| Index: generated/googleapis_beta/lib/ml/v1beta1.dart
|
| diff --git a/generated/googleapis_beta/lib/ml/v1beta1.dart b/generated/googleapis_beta/lib/ml/v1beta1.dart
|
| index af79bdab571e34aedd28a6bee9d28ddad6963f67..9fd37cad2cc6243abcae72157c9418a8e3959401 100644
|
| --- a/generated/googleapis_beta/lib/ml/v1beta1.dart
|
| +++ b/generated/googleapis_beta/lib/ml/v1beta1.dart
|
| @@ -1596,6 +1596,12 @@ class GoogleCloudMlV1beta1Model {
|
| * The model name must be unique within the project it is created in.
|
| */
|
| core.String name;
|
| + /**
|
| + * Optional. The list of regions where the model is going to be deployed.
|
| + * Currently only one region per model is supported.
|
| + * Defaults to 'us-central1' if nothing is set.
|
| + */
|
| + core.List<core.String> regions;
|
|
|
| GoogleCloudMlV1beta1Model();
|
|
|
| @@ -1609,6 +1615,9 @@ class GoogleCloudMlV1beta1Model {
|
| if (_json.containsKey("name")) {
|
| name = _json["name"];
|
| }
|
| + if (_json.containsKey("regions")) {
|
| + regions = _json["regions"];
|
| + }
|
| }
|
|
|
| core.Map toJson() {
|
| @@ -1622,6 +1631,9 @@ class GoogleCloudMlV1beta1Model {
|
| if (name != null) {
|
| _json["name"] = name;
|
| }
|
| + if (regions != null) {
|
| + _json["regions"] = regions;
|
| + }
|
| return _json;
|
| }
|
| }
|
| @@ -1976,6 +1988,11 @@ class GoogleCloudMlV1beta1PredictionInput {
|
| */
|
| core.String region;
|
| /**
|
| + * Optional. The Google Cloud ML runtime version to use for this batch
|
| + * prediction. If not set, Google Cloud ML will choose a version.
|
| + */
|
| + core.String runtimeVersion;
|
| + /**
|
| * Use this field if you want to specify a version of the model to use. The
|
| * string is formatted the same way as `model_version`, with the addition
|
| * of the version information:
|
| @@ -2005,6 +2022,9 @@ class GoogleCloudMlV1beta1PredictionInput {
|
| if (_json.containsKey("region")) {
|
| region = _json["region"];
|
| }
|
| + if (_json.containsKey("runtimeVersion")) {
|
| + runtimeVersion = _json["runtimeVersion"];
|
| + }
|
| if (_json.containsKey("versionName")) {
|
| versionName = _json["versionName"];
|
| }
|
| @@ -2030,6 +2050,9 @@ class GoogleCloudMlV1beta1PredictionInput {
|
| if (region != null) {
|
| _json["region"] = region;
|
| }
|
| + if (runtimeVersion != null) {
|
| + _json["runtimeVersion"] = runtimeVersion;
|
| + }
|
| if (versionName != null) {
|
| _json["versionName"] = versionName;
|
| }
|
| @@ -2041,6 +2064,8 @@ class GoogleCloudMlV1beta1PredictionInput {
|
| class GoogleCloudMlV1beta1PredictionOutput {
|
| /** The number of data instances which resulted in errors. */
|
| core.String errorCount;
|
| + /** Node hours used by the batch prediction job. */
|
| + core.double nodeHours;
|
| /**
|
| * The output Google Cloud Storage location provided at the job creation time.
|
| */
|
| @@ -2054,6 +2079,9 @@ class GoogleCloudMlV1beta1PredictionOutput {
|
| if (_json.containsKey("errorCount")) {
|
| errorCount = _json["errorCount"];
|
| }
|
| + if (_json.containsKey("nodeHours")) {
|
| + nodeHours = _json["nodeHours"];
|
| + }
|
| if (_json.containsKey("outputPath")) {
|
| outputPath = _json["outputPath"];
|
| }
|
| @@ -2067,6 +2095,9 @@ class GoogleCloudMlV1beta1PredictionOutput {
|
| if (errorCount != null) {
|
| _json["errorCount"] = errorCount;
|
| }
|
| + if (nodeHours != null) {
|
| + _json["nodeHours"] = nodeHours;
|
| + }
|
| if (outputPath != null) {
|
| _json["outputPath"] = outputPath;
|
| }
|
| @@ -2166,6 +2197,11 @@ class GoogleCloudMlV1beta1TrainingInput {
|
| /** Required. The Google Compute Engine region to run the training job in. */
|
| core.String region;
|
| /**
|
| + * Optional. The Google Cloud ML runtime version to use for training. If not
|
| + * set, Google Cloud ML will choose the latest stable version.
|
| + */
|
| + core.String runtimeVersion;
|
| + /**
|
| * Required. Specifies the machine types, the number of replicas for workers
|
| * and parameter servers.
