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A native Pulumi package for creating and managing Azure resources.
// *** WARNING: this file was generated by pulumi-java-gen. ***
// *** Do not edit by hand unless you're certain you know what you are doing! ***
package com.pulumi.azurenative.machinelearningservices.inputs;
import com.pulumi.azurenative.machinelearningservices.enums.InstanceSegmentationPrimaryMetrics;
import com.pulumi.azurenative.machinelearningservices.enums.LogVerbosity;
import com.pulumi.azurenative.machinelearningservices.inputs.ImageLimitSettingsArgs;
import com.pulumi.azurenative.machinelearningservices.inputs.ImageModelDistributionSettingsObjectDetectionArgs;
import com.pulumi.azurenative.machinelearningservices.inputs.ImageModelSettingsObjectDetectionArgs;
import com.pulumi.azurenative.machinelearningservices.inputs.ImageSweepSettingsArgs;
import com.pulumi.azurenative.machinelearningservices.inputs.MLTableJobInputArgs;
import com.pulumi.core.Either;
import com.pulumi.core.Output;
import com.pulumi.core.annotations.Import;
import com.pulumi.core.internal.Codegen;
import com.pulumi.exceptions.MissingRequiredPropertyException;
import java.lang.Double;
import java.lang.String;
import java.util.List;
import java.util.Objects;
import java.util.Optional;
import javax.annotation.Nullable;
/**
* Image Instance Segmentation. Instance segmentation is used to identify objects in an image at the pixel level,
* drawing a polygon around each object in the image.
*
*/
public final class ImageInstanceSegmentationArgs extends com.pulumi.resources.ResourceArgs {
public static final ImageInstanceSegmentationArgs Empty = new ImageInstanceSegmentationArgs();
/**
* [Required] Limit settings for the AutoML job.
*
*/
@Import(name="limitSettings", required=true)
private Output limitSettings;
/**
* @return [Required] Limit settings for the AutoML job.
*
*/
public Output limitSettings() {
return this.limitSettings;
}
/**
* Log verbosity for the job.
*
*/
@Import(name="logVerbosity")
private @Nullable Output> logVerbosity;
/**
* @return Log verbosity for the job.
*
*/
public Optional>> logVerbosity() {
return Optional.ofNullable(this.logVerbosity);
}
/**
* Settings used for training the model.
*
*/
@Import(name="modelSettings")
private @Nullable Output modelSettings;
/**
* @return Settings used for training the model.
*
*/
public Optional> modelSettings() {
return Optional.ofNullable(this.modelSettings);
}
/**
* Primary metric to optimize for this task.
*
*/
@Import(name="primaryMetric")
private @Nullable Output> primaryMetric;
/**
* @return Primary metric to optimize for this task.
*
*/
public Optional>> primaryMetric() {
return Optional.ofNullable(this.primaryMetric);
}
/**
* Search space for sampling different combinations of models and their hyperparameters.
*
*/
@Import(name="searchSpace")
private @Nullable Output> searchSpace;
/**
* @return Search space for sampling different combinations of models and their hyperparameters.
*
*/
public Optional>> searchSpace() {
return Optional.ofNullable(this.searchSpace);
}
/**
* Model sweeping and hyperparameter sweeping related settings.
*
*/
@Import(name="sweepSettings")
private @Nullable Output sweepSettings;
/**
* @return Model sweeping and hyperparameter sweeping related settings.
*
*/
public Optional> sweepSettings() {
return Optional.ofNullable(this.sweepSettings);
}
/**
* Target column name: This is prediction values column.
* Also known as label column name in context of classification tasks.
*
*/
@Import(name="targetColumnName")
private @Nullable Output targetColumnName;
/**
* @return Target column name: This is prediction values column.
* Also known as label column name in context of classification tasks.
*
*/
public Optional> targetColumnName() {
return Optional.ofNullable(this.targetColumnName);
}
/**
* AutoMLJob Task type.
* Expected value is 'ImageInstanceSegmentation'.
*
*/
@Import(name="taskType", required=true)
private Output taskType;
/**
* @return AutoMLJob Task type.
* Expected value is 'ImageInstanceSegmentation'.
*
*/
public Output taskType() {
return this.taskType;
}
/**
* [Required] Training data input.
*
*/
@Import(name="trainingData", required=true)
private Output trainingData;
/**
* @return [Required] Training data input.
*
*/
public Output trainingData() {
return this.trainingData;
}
/**
* Validation data inputs.
