Regen SDKs again

pulumi · Apr 28, 2024 · 6959ef1 · 6959ef1
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diff --git a/sdk/dotnet/Aiplatform/V1/Inputs/GoogleCloudAiplatformV1ExplanationMetadataArgs.cs b/sdk/dotnet/Aiplatform/V1/Inputs/GoogleCloudAiplatformV1ExplanationMetadataArgs.cs
@@ -21,23 +21,35 @@ public sealed class GoogleCloudAiplatformV1ExplanationMetadataArgs : global::Pul
         [Input("featureAttributionsSchemaUri")]
         public Input<string>? FeatureAttributionsSchemaUri { get; set; }
 
+        [Input("inputs", required: true)]
+        private InputMap<Inputs.GoogleCloudAiplatformV1ExplanationMetadataInputMetadataArgs>? _inputs;
+
         /// <summary>
         /// Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI-provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance.
         /// </summary>
-        [Input("inputs", required: true)]
-        public Input<Inputs.GoogleCloudAiplatformV1ExplanationMetadataInputMetadataArgs> Inputs { get; set; } = null!;
+        public InputMap<Inputs.GoogleCloudAiplatformV1ExplanationMetadataInputMetadataArgs> Inputs
+        {
+            get => _inputs ?? (_inputs = new InputMap<Inputs.GoogleCloudAiplatformV1ExplanationMetadataInputMetadataArgs>());
+            set => _inputs = value;
+        }
 
         /// <summary>
         /// Name of the source to generate embeddings for example based explanations.
         /// </summary>
         [Input("latentSpaceSource")]
         public Input<string>? LatentSpaceSource { get; set; }
 
+        [Input("outputs", required: true)]
+        private InputMap<Inputs.GoogleCloudAiplatformV1ExplanationMetadataOutputMetadataArgs>? _outputs;
+
         /// <summary>
         /// Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed.
         /// </summary>
-        [Input("outputs", required: true)]
-        public Input<Inputs.GoogleCloudAiplatformV1ExplanationMetadataOutputMetadataArgs> Outputs { get; set; } = null!;
+        public InputMap<Inputs.GoogleCloudAiplatformV1ExplanationMetadataOutputMetadataArgs> Outputs
+        {
+            get => _outputs ?? (_outputs = new InputMap<Inputs.GoogleCloudAiplatformV1ExplanationMetadataOutputMetadataArgs>());
+            set => _outputs = value;
+        }
 
         public GoogleCloudAiplatformV1ExplanationMetadataArgs()
         {

diff --git a/...oogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs.cs b/...oogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs.cs
@@ -15,23 +15,35 @@ namespace Pulumi.GoogleNative.Aiplatform.V1.Inputs
     /// </summary>
     public sealed class GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs : global::Pulumi.ResourceArgs
     {
+        [Input("attributionScoreDriftThresholds")]
+        private InputMap<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>? _attributionScoreDriftThresholds;
+
         /// <summary>
         /// Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows.
         /// </summary>
-        [Input("attributionScoreDriftThresholds")]
-        public Input<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>? AttributionScoreDriftThresholds { get; set; }
+        public InputMap<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs> AttributionScoreDriftThresholds
+        {
+            get => _attributionScoreDriftThresholds ?? (_attributionScoreDriftThresholds = new InputMap<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>());
+            set => _attributionScoreDriftThresholds = value;
+        }
 
         /// <summary>
         /// Drift anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
         /// </summary>
         [Input("defaultDriftThreshold")]
         public Input<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>? DefaultDriftThreshold { get; set; }
 
+        [Input("driftThresholds")]
+        private InputMap<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>? _driftThresholds;
+
         /// <summary>
         /// Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws.
         /// </summary>
-        [Input("driftThresholds")]
-        public Input<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>? DriftThresholds { get; set; }
+        public InputMap<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs> DriftThresholds
+        {
+            get => _driftThresholds ?? (_driftThresholds = new InputMap<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>());
+            set => _driftThresholds = value;
+        }
 
