Class: Google::Cloud::AutoML::V1::ModelExportOutputConfig

Inherits:
Object
  • Object
show all
Extended by:
Protobuf::MessageExts::ClassMethods
Includes:
Protobuf::MessageExts
Defined in:
proto_docs/google/cloud/automl/v1/io.rb

Overview

Output configuration for ModelExport Action.

Defined Under Namespace

Classes: ParamsEntry

Instance Attribute Summary collapse

Instance Attribute Details

#gcs_destination ⇒ ::Google::Cloud::AutoML::V1::GcsDestination

Returns 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--", 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.

Returns:

  • (::Google::Cloud::AutoML::V1::GcsDestination) —

    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--", 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.



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# File 'proto_docs/google/cloud/automl/v1/io.rb', line 1304

class ModelExportOutputConfig
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class ParamsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#model_format ⇒ ::String

Returns 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.

Returns:

  • (::String) —

    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.



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# File 'proto_docs/google/cloud/automl/v1/io.rb', line 1304

class ModelExportOutputConfig
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class ParamsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#params ⇒ ::Google::Protobuf::Map{::String => ::String}

Returns 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".

Returns:

  • (::Google::Protobuf::Map{::String => ::String}) —

    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".


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# File 'proto_docs/google/cloud/automl/v1/io.rb', line 1304

class ModelExportOutputConfig
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # @!attribute [rw] key
  #   @return [::String]
  # @!attribute [rw] value
  #   @return [::String]
  class ParamsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end