*
*/
@Import(name="validationData")
private @Nullable Output validationData;
/**
* @return Validation data inputs.
*
*/
public Optional> validationData() {
return Optional.ofNullable(this.validationData);
}
/**
* The fraction of training dataset that needs to be set aside for validation purpose.
* Values between (0.0 , 1.0)
* Applied when validation dataset is not provided.
*
*/
@Import(name="validationDataSize")
private @Nullable Output validationDataSize;
/**
* @return The fraction of training dataset that needs to be set aside for validation purpose.
* Values between (0.0 , 1.0)
* Applied when validation dataset is not provided.
*
*/
public Optional> validationDataSize() {
return Optional.ofNullable(this.validationDataSize);
}
private ImageInstanceSegmentationArgs() {}
private ImageInstanceSegmentationArgs(ImageInstanceSegmentationArgs $) {
this.limitSettings = $.limitSettings;
this.logVerbosity = $.logVerbosity;
this.modelSettings = $.modelSettings;
this.primaryMetric = $.primaryMetric;
this.searchSpace = $.searchSpace;
this.sweepSettings = $.sweepSettings;
this.targetColumnName = $.targetColumnName;
this.taskType = $.taskType;
this.trainingData = $.trainingData;
this.validationData = $.validationData;
this.validationDataSize = $.validationDataSize;
}
public static Builder builder() {
return new Builder();
}
public static Builder builder(ImageInstanceSegmentationArgs defaults) {
return new Builder(defaults);
}
public static final class Builder {
private ImageInstanceSegmentationArgs $;
public Builder() {
$ = new ImageInstanceSegmentationArgs();
}
public Builder(ImageInstanceSegmentationArgs defaults) {
$ = new ImageInstanceSegmentationArgs(Objects.requireNonNull(defaults));
}
/**
* @param limitSettings [Required] Limit settings for the AutoML job.
*
* @return builder
*
*/
public Builder limitSettings(Output limitSettings) {
$.limitSettings = limitSettings;
return this;
}
/**
* @param limitSettings [Required] Limit settings for the AutoML job.
*
* @return builder
*
*/
public Builder limitSettings(ImageLimitSettingsArgs limitSettings) {
return limitSettings(Output.of(limitSettings));
}
/**
* @param logVerbosity Log verbosity for the job.
*
* @return builder
*
*/
public Builder logVerbosity(@Nullable Output> logVerbosity) {
$.logVerbosity = logVerbosity;
return this;
}
/**
* @param logVerbosity Log verbosity for the job.
*
* @return builder
*
*/
public Builder logVerbosity(Either logVerbosity) {
return logVerbosity(Output.of(logVerbosity));
}
/**
* @param logVerbosity Log verbosity for the job.
*
* @return builder
*
*/
public Builder logVerbosity(String logVerbosity) {
return logVerbosity(Either.ofLeft(logVerbosity));
}
/**
* @param logVerbosity Log verbosity for the job.
*
* @return builder
*
*/
public Builder logVerbosity(LogVerbosity logVerbosity) {
return logVerbosity(Either.ofRight(logVerbosity));
}
/**
* @param modelSettings Settings used for training the model.
*
* @return builder
*
*/
public Builder modelSettings(@Nullable Output modelSettings) {
$.modelSettings = modelSettings;
return this;
}
/**
* @param modelSettings Settings used for training the model.
*
* @return builder
*
*/
public Builder modelSettings(ImageModelSettingsObjectDetectionArgs modelSettings) {
return modelSettings(Output.of(modelSettings));
}
/**
* @param primaryMetric Primary metric to optimize for this task.
*
* @return builder
*
*/
public Builder primaryMetric(@Nullable Output> primaryMetric) {
$.primaryMetric = primaryMetric;
return this;
}
/**
* @param primaryMetric Primary metric to optimize for this task.
*
* @return builder
*
*/
public Builder primaryMetric(Either primaryMetric) {
return primaryMetric(Output.of(primaryMetric));
}
/**
* @param primaryMetric Primary metric to optimize for this task.
*
* @return builder
*
*/
public Builder primaryMetric(String primaryMetric) {
return primaryMetric(Either.ofLeft(primaryMetric));
}
/**
* @param primaryMetric Primary metric to optimize for this task.
*
* @return builder
*
*/
public Builder primaryMetric(InstanceSegmentationPrimaryMetrics primaryMetric) {
return primaryMetric(Either.ofRight(primaryMetric));
}
/**
* @param searchSpace Search space for sampling different combinations of models and their hyperparameters.
