Interface ModelExportOutputConfigOrBuilder (2.1.23)

Version 2.1.23

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public interface ModelExportOutputConfigOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

containsParams(String key)

public abstract boolean containsParams(String key)

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".

map<string, string> params = 2;

Parameter

Name	Description
key	String

Returns

Type	Description
boolean

getDestinationCase()

public abstract ModelExportOutputConfig.DestinationCase getDestinationCase()

Returns

Type	Description
ModelExportOutputConfig.DestinationCase

getGcrDestination()

public abstract GcrDestination getGcrDestination()

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.

.google.cloud.automl.v1beta1.GcrDestination gcr_destination = 3;

Returns

Type	Description
GcrDestination	The gcrDestination.

getGcrDestinationOrBuilder()

public abstract GcrDestinationOrBuilder getGcrDestinationOrBuilder()

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.

.google.cloud.automl.v1beta1.GcrDestination gcr_destination = 3;

Returns

Type	Description
GcrDestinationOrBuilder

getGcsDestination()

public abstract GcsDestination getGcsDestination()

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.

.google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;

Returns

Type	Description
GcsDestination	The gcsDestination.

getGcsDestinationOrBuilder()

public abstract GcsDestinationOrBuilder getGcsDestinationOrBuilder()

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.

.google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;

Returns

Type	Description
GcsDestinationOrBuilder

getModelFormat()

public abstract String getModelFormat()

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
• core_ml - Used for iOS mobile devices.

string model_format = 4;

Returns

Type	Description
String	The modelFormat.

getModelFormatBytes()

public abstract ByteString getModelFormatBytes()

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
• core_ml - Used for iOS mobile devices.

string model_format = 4;

Returns

Type	Description
ByteString	The bytes for modelFormat.

getParams()

public abstract Map<String,String> getParams()

Use #getParamsMap() instead.

Returns

Type	Description
Map<String,String>

getParamsCount()

public abstract int getParamsCount()

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".

map<string, string> params = 2;

Returns

Type	Description
int

getParamsMap()

public abstract Map<String,String> getParamsMap()

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".

map<string, string> params = 2;

Returns

Type	Description
Map<String,String>

getParamsOrDefault(String key, String defaultValue)

public abstract String getParamsOrDefault(String key, String defaultValue)

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".

map<string, string> params = 2;

Parameters

Name	Description
key	String
defaultValue	String

Returns

Type	Description
String

getParamsOrThrow(String key)

public abstract String getParamsOrThrow(String key)

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".

map<string, string> params = 2;

Parameter

Name	Description
key	String

Returns

Type	Description
String

hasGcrDestination()

public abstract boolean hasGcrDestination()

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.

.google.cloud.automl.v1beta1.GcrDestination gcr_destination = 3;

Returns

Type	Description
boolean	Whether the gcrDestination field is set.

hasGcsDestination()

public abstract boolean hasGcsDestination()

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.

.google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;

Returns

Type	Description
boolean	Whether the gcsDestination field is set.