# 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 Object Detection Model. # @!attribute [rw] inputs # @return [::Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageObjectDetectionInputs] # The input parameters of this TrainingJob. # @!attribute [rw] metadata # @return [::Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageObjectDetectionMetadata] # The metadata information class AutoMlImageObjectDetection include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # @!attribute [rw] model_type # @return [::Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageObjectDetectionInputs::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 20,000 # and 900,000 milli node hours, inclusive. The default value is 216,000 # which represents one day in wall time, considering 9 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 Object Detection might stop training before the entire training # budget has been used. class AutoMlImageObjectDetectionInputs 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. Expected to have a higher latency, but should also have a # higher prediction quality than other cloud models. CLOUD_HIGH_ACCURACY_1 = 1 # A model best tailored to be used within Google Cloud, and which cannot # be exported. Expected to have a low latency, but may have lower # prediction quality than other cloud models. CLOUD_LOW_LATENCY_1 = 2 # A model that, in addition to being available within Google # Cloud can also be exported (see ModelService.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 mobile models. MOBILE_TF_LOW_LATENCY_1 = 3 # A model that, in addition to being available within Google # Cloud can also be exported (see ModelService.ExportModel) and # used on a mobile or edge device with TensorFlow afterwards. MOBILE_TF_VERSATILE_1 = 4 # A model that, in addition to being available within Google # Cloud, can also be exported (see ModelService.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 mobile models. MOBILE_TF_HIGH_ACCURACY_1 = 5 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::AutoMlImageObjectDetectionMetadata::SuccessfulStopReason] # For successful job completions, this is the reason why the job has # finished. class AutoMlImageObjectDetectionMetadata 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