*
* @return builder
*
*/
public Builder searchSpace(@Nullable Output> searchSpace) {
$.searchSpace = searchSpace;
return this;
}
/**
* @param searchSpace Search space for sampling different combinations of models and their hyperparameters.
*
* @return builder
*
*/
public Builder searchSpace(List searchSpace) {
return searchSpace(Output.of(searchSpace));
}
/**
* @param searchSpace Search space for sampling different combinations of models and their hyperparameters.
*
* @return builder
*
*/
public Builder searchSpace(ImageModelDistributionSettingsObjectDetectionArgs... searchSpace) {
return searchSpace(List.of(searchSpace));
}
/**
* @param sweepSettings Model sweeping and hyperparameter sweeping related settings.
*
* @return builder
*
*/
public Builder sweepSettings(@Nullable Output sweepSettings) {
$.sweepSettings = sweepSettings;
return this;
}
/**
* @param sweepSettings Model sweeping and hyperparameter sweeping related settings.
*
* @return builder
*
*/
public Builder sweepSettings(ImageSweepSettingsArgs sweepSettings) {
return sweepSettings(Output.of(sweepSettings));
}
/**
* @param targetColumnName Target column name: This is prediction values column.
* Also known as label column name in context of classification tasks.
*
* @return builder
*
*/
public Builder targetColumnName(@Nullable Output targetColumnName) {
$.targetColumnName = targetColumnName;
return this;
}
/**
* @param targetColumnName Target column name: This is prediction values column.
* Also known as label column name in context of classification tasks.
*
* @return builder
*
*/
public Builder targetColumnName(String targetColumnName) {
return targetColumnName(Output.of(targetColumnName));
}
/**
* @param taskType AutoMLJob Task type.
* Expected value is 'ImageInstanceSegmentation'.
*
* @return builder
*
*/
public Builder taskType(Output taskType) {
$.taskType = taskType;
return this;
}
/**
* @param taskType AutoMLJob Task type.
* Expected value is 'ImageInstanceSegmentation'.
*
* @return builder
*
*/
public Builder taskType(String taskType) {
return taskType(Output.of(taskType));
}
/**
* @param trainingData [Required] Training data input.
*
* @return builder
*
*/
public Builder trainingData(Output trainingData) {
$.trainingData = trainingData;
return this;
}
/**
* @param trainingData [Required] Training data input.
*
* @return builder
*
*/
public Builder trainingData(MLTableJobInputArgs trainingData) {
return trainingData(Output.of(trainingData));
}
/**
* @param validationData Validation data inputs.
*
* @return builder
*
*/
public Builder validationData(@Nullable Output validationData) {
$.validationData = validationData;
return this;
}
/**
* @param validationData Validation data inputs.
*
* @return builder
*
*/
public Builder validationData(MLTableJobInputArgs validationData) {
return validationData(Output.of(validationData));
}
/**
* @param validationDataSize The fraction of training dataset that needs to be set aside for validation purpose.
* Values between (0.0 , 1.0)
* Applied when validation dataset is not provided.
*
* @return builder
*
*/
public Builder validationDataSize(@Nullable Output validationDataSize) {
$.validationDataSize = validationDataSize;
return this;
}
/**
* @param validationDataSize The fraction of training dataset that needs to be set aside for validation purpose.
* Values between (0.0 , 1.0)
* Applied when validation dataset is not provided.
*
* @return builder
*
*/
public Builder validationDataSize(Double validationDataSize) {
return validationDataSize(Output.of(validationDataSize));
}
public ImageInstanceSegmentationArgs build() {
if ($.limitSettings == null) {
throw new MissingRequiredPropertyException("ImageInstanceSegmentationArgs", "limitSettings");
}
$.logVerbosity = Codegen.stringProp("logVerbosity").left(LogVerbosity.class).output().arg($.logVerbosity).def("Info").getNullable();
$.primaryMetric = Codegen.stringProp("primaryMetric").left(InstanceSegmentationPrimaryMetrics.class).output().arg($.primaryMetric).def("MeanAveragePrecision").getNullable();
$.taskType = Codegen.stringProp("taskType").output().arg($.taskType).require();
if ($.trainingData == null) {
throw new MissingRequiredPropertyException("ImageInstanceSegmentationArgs", "trainingData");
}
return $;
}
}
}
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