Cloud AutoML V1beta1 Client - Class PredictionServiceClient (1.6.4)

Reference documentation and code samples for the Cloud AutoML V1beta1 Client class PredictionServiceClient.

Service Description: AutoML Prediction API.

On any input that is documented to expect a string parameter in snake_case or kebab-case, either of those cases is accepted.

This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:

$predictionServiceClient = new Google\Cloud\AutoMl\V1beta1\PredictionServiceClient();
try {
    $formattedName = $predictionServiceClient->modelName('[PROJECT]', '[LOCATION]', '[MODEL]');
    $inputConfig = new Google\Cloud\AutoMl\V1beta1\BatchPredictInputConfig();
    $outputConfig = new Google\Cloud\AutoMl\V1beta1\BatchPredictOutputConfig();
    $params = [];
    $operationResponse = $predictionServiceClient->batchPredict($formattedName, $inputConfig, $outputConfig, $params);
    $operationResponse->pollUntilComplete();
    if ($operationResponse->operationSucceeded()) {
        $result = $operationResponse->getResult();
        // doSomethingWith($result)
    } else {
        $error = $operationResponse->getError();
        // handleError($error)
    }
    // Alternatively:
    // start the operation, keep the operation name, and resume later
    $operationResponse = $predictionServiceClient->batchPredict($formattedName, $inputConfig, $outputConfig, $params);
    $operationName = $operationResponse->getName();
    // ... do other work
    $newOperationResponse = $predictionServiceClient->resumeOperation($operationName, 'batchPredict');
    while (!$newOperationResponse->isDone()) {
        // ... do other work
        $newOperationResponse->reload();
    }
    if ($newOperationResponse->operationSucceeded()) {
        $result = $newOperationResponse->getResult();
        // doSomethingWith($result)
    } else {
        $error = $newOperationResponse->getError();
        // handleError($error)
    }
} finally {
    $predictionServiceClient->close();
}

Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parseName method to extract the individual identifiers contained within formatted names that are returned by the API.

Namespace

Google \ Cloud \ AutoMl \ V1beta1

Methods

__construct

Constructor.

Parameters
Name	Description
`options`	`array` Optional. Options for configuring the service API wrapper.
`↳ apiEndpoint`	`string` The address of the API remote host. May optionally include the port, formatted as "
`↳ credentials`	`string\|array\|FetchAuthTokenInterface\|CredentialsWrapper` The credentials to be used by the client to authorize API calls. This option accepts either a path to a credentials file, or a decoded credentials file as a PHP array. Advanced usage: In addition, this option can also accept a pre-constructed Google\Auth\FetchAuthTokenInterface object or Google\ApiCore\CredentialsWrapper object. Note that when one of these objects are provided, any settings in $credentialsConfig will be ignored.
`↳ credentialsConfig`	`array` Options used to configure credentials, including auth token caching, for the client. For a full list of supporting configuration options, see Google\ApiCore\CredentialsWrapper::build() .
`↳ disableRetries`	`bool` Determines whether or not retries defined by the client configuration should be disabled. Defaults to `false`.
`↳ clientConfig`	`string\|array` Client method configuration, including retry settings. This option can be either a path to a JSON file, or a PHP array containing the decoded JSON data. By default this settings points to the default client config file, which is provided in the resources folder.
`↳ transport`	`string\|TransportInterface` The transport used for executing network requests. May be either the string `rest` or `grpc`. Defaults to `grpc` if gRPC support is detected on the system. Advanced usage: Additionally, it is possible to pass in an already instantiated Google\ApiCore\Transport\TransportInterface object. Note that when this object is provided, any settings in $transportConfig, and any $apiEndpoint setting, will be ignored.
`↳ transportConfig`	`array` Configuration options that will be used to construct the transport. Options for each supported transport type should be passed in a key for that transport. For example: $transportConfig = [ 'grpc' => [...], 'rest' => [...], ]; See the Google\ApiCore\Transport\GrpcTransport::build() and Google\ApiCore\Transport\RestTransport::build() methods for the supported options.
`↳ clientCertSource`	`callable` A callable which returns the client cert as a string. This can be used to provide a certificate and private key to the transport layer for mTLS.

batchPredict

Perform a batch prediction. Unlike the online Predict, batch prediction result won't be immediately available in the response. Instead, a long running operation object is returned. User can poll the operation result via GetOperation method. Once the operation is done, BatchPredictResult is returned in the response field.

