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feat: adds ImageClassificationModelDeploymentMetadata
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@yoshi-automation @bcoe
yoshi-automation authored and bcoe committed Oct 1, 2019
1 parent 129be93 commit 42d766d
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Showing 9 changed files with 67,603 additions and 46 deletions.
56 changes: 34 additions & 22 deletions protos/google/cloud/automl/v1beta1/image.proto
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Expand Up @@ -17,10 +17,10 @@ syntax = "proto3";

package google.cloud.automl.v1beta1;

import "google/api/annotations.proto";
import "google/cloud/automl/v1beta1/annotation_spec.proto";
import "google/cloud/automl/v1beta1/classification.proto";
import "google/protobuf/timestamp.proto";
import "google/api/annotations.proto";

option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1beta1;automl";
option java_multiple_files = true;
Expand All @@ -36,9 +36,7 @@ message ImageClassificationDatasetMetadata {
}

// Dataset metadata specific to image object detection.
message ImageObjectDetectionDatasetMetadata {

}
message ImageObjectDetectionDatasetMetadata {}

// Model metadata for image classification.
message ImageClassificationModelMetadata {
Expand Down Expand Up @@ -67,34 +65,38 @@ message ImageClassificationModelMetadata {
// This is the default value.
// * `mobile-low-latency-1` - A model that, in addition to providing
// prediction via AutoML API, can also be exported (see
// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel]) and used on a mobile or edge device
// with TensorFlow afterwards. Expected to have low latency, but
// may have lower prediction quality than other models.
// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel])
// and used on a mobile or edge device with TensorFlow
// afterwards. Expected to have low latency, but may have lower
// prediction quality than other models.
// * `mobile-versatile-1` - A model that, in addition to providing
// prediction via AutoML API, can also be exported (see
// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel]) and used on a mobile or edge device
// with TensorFlow afterwards.
// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel])
// and used on a mobile or edge device with TensorFlow
// afterwards.
// * `mobile-high-accuracy-1` - A model that, in addition to providing
// prediction via AutoML API, can also be exported (see
// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel]) and used on a mobile or edge device
// with TensorFlow afterwards. Expected to have a higher
// latency, but should also have a higher prediction quality
// than other models.
// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel])
// and used on a mobile or edge device with TensorFlow
// afterwards. Expected to have a higher latency, but should
// also have a higher prediction quality than other models.
// * `mobile-core-ml-low-latency-1` - A model that, in addition to providing
// prediction via AutoML API, can also be exported (see
// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel]) and used on a mobile device with Core
// ML afterwards. Expected to have low latency, but may have
// lower prediction quality than other models.
// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel])
// and used on a mobile device with Core ML afterwards. Expected
// to have low latency, but may have lower prediction quality
// than other models.
// * `mobile-core-ml-versatile-1` - A model that, in addition to providing
// prediction via AutoML API, can also be exported (see
// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel]) and used on a mobile device with Core
// ML afterwards.
// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel])
// and used on a mobile device with Core ML afterwards.
// * `mobile-core-ml-high-accuracy-1` - A model that, in addition to
// providing prediction via AutoML API, can also be exported
// (see [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel]) and used on a mobile device with
// Core ML afterwards. Expected to have a higher latency, but
// should also have a higher prediction quality than other
// models.
// (see
// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel])
// and used on a mobile device with Core ML afterwards. Expected
// to have a higher latency, but should also have a higher
// prediction quality than other models.
string model_type = 7;
}

Expand Down Expand Up @@ -146,6 +148,16 @@ message ImageObjectDetectionModelMetadata {
int64 train_cost_milli_node_hours = 7;
}

// Model deployment metadata specific to Image Classification.
message ImageClassificationModelDeploymentMetadata {
// Input only. The number of nodes to deploy the model on. A node is an
// abstraction of a machine resource, which can handle online prediction QPS
// as given in the model's
// [node_qps][google.cloud.automl.v1p1beta.ImageClassificationModelMetadata.node_qps].
// Must be between 1 and 100, inclusive on both ends.
int64 node_count = 1;
}

// Model deployment metadata specific to Image Object Detection.
message ImageObjectDetectionModelDeploymentMetadata {
// Input only. The number of nodes to deploy the model on. A node is an
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2 changes: 2 additions & 0 deletions protos/google/cloud/automl/v1beta1/service.proto
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Expand Up @@ -549,6 +549,8 @@ message DeployModelRequest {
oneof model_deployment_metadata {
// Model deployment metadata specific to Image Object Detection.
ImageObjectDetectionModelDeploymentMetadata image_object_detection_model_deployment_metadata = 2;
// Model deployment metadata specific to Image Classification.
ImageClassificationModelDeploymentMetadata image_classification_model_deployment_metadata = 4;
}

// Resource name of the model to deploy.
Expand Down

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