Cloud AutoML V1 Client - Class PredictionServiceClient (1.5.4)

Reference documentation and code samples for the Cloud AutoML V1 Client class PredictionServiceClient.

Service Description: AutoML Prediction API.

On any input that is documented to expect a string parameter in snake_case or dash-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\V1\PredictionServiceClient();
try {
    $formattedName = $predictionServiceClient->modelName('[PROJECT]', '[LOCATION]', '[MODEL]');
    $inputConfig = new Google\Cloud\AutoMl\V1\BatchPredictInputConfig();
    $outputConfig = new Google\Cloud\AutoMl\V1\BatchPredictOutputConfig();
    $operationResponse = $predictionServiceClient->batchPredict($formattedName, $inputConfig, $outputConfig);
    $operationResponse->pollUntilComplete();
    if ($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);
    $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.

This service has a new (beta) implementation. See Google\Cloud\AutoMl\V1\Client\PredictionServiceClient to use the new surface.

Namespace

Google \ Cloud \ AutoMl \ V1

Methods

__construct

Constructor.

Parameters
NameDescription
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 scenarios:

  • AutoML Vision Classification
  • AutoML Vision Object Detection
  • AutoML Video Intelligence Classification
  • AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification
  • AutoML Natural Language Entity Extraction
  • AutoML Natural Language Sentiment Analysis
  • AutoML Tables
Parameters
NameDescription
name string

Required. Name of the model requested to serve the batch prediction.

inputConfig Google\Cloud\AutoMl\V1\BatchPredictInputConfig

Required. The input configuration for batch prediction.

outputConfig Google\Cloud\AutoMl\V1\BatchPredictOutputConfig

Required. The Configuration specifying where output predictions should be written.

optionalArgs array

Optional.

↳ params array

Additional domain-specific parameters for the predictions, any string must be up to 25000 characters long. AutoML Natural Language 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. AutoML Vision 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. AutoML Vision 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) The maximum number of bounding boxes returned per image. The default is 100, the number of bounding boxes returned might be limited by the server. AutoML Video Intelligence 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. The default is false. 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. 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. The default is false. 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. AutoML Video Intelligence 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) The maximum number of bounding boxes returned per image. The default is 100, the number of bounding boxes returned might be limited by the server. min_bounding_box_size : (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size are returned. Value in 0 to 1 range. Default is 0.

↳ 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
TypeDescription
Google\ApiCore\OperationResponse
Example
use Google\ApiCore\ApiException;
use Google\ApiCore\OperationResponse;
use Google\Cloud\AutoMl\V1\BatchPredictInputConfig;
use Google\Cloud\AutoMl\V1\BatchPredictOutputConfig;
use Google\Cloud\AutoMl\V1\BatchPredictResult;
use Google\Cloud\AutoMl\V1\GcsDestination;
use Google\Cloud\AutoMl\V1\GcsSource;
use Google\Cloud\AutoMl\V1\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.
 * @param string $inputConfigGcsSourceInputUrisElement      Google Cloud Storage URIs to input files, up to 2000
 *                                                          characters long. Accepted forms:
 *                                                          * Full object path, e.g. gs://bucket/directory/object.csv
 * @param string $outputConfigGcsDestinationOutputUriPrefix Google Cloud Storage URI to output directory, up to 2000
 *                                                          characters long.
 *                                                          Accepted forms:
 *                                                          * Prefix path: gs://bucket/directory
 *                                                          The requesting user must have write permission to the bucket.
 *                                                          The directory is created if it doesn't exist.
 */
function batch_predict_sample(
    string $formattedName,
    string $inputConfigGcsSourceInputUrisElement,
    string $outputConfigGcsDestinationOutputUriPrefix
): void {
    // Create a client.
    $predictionServiceClient = new PredictionServiceClient();

    // Prepare any non-scalar elements to be passed along with the request.
    $inputConfigGcsSourceInputUris = [$inputConfigGcsSourceInputUrisElement,];
    $inputConfigGcsSource = (new GcsSource())
        ->setInputUris($inputConfigGcsSourceInputUris);
    $inputConfig = (new BatchPredictInputConfig())
        ->setGcsSource($inputConfigGcsSource);
    $outputConfigGcsDestination = (new GcsDestination())
        ->setOutputUriPrefix($outputConfigGcsDestinationOutputUriPrefix);
    $outputConfig = (new BatchPredictOutputConfig())
        ->setGcsDestination($outputConfigGcsDestination);

    // Call the API and handle any network failures.
    try {
        /** @var OperationResponse $response */
        $response = $predictionServiceClient->batchPredict($formattedName, $inputConfig, $outputConfig);
        $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]');
    $inputConfigGcsSourceInputUrisElement = '[INPUT_URIS]';
    $outputConfigGcsDestinationOutputUriPrefix = '[OUTPUT_URI_PREFIX]';

    batch_predict_sample(
        $formattedName,
        $inputConfigGcsSourceInputUrisElement,
        $outputConfigGcsDestinationOutputUriPrefix
    );
}

predict

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

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

AutoML Vision Classification

  • An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.

AutoML Vision Object Detection

  • An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.

AutoML Natural Language Classification

  • A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB.

AutoML Natural Language Entity Extraction

  • A TextSnippet up to 10,000 characters, UTF-8 NFC encoded or a document in .PDF, .TIF or .TIFF format with size upto 20MB.

AutoML Natural Language Sentiment Analysis

  • A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB.

AutoML Translation

  • A TextSnippet up to 25,000 characters, UTF-8 encoded.

AutoML Tables

  • A row with column values matching the columns of the model, up to 5MB. Not available for FORECASTING prediction_type.
Parameters
NameDescription
name string

Required. Name of the model requested to serve the prediction.

payload Google\Cloud\AutoMl\V1\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. AutoML Vision 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. AutoML Vision 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) The maximum number of bounding boxes returned. The default is 100. The number of returned bounding boxes might be limited by the server. AutoML Tables feature_importance : (boolean) Whether feature_importance is populated in the returned list of TablesAnnotation objects. 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
TypeDescription
Google\Cloud\AutoMl\V1\PredictResponse
Example
use Google\ApiCore\ApiException;
use Google\Cloud\AutoMl\V1\ExamplePayload;
use Google\Cloud\AutoMl\V1\PredictResponse;
use Google\Cloud\AutoMl\V1\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
TypeDescription
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
NameDescription
operationName string

The name of the long running operation

methodName string

The name of the method used to start the operation

Returns
TypeDescription
Google\ApiCore\OperationResponse

static::modelName

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

Parameters
NameDescription
project string
location string
model string
Returns
TypeDescription
stringThe 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
NameDescription
formattedName string

The formatted name string

template string

Optional name of template to match

Returns
TypeDescription
arrayAn associative array from name component IDs to component values.

Constants

SERVICE_NAME

Value: 'google.cloud.automl.v1.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.