|
| * Possible string values are:
|
| @@ -2247,6 +2283,9 @@ class GoogleCloudMlV1beta1TrainingInput {
|
| if (_json.containsKey("region")) {
|
| region = _json["region"];
|
| }
|
| + if (_json.containsKey("runtimeVersion")) {
|
| + runtimeVersion = _json["runtimeVersion"];
|
| + }
|
| if (_json.containsKey("scaleTier")) {
|
| scaleTier = _json["scaleTier"];
|
| }
|
| @@ -2284,6 +2323,9 @@ class GoogleCloudMlV1beta1TrainingInput {
|
| if (region != null) {
|
| _json["region"] = region;
|
| }
|
| + if (runtimeVersion != null) {
|
| + _json["runtimeVersion"] = runtimeVersion;
|
| + }
|
| if (scaleTier != null) {
|
| _json["scaleTier"] = scaleTier;
|
| }
|
| @@ -2297,15 +2339,21 @@ class GoogleCloudMlV1beta1TrainingInput {
|
| }
|
| }
|
|
|
| -/** Represents results of a training job. */
|
| +/** Represents results of a training job. Output only. */
|
| class GoogleCloudMlV1beta1TrainingOutput {
|
| /**
|
| * The number of hyperparameter tuning trials that completed successfully.
|
| + * Only set for hyperparameter tuning jobs.
|
| */
|
| core.String completedTrialCount;
|
| /** The amount of ML units consumed by the job. */
|
| - core.double consumedMlUnits;
|
| - /** Results for individual Hyperparameter trials. */
|
| + core.double consumedMLUnits;
|
| + /** Whether this job is a hyperparameter tuning job. */
|
| + core.bool isHyperparameterTuningJob;
|
| + /**
|
| + * Results for individual Hyperparameter trials.
|
| + * Only set for hyperparameter tuning jobs.
|
| + */
|
| core.List<GoogleCloudMlV1beta1HyperparameterOutput> trials;
|
|
|
| GoogleCloudMlV1beta1TrainingOutput();
|
| @@ -2314,8 +2362,11 @@ class GoogleCloudMlV1beta1TrainingOutput {
|
| if (_json.containsKey("completedTrialCount")) {
|
| completedTrialCount = _json["completedTrialCount"];
|
| }
|
| - if (_json.containsKey("consumedMlUnits")) {
|
| - consumedMlUnits = _json["consumedMlUnits"];
|
| + if (_json.containsKey("consumedMLUnits")) {
|
| + consumedMLUnits = _json["consumedMLUnits"];
|
| + }
|
| + if (_json.containsKey("isHyperparameterTuningJob")) {
|
| + isHyperparameterTuningJob = _json["isHyperparameterTuningJob"];
|
| }
|
| if (_json.containsKey("trials")) {
|
| trials = _json["trials"].map((value) => new GoogleCloudMlV1beta1HyperparameterOutput.fromJson(value)).toList();
|
| @@ -2327,8 +2378,11 @@ class GoogleCloudMlV1beta1TrainingOutput {
|
| if (completedTrialCount != null) {
|
| _json["completedTrialCount"] = completedTrialCount;
|
| }
|
| - if (consumedMlUnits != null) {
|
| - _json["consumedMlUnits"] = consumedMlUnits;
|
| + if (consumedMLUnits != null) {
|
| + _json["consumedMLUnits"] = consumedMLUnits;
|
| + }
|
| + if (isHyperparameterTuningJob != null) {
|
| + _json["isHyperparameterTuningJob"] = isHyperparameterTuningJob;
|
| }
|
| if (trials != null) {
|
| _json["trials"] = trials.map((value) => (value).toJson()).toList();
|
| @@ -2381,6 +2435,16 @@ class GoogleCloudMlV1beta1Version {
|
| * The version name must be unique within the model it is created in.
|
| */
|
| core.String name;
|
| + /**
|
| + * Optional. If true, enables StackDriver Logging for online prediction.
|
| + * Default is false.
|
| + */
|
| + core.bool onlinePredictionLogging;
|
| + /**
|
| + * Optional. The Google Cloud ML runtime version to use for this deployment.
|
| + * If not set, Google Cloud ML will choose a version.
|
| + */
|
| + core.String runtimeVersion;
|
|
|
| GoogleCloudMlV1beta1Version();
|
|
|
| @@ -2403,6 +2467,12 @@ class GoogleCloudMlV1beta1Version {
|
| if (_json.containsKey("name")) {
|
| name = _json["name"];
|
| }
|
| + if (_json.containsKey("onlinePredictionLogging")) {
|
| + onlinePredictionLogging = _json["onlinePredictionLogging"];
|
| + }
|
| + if (_json.containsKey("runtimeVersion")) {
|
| + runtimeVersion = _json["runtimeVersion"];
|
| + }
|
| }
|
|
|
| core.Map toJson() {
|
| @@ -2425,6 +2495,12 @@ class GoogleCloudMlV1beta1Version {
|
| if (name != null) {
|
| _json["name"] = name;
|
| }
|
| + if (onlinePredictionLogging != null) {
|
| + _json["onlinePredictionLogging"] = onlinePredictionLogging;
|
| + }
|
| + if (runtimeVersion != null) {
|
| + _json["runtimeVersion"] = runtimeVersion;
|
| + }
|
| return _json;
|
| }
|
| }
|
|
|