         public GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs()
         {

diff --git a/...oudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs.cs b/...oudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs.cs
@@ -15,23 +15,35 @@ namespace Pulumi.GoogleNative.Aiplatform.V1.Inputs
     /// </summary>
     public sealed class GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs : global::Pulumi.ResourceArgs
     {
+        [Input("attributionScoreSkewThresholds")]
+        private InputMap<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>? _attributionScoreSkewThresholds;
+
         /// <summary>
         /// Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.
         /// </summary>
-        [Input("attributionScoreSkewThresholds")]
-        public Input<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>? AttributionScoreSkewThresholds { get; set; }
+        public InputMap<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs> AttributionScoreSkewThresholds
+        {
+            get => _attributionScoreSkewThresholds ?? (_attributionScoreSkewThresholds = new InputMap<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>());
+            set => _attributionScoreSkewThresholds = value;
+        }
 
         /// <summary>
         /// Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
         /// </summary>
         [Input("defaultSkewThreshold")]
         public Input<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>? DefaultSkewThreshold { get; set; }
 
+        [Input("skewThresholds")]
+        private InputMap<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>? _skewThresholds;
+
         /// <summary>
         /// Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.
         /// </summary>
-        [Input("skewThresholds")]
-        public Input<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>? SkewThresholds { get; set; }
+        public InputMap<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs> SkewThresholds
+        {
+            get => _skewThresholds ?? (_skewThresholds = new InputMap<Inputs.GoogleCloudAiplatformV1ThresholdConfigArgs>());
+            set => _skewThresholds = value;
+        }
 
         public GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs()
         {

diff --git a/sdk/dotnet/Aiplatform/V1/Inputs/GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs.cs b/sdk/dotnet/Aiplatform/V1/Inputs/GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs.cs
@@ -27,11 +27,17 @@ public sealed class GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs : global
         [Input("gcsOutputDirectory", required: true)]
         public Input<string> GcsOutputDirectory { get; set; } = null!;
 
+        [Input("inputArtifacts")]
+        private InputMap<Inputs.GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifactArgs>? _inputArtifacts;
+
         /// <summary>
         /// The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
         /// </summary>
-        [Input("inputArtifacts")]
-        public Input<Inputs.GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifactArgs>? InputArtifacts { get; set; }
+        public InputMap<Inputs.GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifactArgs> InputArtifacts
+        {
+            get => _inputArtifacts ?? (_inputArtifacts = new InputMap<Inputs.GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifactArgs>());
+            set => _inputArtifacts = value;
+        }
 
         [Input("parameterValues")]
         private InputMap<object>? _parameterValues;
@@ -45,11 +51,18 @@ public InputMap<object> ParameterValues
             set => _parameterValues = value;
         }
 
+        [Input("parameters")]
+        private InputMap<Inputs.GoogleCloudAiplatformV1ValueArgs>? _parameters;
+
         /// <summary>
         /// Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
         /// </summary>
-        [Input("parameters")]
-        public Input<Inputs.GoogleCloudAiplatformV1ValueArgs>? Parameters { get; set; }
+        [Obsolete(@"Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.")]
+        public InputMap<Inputs.GoogleCloudAiplatformV1ValueArgs> Parameters
+        {
+            get => _parameters ?? (_parameters = new InputMap<Inputs.GoogleCloudAiplatformV1ValueArgs>());
+            set => _parameters = value;
+        }
 
         public GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs()
         {

diff --git a/sdk/dotnet/Aiplatform/V1/Outputs/GoogleCloudAiplatformV1ExplanationMetadataResponse.cs b/sdk/dotnet/Aiplatform/V1/Outputs/GoogleCloudAiplatformV1ExplanationMetadataResponse.cs
@@ -23,25 +23,25 @@ public sealed class GoogleCloudAiplatformV1ExplanationMetadataResponse
         /// <summary>
         /// Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI-provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance.
         /// </summary>
-        public readonly Outputs.GoogleCloudAiplatformV1ExplanationMetadataInputMetadataResponse Inputs;
+        public readonly ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ExplanationMetadataInputMetadataResponse> Inputs;
         /// <summary>
         /// Name of the source to generate embeddings for example based explanations.
         /// </summary>
         public readonly string LatentSpaceSource;
         /// <summary>
         /// Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed.
         /// </summary>
-        public readonly Outputs.GoogleCloudAiplatformV1ExplanationMetadataOutputMetadataResponse Outputs;
+        public readonly ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ExplanationMetadataOutputMetadataResponse> Outputs;
 
