Reference documentation and code samples for the Cloud AutoML V1beta1 Client class ImageClassificationModelMetadata.
Model metadata for image classification.
Generated from protobuf message google.cloud.automl.v1beta1.ImageClassificationModelMetadata
Methods
__construct
Constructor.
| Parameters | |
|---|---|
| Name | Description |
data |
array
Optional. Data for populating the Message object. |
↳ base_model_id |
string
Optional. The ID of the |
↳ train_budget |
int|string
Required. The train budget of creating this model, expressed in hours. The actual |
↳ train_cost |
int|string
Output only. The actual train cost of creating this model, expressed in hours. If this model is created from a |
↳ stop_reason |
string
Output only. The reason that this create model operation stopped, e.g. |
↳ model_type |
string
Optional. Type of the model. The available values are: * |
↳ node_qps |
float
Output only. An approximate number of online prediction QPS that can be supported by this model per each node on which it is deployed. |
↳ node_count |
int|string
Output only. The number of nodes this model is deployed on. A node is an abstraction of a machine resource, which can handle online prediction QPS as given in the node_qps field. |
getBaseModelId
Optional. The ID of the base model. If it is specified, the new model
will be created based on the base model. Otherwise, the new model will be
created from scratch. The base model must be in the same
project and location as the new model to create, and have the same
model_type.
| Returns | |
|---|---|
| Type | Description |
string | |
setBaseModelId
Optional. The ID of the base model. If it is specified, the new model
will be created based on the base model. Otherwise, the new model will be
created from scratch. The base model must be in the same
project and location as the new model to create, and have the same
model_type.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getTrainBudget
Required. The train budget of creating this model, expressed in hours. The
actual train_cost will be equal or less than this value.
| Returns | |
|---|---|
| Type | Description |
int|string | |
setTrainBudget
Required. The train budget of creating this model, expressed in hours. The
actual train_cost will be equal or less than this value.
| Parameter | |
|---|---|
| Name | Description |
var |
int|string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getTrainCost
Output only. The actual train cost of creating this model, expressed in
hours. If this model is created from a base model, the train cost used
to create the base model are not included.
| Returns | |
|---|---|
| Type | Description |
int|string | |
setTrainCost
Output only. The actual train cost of creating this model, expressed in
hours. If this model is created from a base model, the train cost used
to create the base model are not included.
| Parameter | |
|---|---|
| Name | Description |
var |
int|string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getStopReason
Output only. The reason that this create model operation stopped,
e.g. BUDGET_REACHED, MODEL_CONVERGED.
| Returns | |
|---|---|
| Type | Description |
string | |
setStopReason
Output only. The reason that this create model operation stopped,
e.g. BUDGET_REACHED, MODEL_CONVERGED.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getModelType
Optional. Type of the model. The available values are:
cloud- Model to be used via prediction calls to AutoML API.
This is the default value.
mobile-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards.mobile-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.mobile-core-ml-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-core-ml-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards.mobile-core-ml-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.
| Returns | |
|---|---|
| Type | Description |
string | |
setModelType
Optional. Type of the model. The available values are:
cloud- Model to be used via prediction calls to AutoML API.
This is the default value.
mobile-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards.mobile-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.mobile-core-ml-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-core-ml-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards.mobile-core-ml-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getNodeQps
Output only. An approximate number of online prediction QPS that can be supported by this model per each node on which it is deployed.
| Returns | |
|---|---|
| Type | Description |
float | |
setNodeQps
Output only. An approximate number of online prediction QPS that can be supported by this model per each node on which it is deployed.
| Parameter | |
|---|---|
| Name | Description |
var |
float
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getNodeCount
Output only. The number of nodes this model is deployed on. A node is an abstraction of a machine resource, which can handle online prediction QPS as given in the node_qps field.
| Returns | |
|---|---|
| Type | Description |
int|string | |
setNodeCount
Output only. The number of nodes this model is deployed on. A node is an abstraction of a machine resource, which can handle online prediction QPS as given in the node_qps field.
| Parameter | |
|---|---|
| Name | Description |
var |
int|string
|
| Returns | |
|---|---|
| Type | Description |
$this | |