# frozen_string_literal: true
# Copyright 2022 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.
# Auto-generated by gapic-generator-ruby. DO NOT EDIT!
module Google
module Cloud
module AIPlatform
module V1
module Schema
module TrainingJob
module Definition
# A TrainingJob that trains and uploads an AutoML Image Classification Model.
# @!attribute [rw] inputs
# @return [::Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageClassificationInputs]
# The input parameters of this TrainingJob.
# @!attribute [rw] metadata
# @return [::Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageClassificationMetadata]
# The metadata information.
class AutoMlImageClassification
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
# @!attribute [rw] model_type
# @return [::Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageClassificationInputs::ModelType]
# @!attribute [rw] base_model_id
# @return [::String]
# The ID of the `base` model. If it is specified, the new model will be
# trained based on the `base` model. Otherwise, the new model will be
# trained from scratch. The `base` model must be in the same
# Project and Location as the new Model to train, and have the same
# modelType.
# @!attribute [rw] budget_milli_node_hours
# @return [::Integer]
# The training budget of creating this model, expressed in milli node
# hours i.e. 1,000 value in this field means 1 node hour. The actual
# metadata.costMilliNodeHours will be equal or less than this value.
# If further model training ceases to provide any improvements, it will
# stop without using the full budget and the metadata.successfulStopReason
# will be `model-converged`.
# Note, node_hour = actual_hour * number_of_nodes_involved.
# For modelType `cloud`(default), the budget must be between 8,000
# and 800,000 milli node hours, inclusive. The default value is 192,000
# which represents one day in wall time, considering 8 nodes are used.
# For model types `mobile-tf-low-latency-1`, `mobile-tf-versatile-1`,
# `mobile-tf-high-accuracy-1`, the training 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 on a
# single node that is used.
# @!attribute [rw] disable_early_stopping
# @return [::Boolean]
# Use the entire training budget. This disables the early stopping feature.
# When false the early stopping feature is enabled, which means that
# AutoML Image Classification might stop training before the entire
# training budget has been used.
# @!attribute [rw] multi_label
# @return [::Boolean]
# If false, a single-label (multi-class) Model will be trained (i.e.
# assuming that for each image just up to one annotation may be
# applicable). If true, a multi-label Model will be trained (i.e.
# assuming that for each image multiple annotations may be applicable).
class AutoMlImageClassificationInputs
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
module ModelType
# Should not be set.
MODEL_TYPE_UNSPECIFIED = 0
# A Model best tailored to be used within Google Cloud, and which cannot
# be exported.
# Default.
CLOUD = 1
# A model that, in addition to being available within Google
# Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow
# or Core ML model and used on a mobile or edge device afterwards.
# Expected to have low latency, but may have lower prediction
# quality than other mobile models.
MOBILE_TF_LOW_LATENCY_1 = 2
# A model that, in addition to being available within Google
# Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow
# or Core ML model and used on a mobile or edge device with afterwards.
MOBILE_TF_VERSATILE_1 = 3
# A model that, in addition to being available within Google
# Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow
# or Core ML model and used on a mobile or edge device afterwards.
# Expected to have a higher latency, but should also have a higher
# prediction quality than other mobile models.
MOBILE_TF_HIGH_ACCURACY_1 = 4
end
end
# @!attribute [rw] cost_milli_node_hours
# @return [::Integer]
# The actual training 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 inputs.budgetMilliNodeHours.
# @!attribute [rw] successful_stop_reason
# @return [::Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageClassificationMetadata::SuccessfulStopReason]
# For successful job completions, this is the reason why the job has
# finished.
class AutoMlImageClassificationMetadata
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
module SuccessfulStopReason
# Should not be set.
SUCCESSFUL_STOP_REASON_UNSPECIFIED = 0
# The inputs.budgetMilliNodeHours had been reached.
BUDGET_REACHED = 1
# Further training of the Model ceased to increase its quality, since it
# already has converged.
MODEL_CONVERGED = 2
end
end
end
end
end
end
end
end
end