Google AutoML v1 API - Class ModelExportOutputConfig (3.2.0) 

public sealed class ModelExportOutputConfig : IMessage<ModelExportOutputConfig>, IEquatable<ModelExportOutputConfig>, IDeepCloneable<ModelExportOutputConfig>, IBufferMessage, IMessage

Reference documentation and code samples for the Google AutoML v1 API class ModelExportOutputConfig.

Output configuration for ModelExport Action.

Inheritance

object > ModelExportOutputConfig

Namespace

Google.Cloud.AutoML.V1

Assembly

Google.Cloud.AutoML.V1.dll

Constructors

ModelExportOutputConfig()

public ModelExportOutputConfig()

ModelExportOutputConfig(ModelExportOutputConfig)

public ModelExportOutputConfig(ModelExportOutputConfig other)
Parameter
NameDescription
otherModelExportOutputConfig

Properties

DestinationCase

public ModelExportOutputConfig.DestinationOneofCase DestinationCase { get; }
Property Value
TypeDescription
ModelExportOutputConfigDestinationOneofCase

GcsDestination

public GcsDestination GcsDestination { get; set; }

Required. The Google Cloud Storage location where the model is to be written to. This location may only be set for the following model formats: "tflite", "edgetpu_tflite", "tf_saved_model", "tf_js", "core_ml".

Under the directory given as the destination a new one with name "model-export-<model-display-name>-<timestamp-of-export-call>", where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format, will be created. Inside the model and any of its supporting files will be written.

Property Value
TypeDescription
GcsDestination

ModelFormat

public string ModelFormat { get; set; }

The format in which the model must be exported. The available, and default, formats depend on the problem and model type (if given problem and type combination doesn't have a format listed, it means its models are not exportable):

  • For Image Classification mobile-low-latency-1, mobile-versatile-1, mobile-high-accuracy-1: "tflite" (default), "edgetpu_tflite", "tf_saved_model", "tf_js", "docker".

  • For Image Classification mobile-core-ml-low-latency-1, mobile-core-ml-versatile-1, mobile-core-ml-high-accuracy-1: "core_ml" (default).

  • For Image Object Detection mobile-low-latency-1, mobile-versatile-1, mobile-high-accuracy-1: "tflite", "tf_saved_model", "tf_js". Formats description:

  • tflite - Used for Android mobile devices.

  • edgetpu_tflite - Used for Edge TPU devices.
  • tf_saved_model - A tensorflow model in SavedModel format.
  • tf_js - A TensorFlow.js model that can be used in the browser and in Node.js using JavaScript.
  • docker - Used for Docker containers. Use the params field to customize the container. The container is verified to work correctly on ubuntu 16.04 operating system. See more at containers quickstart
  • core_ml - Used for iOS mobile devices.
Property Value
TypeDescription
string

Params

public MapField<string, string> Params { get; }

Additional model-type and format specific parameters describing the requirements for the to be exported model files, any string must be up to 25000 characters long.

  • For docker format: cpu_architecture - (string) "x86_64" (default). gpu_architecture - (string) "none" (default), "nvidia".
Property Value
TypeDescription
MapFieldstringstring