// Copyright 2019 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// Note: this file is purely for documentation. Any contents are not expected
// to be loaded as the JS file.
/**
* Dataset metadata that is specific to image classification.
*
* @property {number} classificationType
* Required. Type of the classification problem.
*
* The number should be among the values of [ClassificationType]{@link google.cloud.automl.v1beta1.ClassificationType}
*
* @typedef ImageClassificationDatasetMetadata
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.ImageClassificationDatasetMetadata definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/image.proto}
*/
const ImageClassificationDatasetMetadata = {
// This is for documentation. Actual contents will be loaded by gRPC.
};
/**
* Dataset metadata specific to image object detection.
* @typedef ImageObjectDetectionDatasetMetadata
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.ImageObjectDetectionDatasetMetadata definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/image.proto}
*/
const ImageObjectDetectionDatasetMetadata = {
// This is for documentation. Actual contents will be loaded by gRPC.
};
/**
* Model metadata for image classification.
*
* @property {string} baseModelId
* Optional. The ID of the `base` model. If it is specified, the new model
* will be created based on the `base` model. Otherwise, the new model will be
* created from scratch. The `base` model must be in the same
* `project` and `location` as the new model to create, and have the same
* `model_type`.
*
* @property {number} trainBudget
* Required. The train budget of creating this model, expressed in hours. The
* actual `train_cost` will be equal or less than this value.
*
* @property {number} trainCost
* Output only. The actual train cost of creating this model, expressed in
* hours. If this model is created from a `base` model, the train cost used
* to create the `base` model are not included.
*
* @property {string} stopReason
* Output only. The reason that this create model operation stopped,
* e.g. `BUDGET_REACHED`, `MODEL_CONVERGED`.
*
* @property {string} modelType
* Optional. Type of the model. The available values are:
* * `cloud` - Model to be used via prediction calls to AutoML API.
* 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)
* 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)
* 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)
* 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)
* 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)
* 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)
* 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.
*
* @typedef ImageClassificationModelMetadata
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.ImageClassificationModelMetadata definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/image.proto}
*/
const ImageClassificationModelMetadata = {
// This is for documentation. Actual contents will be loaded by gRPC.
};
/**
* Model metadata specific to image object detection.
*
* @property {string} modelType
* Optional. Type of the model. The available values are:
* * `cloud-high-accuracy-1` - (default) A model to be used via prediction
* calls to AutoML API. Expected to have a higher latency, but
* should also have a higher prediction quality than other
* models.
* * `cloud-low-latency-1` - A model to be used via prediction
* calls to AutoML API. Expected to have low latency, but may
* have lower prediction quality than other models.
*
* @property {number} nodeCount
* Output only. The number of nodes this model is deployed on. A node is an
* abstraction of a machine resource, which can handle online prediction QPS
* as given in the qps_per_node field.
*
* @property {number} nodeQps
* Output only. An approximate number of online prediction QPS that can
* be supported by this model per each node on which it is deployed.
*
* @property {string} stopReason
* Output only. The reason that this create model operation stopped,
* e.g. `BUDGET_REACHED`, `MODEL_CONVERGED`.
*
* @property {number} trainBudgetMilliNodeHours
* The train budget of creating this model, expressed in milli node
* hours i.e. 1,000 value in this field means 1 node hour. The actual
* `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.
* 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.
*
* @property {number} trainCostMilliNodeHours
* Output only. The actual train cost of creating this model, expressed in
* milli node hours, i.e. 1,000 value in this field means 1 node hour.
* Guaranteed to not exceed the train budget.
*
* @typedef ImageObjectDetectionModelMetadata
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.ImageObjectDetectionModelMetadata definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/image.proto}
*/
const ImageObjectDetectionModelMetadata = {
// This is for documentation. Actual contents will be loaded by gRPC.
};
/**
* Model deployment metadata specific to Image Classification.
*
* @property {number} nodeCount
* 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.
* Must be between 1 and 100, inclusive on both ends.
*
* @typedef ImageClassificationModelDeploymentMetadata
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.ImageClassificationModelDeploymentMetadata definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/image.proto}
*/
const ImageClassificationModelDeploymentMetadata = {
// This is for documentation. Actual contents will be loaded by gRPC.
};
/**
* Model deployment metadata specific to Image Object Detection.
*
* @property {number} nodeCount
* 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
*
* qps_per_node.
* Must be between 1 and 100, inclusive on both ends.
*
* @typedef ImageObjectDetectionModelDeploymentMetadata
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.ImageObjectDetectionModelDeploymentMetadata definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/image.proto}
*/
const ImageObjectDetectionModelDeploymentMetadata = {
// This is for documentation. Actual contents will be loaded by gRPC.
};