         [OutputConstructor]
         private GoogleCloudAiplatformV1ExplanationMetadataResponse(
             string featureAttributionsSchemaUri,
 
-            Outputs.GoogleCloudAiplatformV1ExplanationMetadataInputMetadataResponse inputs,
+            ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ExplanationMetadataInputMetadataResponse> inputs,
 
             string latentSpaceSource,
 
-            Outputs.GoogleCloudAiplatformV1ExplanationMetadataOutputMetadataResponse outputs)
+            ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ExplanationMetadataOutputMetadataResponse> outputs)
         {
             FeatureAttributionsSchemaUri = featureAttributionsSchemaUri;
             Inputs = inputs;

diff --git a/...eCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponse.cs b/...eCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponse.cs
@@ -19,23 +19,23 @@ public sealed class GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredict
         /// <summary>
         /// Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows.
         /// </summary>
-        public readonly Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse AttributionScoreDriftThresholds;
+        public readonly ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse> AttributionScoreDriftThresholds;
         /// <summary>
         /// Drift anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
         /// </summary>
         public readonly Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse DefaultDriftThreshold;
         /// <summary>
         /// Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws.
         /// </summary>
-        public readonly Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse DriftThresholds;
+        public readonly ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse> DriftThresholds;
 
         [OutputConstructor]
         private GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponse(
-            Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse attributionScoreDriftThresholds,
+            ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse> attributionScoreDriftThresholds,
 
             Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse defaultDriftThreshold,
 
-            Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse driftThresholds)
+            ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse> driftThresholds)
         {
             AttributionScoreDriftThresholds = attributionScoreDriftThresholds;
             DefaultDriftThreshold = defaultDriftThreshold;

diff --git a/...iplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponse.cs b/...iplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponse.cs
@@ -19,23 +19,23 @@ public sealed class GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainin
         /// <summary>
         /// Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.
         /// </summary>
-        public readonly Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse AttributionScoreSkewThresholds;
+        public readonly ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse> AttributionScoreSkewThresholds;
         /// <summary>
         /// Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
         /// </summary>
         public readonly Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse DefaultSkewThreshold;
         /// <summary>
         /// Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.
         /// </summary>
-        public readonly Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse SkewThresholds;
+        public readonly ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse> SkewThresholds;
 
         [OutputConstructor]
         private GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponse(
-            Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse attributionScoreSkewThresholds,
+            ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse> attributionScoreSkewThresholds,
 
             Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse defaultSkewThreshold,
 
-            Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse skewThresholds)
+            ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ThresholdConfigResponse> skewThresholds)
         {
             AttributionScoreSkewThresholds = attributionScoreSkewThresholds;
             DefaultSkewThreshold = defaultSkewThreshold;

diff --git a/sdk/dotnet/Aiplatform/V1/Outputs/GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse.cs b/sdk/dotnet/Aiplatform/V1/Outputs/GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse.cs
@@ -27,27 +27,27 @@ public sealed class GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse
         /// <summary>
         /// The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
         /// </summary>
-        public readonly Outputs.GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifactResponse InputArtifacts;
+        public readonly ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifactResponse> InputArtifacts;
         /// <summary>
         /// The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
         /// </summary>
         public readonly ImmutableDictionary<string, object> ParameterValues;
         /// <summary>
         /// Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
         /// </summary>
-        public readonly Outputs.GoogleCloudAiplatformV1ValueResponse Parameters;
+        public readonly ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ValueResponse> Parameters;
 
         [OutputConstructor]
         private GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse(
             string failurePolicy,
 
             string gcsOutputDirectory,
 
-            Outputs.GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifactResponse inputArtifacts,
+            ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifactResponse> inputArtifacts,
 
             ImmutableDictionary<string, object> parameterValues,
 
-            Outputs.GoogleCloudAiplatformV1ValueResponse parameters)
+            ImmutableDictionary<string, Outputs.GoogleCloudAiplatformV1ValueResponse> parameters)
         {
             FailurePolicy = failurePolicy;
             GcsOutputDirectory = gcsOutputDirectory;