Available for following ML problems:

Image Classification
Image Object Detection
Video Classification
Video Object Tracking * Text Extraction
Tables

Parameters
Name	Description
`name`	`string` Required. Name of the model requested to serve the batch prediction.
`inputConfig`	`Google\Cloud\AutoMl\V1beta1\BatchPredictInputConfig` Required. The input configuration for batch prediction.
`outputConfig`	`Google\Cloud\AutoMl\V1beta1\BatchPredictOutputConfig` Required. The Configuration specifying where output predictions should be written.
`params`	`array` Required. Additional domain-specific parameters for the predictions, any string must be up to 25000 characters long. For Text Classification: `score_threshold` - (float) A value from 0.0 to 1.0. When the model makes predictions for a text snippet, it will only produce results that have at least this confidence score. The default is 0.5. For Image Classification: `score_threshold` - (float) A value from 0.0 to 1.0. When the model makes predictions for an image, it will only produce results that have at least this confidence score. The default is 0.5. For Image Object Detection: `score_threshold` - (float) When Model detects objects on the image, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. `max_bounding_box_count` - (int64) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server. For Video Classification : `score_threshold` - (float) A value from 0.0 to 1.0. When the model makes predictions for a video, it will only produce results that have at least this confidence score. The default is 0.5. `segment_classification` - (boolean) Set to true to request segment-level classification. AutoML Video Intelligence returns labels and their confidence scores for the entire segment of the video that user specified in the request configuration. The default is "true". `shot_classification` - (boolean) Set to true to request shot-level classification. AutoML Video Intelligence determines the boundaries for each camera shot in the entire segment of the video that user specified in the request configuration. AutoML Video Intelligence then returns labels and their confidence scores for each detected shot, along with the start and end time of the shot. WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality. The default is "false". `1s_interval_classification` - (boolean) Set to true to request classification for a video at one-second intervals. AutoML Video Intelligence returns labels and their confidence scores for each second of the entire segment of the video that user specified in the request configuration. WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality. The default is "false". For Tables: feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false. For Video Object Tracking: `score_threshold` - (float) When Model detects objects on video frames, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. `max_bounding_box_count` - (int64) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. `min_bounding_box_size` - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.
`optionalArgs`	`array` Optional.
`↳ retrySettings`	`RetrySettings\|array` Retry settings to use for this call. Can be a Google\ApiCore\RetrySettings object, or an associative array of retry settings parameters. See the documentation on Google\ApiCore\RetrySettings for example usage.

Returns
Type	Description
`Google\ApiCore\OperationResponse`

Example

use Google\ApiCore\ApiException;
use Google\ApiCore\OperationResponse;
use Google\Cloud\AutoMl\V1beta1\BatchPredictInputConfig;
use Google\Cloud\AutoMl\V1beta1\BatchPredictOutputConfig;
use Google\Cloud\AutoMl\V1beta1\BatchPredictResult;
use Google\Cloud\AutoMl\V1beta1\PredictionServiceClient;
use Google\Rpc\Status;

/**
 * @param string $formattedName Name of the model requested to serve the batch prediction. Please see
 *                              {@see PredictionServiceClient::modelName()} for help formatting this field.
 */
function batch_predict_sample(string $formattedName): void
{
    // Create a client.
    $predictionServiceClient = new PredictionServiceClient();

    // Prepare any non-scalar elements to be passed along with the request.
    $inputConfig = new BatchPredictInputConfig();
    $outputConfig = new BatchPredictOutputConfig();
    $params = [];

    // Call the API and handle any network failures.
    try {
        /** @var OperationResponse $response */
        $response = $predictionServiceClient->batchPredict(
            $formattedName,
            $inputConfig,
            $outputConfig,
            $params
        );
        $response->pollUntilComplete();

        if ($response->operationSucceeded()) {
            /** @var BatchPredictResult $result */
            $result = $response->getResult();
            printf('Operation successful with response data: %s' . PHP_EOL, $result->serializeToJsonString());
        } else {
            /** @var Status $error */
            $error = $response->getError();
            printf('Operation failed with error data: %s' . PHP_EOL, $error->serializeToJsonString());
        }
    } catch (ApiException $ex) {
        printf('Call failed with message: %s' . PHP_EOL, $ex->getMessage());
    }
}

/**
 * Helper to execute the sample.
 *
 * This sample has been automatically generated and should be regarded as a code
 * template only. It will require modifications to work:
 *  - It may require correct/in-range values for request initialization.
 *  - It may require specifying regional endpoints when creating the service client,
 *    please see the apiEndpoint client configuration option for more details.
 */
function callSample(): void
{
    $formattedName = PredictionServiceClient::modelName('[PROJECT]', '[LOCATION]', '[MODEL]');

    batch_predict_sample($formattedName);
}

predict

Perform an online prediction. The prediction result will be directly returned in the response.

Available for following ML problems, and their expected request payloads:

Image Classification - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
Image Object Detection - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
Text Classification - TextSnippet, content up to 60,000 characters, UTF-8 encoded.
Text Extraction - TextSnippet, content up to 30,000 characters, UTF-8 NFC encoded.
Translation - TextSnippet, content up to 25,000 characters, UTF-8 encoded.
Tables - Row, with column values matching the columns of the model, up to 5MB. Not available for FORECASTING

prediction_type.

