Reference documentation and code samples for the Cloud AutoML V1beta1 Client class ModelExportOutputConfig.
Output configuration for ModelExport Action.
Generated from protobuf message google.cloud.automl.v1beta1.ModelExportOutputConfig
Namespace
Google \ Cloud \ AutoMl \ V1beta1Methods
__construct
Constructor.
| Parameters | |
|---|---|
| Name | Description |
data |
array
Optional. Data for populating the Message object. |
↳ gcs_destination |
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-
|
↳ gcr_destination |
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. |
↳ model_format |
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 |
array|Google\Protobuf\Internal\MapField
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 |
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-
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AutoMl\V1beta1\GcsDestination|null |
|
hasGcsDestination
setGcsDestination
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-
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Cloud\AutoMl\V1beta1\GcsDestination
|
| Returns | |
|---|---|
| Type | Description |
$this |
|
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.
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AutoMl\V1beta1\GcrDestination|null |
|
hasGcrDestination
setGcrDestination
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.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Cloud\AutoMl\V1beta1\GcrDestination
|
| Returns | |
|---|---|
| Type | Description |
$this |
|
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](https: //cloud.google.com/vision/automl/docs/containers-gcs-quickstart)
- core_ml - Used for iOS mobile devices.
| Returns | |
|---|---|
| Type | Description |
string |
|
setModelFormat
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.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this |
|
getParams
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
dockerformat:cpu_architecture- (string) "x86_64" (default).gpu_architecture- (string) "none" (default), "nvidia".
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Internal\MapField |
|
setParams
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
dockerformat:cpu_architecture- (string) "x86_64" (default).gpu_architecture- (string) "none" (default), "nvidia".
| Parameter | |
|---|---|
| Name | Description |
var |
array|Google\Protobuf\Internal\MapField
|
| Returns | |
|---|---|
| Type | Description |
$this |
|
getDestination
| Returns | |
|---|---|
| Type | Description |
string |
|