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feat(all): auto-regenerate discovery clients (#2069)
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yoshi-automation authored Jul 14, 2023
1 parent 25a3230 commit 16cf0c3
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9 changes: 8 additions & 1 deletion artifactregistry/v1/artifactregistry-api.json
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Expand Up @@ -1661,7 +1661,7 @@
}
}
},
"revision": "20230628",
"revision": "20230710",
"rootUrl": "https://artifactregistry.googleapis.com/",
"schemas": {
"AptArtifact": {
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"type": "string"
},
"versionAge": {
"deprecated": true,
"description": "DEPRECATED: Use older_than.",
"format": "google-duration",
"type": "string"
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"REDIRECTION_FROM_GCR_IO_ENABLED",
"REDIRECTION_FROM_GCR_IO_FINALIZED"
],
"enumDeprecated": [
false,
false,
false,
true
],
"enumDescriptions": [
"No redirection status has been set.",
"Redirection is disabled.",
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8 changes: 7 additions & 1 deletion artifactregistry/v1beta2/artifactregistry-api.json
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Expand Up @@ -1135,7 +1135,7 @@
}
}
},
"revision": "20230522",
"revision": "20230710",
"rootUrl": "https://artifactregistry.googleapis.com/",
"schemas": {
"AptArtifact": {
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"REDIRECTION_FROM_GCR_IO_ENABLED",
"REDIRECTION_FROM_GCR_IO_FINALIZED"
],
"enumDeprecated": [
false,
false,
false,
true
],
"enumDescriptions": [
"No redirection status has been set.",
"Redirection is disabled.",
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90 changes: 88 additions & 2 deletions bigquery/v2/bigquery-api.json
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Expand Up @@ -1710,7 +1710,7 @@
}
}
},
"revision": "20230617",
"revision": "20230708",
"rootUrl": "https://bigquery.googleapis.com/",
"schemas": {
"AggregateClassificationMetrics": {
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"id": "ArimaForecastingMetrics",
"properties": {
"arimaFittingMetrics": {
"deprecated": true,
"description": "Arima model fitting metrics.",
"items": {
"$ref": "ArimaFittingMetrics"
Expand All @@ -1869,20 +1870,23 @@
"type": "array"
},
"hasDrift": {
"deprecated": true,
"description": "Whether Arima model fitted with drift or not. It is always false when d is not 1.",
"items": {
"type": "boolean"
},
"type": "array"
},
"nonSeasonalOrder": {
"deprecated": true,
"description": "Non-seasonal order.",
"items": {
"$ref": "ArimaOrder"
},
"type": "array"
},
"seasonalPeriods": {
"deprecated": true,
"description": "Seasonal periods. Repeated because multiple periods are supported for one time series.",
"items": {
"enum": [
Expand All @@ -1908,6 +1912,7 @@
"type": "array"
},
"timeSeriesId": {
"deprecated": true,
"description": "Id to differentiate different time series for the large-scale case.",
"items": {
"type": "string"
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"id": "Model",
"properties": {
"bestTrialId": {
"deprecated": true,
"description": "The best trial_id across all training runs.",
"format": "int64",
"type": "string"
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"type": "string"
},
"featureColumns": {
"description": "Output only. Input feature columns that were used to train this model.",
"description": "Output only. Input feature columns for the model inference. If the model is trained with TRANSFORM clause, these are the input of the TRANSFORM clause.",
"items": {
"$ref": "StandardSqlField"
},
Expand Down Expand Up @@ -7084,6 +7090,10 @@
"description": "Options used in model training.",
"id": "TrainingOptions",
"properties": {
"activationFn": {
"description": "Activation function of the neural nets.",
"type": "string"
},
"adjustStepChanges": {
"description": "If true, detect step changes and make data adjustment in the input time series.",
"type": "boolean"
Expand All @@ -7106,6 +7116,10 @@
"format": "int64",
"type": "string"
},
"autoClassWeights": {
"description": "Whether to calculate class weights automatically based on the popularity of each label.",
"type": "boolean"
},
"batchSize": {
"description": "Batch size for dnn models.",
"format": "int64",
Expand All @@ -7125,6 +7139,11 @@
],
"type": "string"
},
"budgetHours": {
"description": "Budget in hours for AutoML training.",
"format": "double",
"type": "number"
},
"calculatePValues": {
"description": "Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.",
"type": "boolean"
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],
"type": "string"
},
"fitIntercept": {
"description": "Whether the model should include intercept during model training.",
"type": "boolean"
},
"hiddenUnits": {
"description": "Hidden units for dnn models.",
"items": {
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],
"type": "string"
},
"l1RegActivation": {
"description": "L1 regularization coefficient to activations.",
"format": "double",
"type": "number"
},
"l1Regularization": {
"description": "L1 regularization coefficient.",
"format": "double",
Expand Down Expand Up @@ -7626,6 +7654,18 @@
"format": "int64",
"type": "string"
},
"modelRegistry": {
"description": "The model registry.",
"enum": [
"MODEL_REGISTRY_UNSPECIFIED",
"VERTEX_AI"
],
"enumDescriptions": [
"",
"Vertex AI."
],
"type": "string"
},
"modelUri": {
"description": "Google Cloud Storage URI from which the model was imported. Only applicable for imported models.",
"type": "string"
Expand All @@ -7649,6 +7689,11 @@
"format": "int64",
"type": "string"
},
"numPrincipalComponents": {
"description": "Number of principal components to keep in the PCA model. Must be \u003c= the number of features.",
"format": "int64",
"type": "string"
},
"numTrials": {
"description": "Number of trials to run this hyperparameter tuning job.",
"format": "int64",
Expand All @@ -7668,11 +7713,44 @@
],
"type": "string"
},
"optimizer": {
"description": "Optimizer used for training the neural nets.",
"type": "string"
},
"pcaExplainedVarianceRatio": {
"description": "The minimum ratio of cumulative explained variance that needs to be given by the PCA model.",
"format": "double",
"type": "number"
},
"pcaSolver": {
"description": "The solver for PCA.",
"enum": [
"UNSPECIFIED",
"FULL",
"RANDOMIZED",
"AUTO"
],
"enumDescriptions": [
"",
"Full eigen-decoposition.",
"Randomized SVD.",
"Auto."
],
"type": "string"
},
"sampledShapleyNumPaths": {
"description": "Number of paths for the sampled Shapley explain method.",
"format": "int64",
"type": "string"
},
"scaleFeatures": {
"description": "If true, scale the feature values by dividing the feature standard deviation. Currently only apply to PCA.",
"type": "boolean"
},
"standardizeFeatures": {
"description": "Whether to standardize numerical features. Default to true.",
"type": "boolean"
},
"subsample": {
"description": "Subsample fraction of the training data to grow tree to prevent overfitting for boosted tree models.",
"format": "double",
Expand Down Expand Up @@ -7733,6 +7811,13 @@
"description": "User column specified for matrix factorization models.",
"type": "string"
},
"vertexAiModelVersionAliases": {
"description": "The version aliases to apply in Vertex AI model registry. Always overwrite if the version aliases exists in a existing model.",
"items": {
"type": "string"
},
"type": "array"
},
"walsAlpha": {
"description": "Hyperparameter for matrix factoration when implicit feedback type is specified.",
"format": "double",
Expand Down Expand Up @@ -7796,6 +7881,7 @@
"readOnly": true
},
"trainingStartTime": {
"deprecated": true,
"description": "Output only. The start time of this training run, in milliseconds since epoch.",
"format": "int64",
"readOnly": true,
Expand Down
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