    
    Parameters:
    
    name - name or null for none
  - getOnlinePredictionConsoleLogging
```
public Boolean getOnlinePredictionConsoleLogging()
```
    Optional. If true, online prediction nodes send `stderr` and `stdout` streams to Cloud Logging. These can be more verbose than the standard access logs (see `onlinePredictionLogging`) and can incur higher cost. However, they are helpful for debugging. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high QPS. Estimate your costs before enabling this option. Default is false.
    
    Returns:
    
    value or null for none
  - setOnlinePredictionConsoleLogging
```
public GoogleCloudMlV1Model setOnlinePredictionConsoleLogging(Boolean onlinePredictionConsoleLogging)
```
    Optional. If true, online prediction nodes send `stderr` and `stdout` streams to Cloud Logging. These can be more verbose than the standard access logs (see `onlinePredictionLogging`) and can incur higher cost. However, they are helpful for debugging. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high QPS. Estimate your costs before enabling this option. Default is false.
    
    Parameters:
    
    onlinePredictionConsoleLogging - onlinePredictionConsoleLogging or null for none
  - getOnlinePredictionLogging
```
public Boolean getOnlinePredictionLogging()
```
    Optional. If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each request. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option. Default is false.
    
    Returns:
    
    value or null for none
  - setOnlinePredictionLogging
```
public GoogleCloudMlV1Model setOnlinePredictionLogging(Boolean onlinePredictionLogging)
```
    Optional. If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each request. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option. Default is false.
    
    Parameters:
    
    onlinePredictionLogging - onlinePredictionLogging or null for none
  - getRegions
```
public List<String> getRegions()
```
    Optional. The list of regions where the model is going to be deployed. Only one region per model is supported. Defaults to 'us-central1' if nothing is set. See the available regions for AI Platform services. Note: * No matter where a model is deployed, it can always be accessed by users from anywhere, both for online and batch prediction. * The region for a batch prediction job is set by the region field when submitting the batch prediction job and does not take its value from this field.
    
    Returns:
    
    value or null for none
  - setRegions
```
public GoogleCloudMlV1Model setRegions(List<String> regions)
```
    Optional. The list of regions where the model is going to be deployed. Only one region per model is supported. Defaults to 'us-central1' if nothing is set. See the available regions for AI Platform services. Note: * No matter where a model is deployed, it can always be accessed by users from anywhere, both for online and batch prediction. * The region for a batch prediction job is set by the region field when submitting the batch prediction job and does not take its value from this field.
    
    Parameters:
    
    regions - regions or null for none
  - set
```
public GoogleCloudMlV1Model set(String fieldName,
                                Object value)
```
    Overrides:
    
    set in class GenericJson
  - clone
```
public GoogleCloudMlV1Model clone()
```
    Overrides:
    
    clone in class GenericJson

Class GoogleCloudMlV1Model

Nested Class Summary

Nested classes/interfaces inherited from class com.google.api.client.util.GenericData

Nested classes/interfaces inherited from class java.util.AbstractMap

Nested classes/interfaces inherited from interface java.util.Map

Constructor Summary

Method Summary

Methods inherited from class com.google.api.client.json.GenericJson

Methods inherited from class com.google.api.client.util.GenericData

Methods inherited from class java.util.AbstractMap

Methods inherited from class java.lang.Object

Methods inherited from interface java.util.Map

Constructor Detail

GoogleCloudMlV1Model

Method Detail

getDefaultVersion

setDefaultVersion

getDescription

setDescription

getEtag

decodeEtag

setEtag

encodeEtag

getLabels

setLabels

getName

setName

getOnlinePredictionConsoleLogging

setOnlinePredictionConsoleLogging

getOnlinePredictionLogging

setOnlinePredictionLogging

getRegions

setRegions

set

clone