Cloud AutoML V1beta1 API - Class Google::Cloud::AutoML::V1beta1::ModelExportOutputConfig (v0.9.0)

Reference documentation and code samples for the Cloud AutoML V1beta1 API class Google::Cloud::AutoML::V1beta1::ModelExportOutputConfig.

Output configuration for ModelExport Action.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#gcr_destination

def gcr_destination() -> ::Google::Cloud::AutoML::V1beta1::GcrDestination
Returns

#gcr_destination=

def gcr_destination=(value) -> ::Google::Cloud::AutoML::V1beta1::GcrDestination
Parameter
  • value (::Google::Cloud::AutoML::V1beta1::GcrDestination) — The GCR location where model image is to be pushed to. This location may only be set for the following model formats: "docker".

    The model image will be created under the given URI.

Returns

#gcs_destination

def gcs_destination() -> ::Google::Cloud::AutoML::V1beta1::GcsDestination
Returns
  • (::Google::Cloud::AutoML::V1beta1::GcsDestination) — 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-

#gcs_destination=

def gcs_destination=(value) -> ::Google::Cloud::AutoML::V1beta1::GcsDestination
Parameter
  • value (::Google::Cloud::AutoML::V1beta1::GcsDestination) — 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-

Returns
  • (::Google::Cloud::AutoML::V1beta1::GcsDestination) — 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_format

def model_format() -> ::String
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".

    • For Video Classification cloud, "tf_saved_model".

    • For Video Object Tracking cloud, "tf_saved_model".

    • For Video Object Tracking mobile-versatile-1: "tflite", "edgetpu_tflite", "tf_saved_model", "docker".

    • For Video Object Tracking mobile-coral-versatile-1: "tflite", "edgetpu_tflite", "docker".

    • For Video Object Tracking mobile-coral-low-latency-1: "tflite", "edgetpu_tflite", "docker".

    • For Video Object Tracking mobile-jetson-versatile-1: "tf_saved_model", "docker".

    • For Tables: "docker".

    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](https: //cloud.google.com/vision/automl/docs/containers-gcs-quickstart)

    • core_ml - Used for iOS mobile devices.

#model_format=

def model_format=(value) -> ::String
Parameter
  • value (::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".

    • For Video Classification cloud, "tf_saved_model".

    • For Video Object Tracking cloud, "tf_saved_model".

    • For Video Object Tracking mobile-versatile-1: "tflite", "edgetpu_tflite", "tf_saved_model", "docker".

    • For Video Object Tracking mobile-coral-versatile-1: "tflite", "edgetpu_tflite", "docker".

    • For Video Object Tracking mobile-coral-low-latency-1: "tflite", "edgetpu_tflite", "docker".

    • For Video Object Tracking mobile-jetson-versatile-1: "tf_saved_model", "docker".

    • For Tables: "docker".

    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](https: //cloud.google.com/vision/automl/docs/containers-gcs-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".

    • For Video Classification cloud, "tf_saved_model".

    • For Video Object Tracking cloud, "tf_saved_model".

    • For Video Object Tracking mobile-versatile-1: "tflite", "edgetpu_tflite", "tf_saved_model", "docker".

    • For Video Object Tracking mobile-coral-versatile-1: "tflite", "edgetpu_tflite", "docker".

    • For Video Object Tracking mobile-coral-low-latency-1: "tflite", "edgetpu_tflite", "docker".

    • For Video Object Tracking mobile-jetson-versatile-1: "tf_saved_model", "docker".

    • For Tables: "docker".

    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](https: //cloud.google.com/vision/automl/docs/containers-gcs-quickstart)

    • core_ml - Used for iOS mobile devices.

#params

def params() -> ::Google::Protobuf::Map{::String => ::String}
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".

#params=

def params=(value) -> ::Google::Protobuf::Map{::String => ::String}
Parameter
  • value (::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".
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".