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131 lines
6.3 KiB
131 lines
6.3 KiB
// Copyright 2018 Google LLC.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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syntax = "proto3";
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package google.cloud.automl.v1beta1;
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import "google/api/annotations.proto";
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import "google/cloud/automl/v1beta1/classification.proto";
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import "google/protobuf/timestamp.proto";
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option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1beta1;automl";
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option java_multiple_files = true;
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option java_outer_classname = "ImageProto";
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option java_package = "com.google.cloud.automl.v1beta1";
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option php_namespace = "Google\\Cloud\\AutoMl\\V1beta1";
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// Dataset metadata that is specific to image classification.
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message ImageClassificationDatasetMetadata {
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// Required. Type of the classification problem.
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ClassificationType classification_type = 1;
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}
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// Dataset metadata specific to image object detection.
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message ImageObjectDetectionDatasetMetadata {
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}
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// Model metadata for image classification.
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message ImageClassificationModelMetadata {
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// Optional. The ID of the `base` model. If it is specified, the new model
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// will be created based on the `base` model. Otherwise, the new model will be
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// created from scratch. The `base` model must be in the same
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// `project` and `location` as the new model to create, and have the same
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// `model_type`.
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string base_model_id = 1;
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// Required. The train budget of creating this model, expressed in hours. The
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// actual `train_cost` will be equal or less than this value.
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int64 train_budget = 2;
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// Output only. The actual train cost of creating this model, expressed in
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// hours. If this model is created from a `base` model, the train cost used
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// to create the `base` model are not included.
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int64 train_cost = 3;
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// Output only. The reason that this create model operation stopped,
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// e.g. `BUDGET_REACHED`, `MODEL_CONVERGED`.
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string stop_reason = 5;
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// Optional. Type of the model. The available values are:
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// * `cloud` - Model to be used via prediction calls to AutoML API.
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// This is the default value.
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// * `mobile-low-latency-1` - A model that, in addition to providing
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// prediction via AutoML API, can also be exported (see
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// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel]) and used on a mobile or edge device
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// with TensorFlow afterwards. Expected to have low latency, but
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// may have lower prediction quality than other models.
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// * `mobile-versatile-1` - A model that, in addition to providing
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// prediction via AutoML API, can also be exported (see
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// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel]) and used on a mobile or edge device
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// with TensorFlow afterwards.
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// * `mobile-high-accuracy-1` - A model that, in addition to providing
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// prediction via AutoML API, can also be exported (see
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// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel]) and used on a mobile or edge device
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// with TensorFlow afterwards. Expected to have a higher
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// latency, but should also have a higher prediction quality
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// than other models.
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// * `mobile-core-ml-low-latency-1` - A model that, in addition to providing
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// prediction via AutoML API, can also be exported (see
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// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel]) and used on a mobile device with Core
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// ML afterwards. Expected to have low latency, but may have
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// lower prediction quality than other models.
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// * `mobile-core-ml-versatile-1` - A model that, in addition to providing
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// prediction via AutoML API, can also be exported (see
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// [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel]) and used on a mobile device with Core
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// ML afterwards.
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// * `mobile-core-ml-high-accuracy-1` - A model that, in addition to
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// providing prediction via AutoML API, can also be exported
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// (see [AutoMl.ExportModel][google.cloud.automl.v1beta1.AutoMl.ExportModel]) and used on a mobile device with
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// Core ML afterwards. Expected to have a higher latency, but
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// should also have a higher prediction quality than other
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// models.
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string model_type = 7;
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}
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// Model metadata specific to image object detection.
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message ImageObjectDetectionModelMetadata {
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// Optional. Type of the model. The available values are:
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// * `cloud-high-accuracy-1` - (default) A model to be used via prediction
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// calls to AutoML API. Expected to have a higher latency, but
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// should also have a higher prediction quality than other
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// models.
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// * `cloud-low-latency-1` - A model to be used via prediction
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// calls to AutoML API. Expected to have low latency, but may
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// have lower prediction quality than other models.
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string model_type = 1;
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// Output only. The number of nodes this model is deployed on. A node is an
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// abstraction of a machine resource, which can handle online prediction QPS
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// as given in the qps_per_node field.
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int64 node_count = 3;
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// Output only. An approximate number of online prediction QPS that can
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// be supported by this model per each node on which it is deployed.
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double node_qps = 4;
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}
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// Model deployment metadata specific to Image Object Detection.
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message ImageObjectDetectionModelDeploymentMetadata {
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// Input only. The number of nodes to deploy the model on. A node is an
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// abstraction of a machine resource, which can handle online prediction QPS
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// as given in the model's
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//
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// [qps_per_node][google.cloud.automl.v1beta1.ImageObjectDetectionModelMetadata.qps_per_node].
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// Must be between 1 and 100, inclusive on both ends.
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int64 node_count = 1;
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}
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