Text Sentiment - TextSnippet, content up 500 characters, UTF-8 encoded.

Parameters
Name	Description
`name`	`string` Required. Name of the model requested to serve the prediction.
`payload`	`Google\Cloud\AutoMl\V1beta1\ExamplePayload` Required. Payload to perform a prediction on. The payload must match the problem type that the model was trained to solve.
`optionalArgs`	`array` Optional.
`↳ params`	`array` Additional domain-specific parameters, any string must be up to 25000 characters long. * For Image Classification: `score_threshold` - (float) A value from 0.0 to 1.0. When the model makes predictions for an image, it will only produce results that have at least this confidence score. The default is 0.5. * For Image Object Detection: `score_threshold` - (float) When Model detects objects on the image, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. `max_bounding_box_count` - (int64) No more than this number of bounding boxes will be returned in the response. Default is 100, the requested value may be limited by server. * For Tables: feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotation. The default is false.
`↳ retrySettings`	`RetrySettings\|array` Retry settings to use for this call. Can be a Google\ApiCore\RetrySettings object, or an associative array of retry settings parameters. See the documentation on Google\ApiCore\RetrySettings for example usage.

Returns
Type	Description
`Google\Cloud\AutoMl\V1beta1\PredictResponse`

Example

use Google\ApiCore\ApiException;
use Google\Cloud\AutoMl\V1beta1\ExamplePayload;
use Google\Cloud\AutoMl\V1beta1\PredictResponse;
use Google\Cloud\AutoMl\V1beta1\PredictionServiceClient;

/**
 * @param string $formattedName Name of the model requested to serve the prediction. Please see
 *                              {@see PredictionServiceClient::modelName()} for help formatting this field.
 */
function predict_sample(string $formattedName): void
{
    // Create a client.
    $predictionServiceClient = new PredictionServiceClient();

    // Prepare any non-scalar elements to be passed along with the request.
    $payload = new ExamplePayload();

    // Call the API and handle any network failures.
    try {
        /** @var PredictResponse $response */
        $response = $predictionServiceClient->predict($formattedName, $payload);
        printf('Response data: %s' . PHP_EOL, $response->serializeToJsonString());
    } catch (ApiException $ex) {
        printf('Call failed with message: %s' . PHP_EOL, $ex->getMessage());
    }
}

/**
 * Helper to execute the sample.
 *
 * This sample has been automatically generated and should be regarded as a code
 * template only. It will require modifications to work:
 *  - It may require correct/in-range values for request initialization.
 *  - It may require specifying regional endpoints when creating the service client,
 *    please see the apiEndpoint client configuration option for more details.
 */
function callSample(): void
{
    $formattedName = PredictionServiceClient::modelName('[PROJECT]', '[LOCATION]', '[MODEL]');

    predict_sample($formattedName);
}

getOperationsClient

Return an OperationsClient object with the same endpoint as $this.

Returns
Type	Description
`Google\ApiCore\LongRunning\OperationsClient`

resumeOperation

Resume an existing long running operation that was previously started by a long running API method. If $methodName is not provided, or does not match a long running API method, then the operation can still be resumed, but the OperationResponse object will not deserialize the final response.

Parameters
Name	Description
`operationName`	`string` The name of the long running operation
`methodName`	`string` The name of the method used to start the operation

Returns
Type	Description
`Google\ApiCore\OperationResponse`

static::modelName

Formats a string containing the fully-qualified path to represent a model resource.

Parameters
Name	Description
`project`	`string`
`location`	`string`
`model`	`string`

Returns
Type	Description
`string`	The formatted model resource.

static::parseName

Parses a formatted name string and returns an associative array of the components in the name.

The following name formats are supported: Template: Pattern

model: projects/{project}/locations/{location}/models/{model}

The optional $template argument can be supplied to specify a particular pattern, and must match one of the templates listed above. If no $template argument is provided, or if the $template argument does not match one of the templates listed, then parseName will check each of the supported templates, and return the first match.

Parameters
Name	Description
`formattedName`	`string` The formatted name string
`template`	`string` Optional name of template to match

Returns
Type	Description
`array`	An associative array from name component IDs to component values.

Constants

SERVICE_NAME

Value: 'google.cloud.automl.v1beta1.PredictionService'

The name of the service.

SERVICE_ADDRESS

Value: 'automl.googleapis.com'

The default address of the service.

DEFAULT_SERVICE_PORT

Value: 443

The default port of the service.

CODEGEN_NAME

Value: 'gapic'

The name of the code generator, to be included in the agent header.