feat: introduces validRowCount

protos/google/cloud/automl/v1beta1/classification.proto

@@ -164,6 +164,15 @@ message ClassificationEvaluationMetrics {
     // only list of [annotation_spec_display_name-s][] is populated.
     repeated string annotation_spec_id = 1;
 
+    // Output only. Display name of the annotation specs used in the confusion
+    // matrix, as they were at the moment of the evaluation. For Tables
+    // CLASSIFICATION
+    //
+    // [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type],
+    // distinct values of the target column at the moment of the model
+    // evaluation are populated here.
+    repeated string display_name = 3;
+
     // Output only. Rows in the confusion matrix. The number of rows is equal to
     // the size of `annotation_spec_id`.
     // `row[i].value[j]` is the number of examples that have ground truth of the

protos/google/cloud/automl/v1beta1/column_spec.proto

@@ -64,12 +64,7 @@ message ColumnSpec {
   // for the timestamp at which these stats were last updated.
   DataStats data_stats = 4;
 
-  // Output only. Top 10 most correlated with this column columns of the table,
-  // ordered by
-  // [cramers_v][google.cloud.automl.v1beta1.CorrelationStats.cramers_v] metric.
-  // This field may be stale, see the ancestor's
-  // Dataset.tables_dataset_metadata.stats_update_time field
-  // for the timestamp at which these stats were last updated.
+  // Deprecated.
   repeated CorrelatedColumn top_correlated_columns = 5;
 
   // Used to perform consistent read-modify-write updates. If not set, a blind

protos/google/cloud/automl/v1beta1/data_items.proto

@@ -56,9 +56,9 @@ message TextSnippet {
   // characters long.
   string content = 1;
 
-  // The format of the source text. Currently the only two allowed values are
-  // "text/html" and "text/plain". If left blank the format is automatically
-  // determined from the type of the uploaded content.
+  // Optional. The format of [content][google.cloud.automl.v1beta1.TextSnippet.content]. Currently the only two allowed
+  // values are "text/html" and "text/plain". If left blank, the format is
+  // automatically determined from the type of the uploaded [content][google.cloud.automl.v1beta1.TextSnippet.content].
   string mime_type = 2;
 
   // Output only. HTTP URI where you can download the content.
@@ -73,19 +73,19 @@ message Document {
 
 // A representation of a row in a relational table.
 message Row {
-  // Input Only.
   // The resource IDs of the column specs describing the columns of the row.
-  // If set must contain, but possibly in a different order, all input feature
+  // If set must contain, but possibly in a different order, all input
+  // feature
   //
   // [column_spec_ids][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs]
   // of the Model this row is being passed to.
   // Note: The below `values` field must match order of this field, if this
   // field is set.
   repeated string column_spec_ids = 2;
 
-  // Input Only.
-  // The values of the row cells, given in the same order as the
-  // column_spec_ids, or, if not set, then in the same order as input feature
+  // Required. The values of the row cells, given in the same order as the
+  // column_spec_ids, or, if not set, then in the same order as input
+  // feature
   //
   // [column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs]
   // of the Model this row is being passed to.

protos/google/cloud/automl/v1beta1/data_types.proto

@@ -27,14 +27,6 @@ option ruby_package = "Google::Cloud::AutoML::V1beta1";
 
 // `TypeCode` is used as a part of
 // [DataType][google.cloud.automl.v1beta1.DataType].
-//
-// Each legal value of a DataType can be encoded to or decoded from a JSON
-// value, using the encodings listed below, and definitions of which can be
-// found at
-//
-// https:
-// //developers.google.com/protocol-buffers
-// // /docs/reference/google.protobuf#value.
 enum TypeCode {
   // Not specified. Should not be used.
   TYPE_CODE_UNSPECIFIED = 0;

protos/google/cloud/automl/v1beta1/detection.proto

@@ -29,20 +29,17 @@ option ruby_package = "Google::Cloud::AutoML::V1beta1";
 
 // Annotation details for image object detection.
 message ImageObjectDetectionAnnotation {
-  // Output only.
-  // The rectangle representing the object location.
+  // Output only. The rectangle representing the object location.
   BoundingPoly bounding_box = 1;
 
-  // Output only.
-  // The confidence that this annotation is positive for the parent example,
+  // Output only. The confidence that this annotation is positive for the parent example,
   // value in [0, 1], higher means higher positivity confidence.
   float score = 2;
 }
 
 // Annotation details for video object tracking.
 message VideoObjectTrackingAnnotation {
-  // Optional.
-  // The instance of the object, expressed as a positive integer. Used to tell
+  // Optional. The instance of the object, expressed as a positive integer. Used to tell
   // apart objects of the same type (i.e. AnnotationSpec) when multiple are
   // present on a single example.
   // NOTE: Instance ID prediction quality is not a part of model evaluation and
@@ -59,8 +56,7 @@ message VideoObjectTrackingAnnotation {
   // at the time_offset of the video).
   BoundingPoly bounding_box = 3;
 
-  // Output only.
-  // The confidence that this annotation is positive for the video at
+  // Output only. The confidence that this annotation is positive for the video at
   // the time_offset, value in [0, 1], higher means higher positivity
   // confidence. For annotations created by the user the score is 1. When
   // user approves an annotation, the original float score is kept (and not

protos/google/cloud/automl/v1beta1/image.proto

@@ -128,9 +128,16 @@ message ImageObjectDetectionModelMetadata {
   // `train_cost` will be equal or less than this value. If further model
   // training ceases to provide any improvements, it will stop without using
   // full budget and the stop_reason will be `MODEL_CONVERGED`.
-  // Note, node_hour  = actual_hour * number_of_nodes_invovled. The train budget
-  // must be between 20,000 and 2,000,000 milli node hours, inclusive. The
-  // default value is 216, 000 which represents one day in wall time.
+  // Note, node_hour  = actual_hour * number_of_nodes_invovled.
+  // For model type `cloud-high-accuracy-1`(default) and `cloud-low-latency-1`,
+  // the train budget must be between 20,000 and 2,000,000 milli node hours,
+  // inclusive. The default value is 216, 000 which represents one day in
+  // wall time.
+  // For model type `mobile-low-latency-1`, `mobile-versatile-1`,
+  // `mobile-high-accuracy-1`, `mobile-core-ml-low-latency-1`,
+  // `mobile-core-ml-versatile-1`, `mobile-core-ml-high-accuracy-1`, the train
+  // budget must be between 1,000 and 100,000 milli node hours, inclusive.
+  // The default value is 24, 000 which represents one day in wall time.
   int64 train_budget_milli_node_hours = 6;
 
   // Output only. The actual train cost of creating this model, expressed in