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Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class PredictionServiceClient.
Service Description: A service for online predictions and explanations.
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 PredictionServiceClient();
try {
$formattedEndpoint = $predictionServiceClient->endpointName('[PROJECT]', '[LOCATION]', '[ENDPOINT]');
$instances = [];
$response = $predictionServiceClient->explain($formattedEndpoint, $instances);
} 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.
Methods
endpointName
Formats a string containing the fully-qualified path to represent a endpoint resource.
project
string
location
string
endpoint
string
string
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
- endpoint: projects/{project}/locations/{location}/endpoints/{endpoint}
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.
formattedName
string
The formatted name string
template
string
Optional name of template to match
array
__construct
Constructor.
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 {@see} object or {@see} 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 {@see} .
↳ 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 {@see} 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 {@see} and {@see} 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.
explain
Perform an online explanation.
If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have explanation_spec populated. Only deployed AutoML tabular Models have explanation_spec.
Sample code:
$predictionServiceClient = new PredictionServiceClient();
try {
$formattedEndpoint = $predictionServiceClient->endpointName('[PROJECT]', '[LOCATION]', '[ENDPOINT]');
$instances = [];
$response = $predictionServiceClient->explain($formattedEndpoint, $instances);
} finally {
$predictionServiceClient->close();
}
endpoint
string
Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint}
instances
array<Google\Protobuf\Value>
Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri .
optionalArgs
array
Optional.
↳ parameters
Value
The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri .
↳ explanationSpecOverride
ExplanationSpecOverride
If specified, overrides the explanation_spec of the DeployedModel. Can be used for explaining prediction results with different configurations, such as: - Explaining top-5 predictions results as opposed to top-1; - Increasing path count or step count of the attribution methods to reduce approximate errors; - Using different baselines for explaining the prediction results.
↳ deployedModelId
string
If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split .
↳ retrySettings
RetrySettings|array
Retry settings to use for this call. Can be a {@see} object, or an associative array of retry settings parameters. See the documentation on {@see} for example usage.
predict
Perform an online prediction.
Sample code:
$predictionServiceClient = new PredictionServiceClient();
try {
$formattedEndpoint = $predictionServiceClient->endpointName('[PROJECT]', '[LOCATION]', '[ENDPOINT]');
$instances = [];
$response = $predictionServiceClient->predict($formattedEndpoint, $instances);
} finally {
$predictionServiceClient->close();
}
endpoint
string
Required. The name of the Endpoint requested to serve the prediction. Format: projects/{project}/locations/{location}/endpoints/{endpoint}
instances
array<Google\Protobuf\Value>
Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri .
optionalArgs
array
Optional.
↳ parameters
Value
The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri .
↳ retrySettings
RetrySettings|array
Retry settings to use for this call. Can be a {@see} object, or an associative array of retry settings parameters. See the documentation on {@see} for example usage.
rawPredict
Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
-
X-Vertex-AI-Endpoint-Id: ID of the Endpoint that served this prediction. -
X-Vertex-AI-Deployed-Model-Id: ID of the Endpoint's DeployedModel that served this prediction.
Sample code:
$predictionServiceClient = new PredictionServiceClient();
try {
$formattedEndpoint = $predictionServiceClient->endpointName('[PROJECT]', '[LOCATION]', '[ENDPOINT]');
$response = $predictionServiceClient->rawPredict($formattedEndpoint);
} finally {
$predictionServiceClient->close();
}
endpoint
string
Required. The name of the Endpoint requested to serve the prediction. Format: projects/{project}/locations/{location}/endpoints/{endpoint}
optionalArgs
array
Optional.
↳ httpBody
HttpBody
The prediction input. Supports HTTP headers and arbitrary data payload. A DeployedModel
may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the RawPredict
method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the predict_schemata.instance_schema_uri
field when you create a Model
. This schema applies when you deploy the Model
as a DeployedModel
to an Endpoint
and use the RawPredict
method.
↳ retrySettings
RetrySettings|array
Retry settings to use for this call. Can be a {@see} object, or an associative array of retry settings parameters. See the documentation on {@see} for example usage.
getLocation
Gets information about a location.
Sample code:
$predictionServiceClient = new PredictionServiceClient();
try {
$response = $predictionServiceClient->getLocation();
} finally {
$predictionServiceClient->close();
}
optionalArgs
array
Optional.
↳ name
string
Resource name for the location.
↳ retrySettings
RetrySettings|array
Retry settings to use for this call. Can be a {@see} object, or an associative array of retry settings parameters. See the documentation on {@see} for example usage.
listLocations
Lists information about the supported locations for this service.
Sample code:
$predictionServiceClient = new PredictionServiceClient();
try {
// Iterate over pages of elements
$pagedResponse = $predictionServiceClient->listLocations();
foreach ($pagedResponse->iteratePages() as $page) {
foreach ($page as $element) {
// doSomethingWith($element);
}
}
// Alternatively:
// Iterate through all elements
$pagedResponse = $predictionServiceClient->listLocations();
foreach ($pagedResponse->iterateAllElements() as $element) {
// doSomethingWith($element);
}
} finally {
$predictionServiceClient->close();
}
optionalArgs
array
Optional.
↳ name
string
The resource that owns the locations collection, if applicable.
↳ filter
string
The standard list filter.
↳ pageSize
int
The maximum number of resources contained in the underlying API response. The API may return fewer values in a page, even if there are additional values to be retrieved.
↳ pageToken
string
A page token is used to specify a page of values to be returned. If no page token is specified (the default), the first page of values will be returned. Any page token used here must have been generated by a previous call to the API.
↳ retrySettings
RetrySettings|array
Retry settings to use for this call. Can be a {@see} object, or an associative array of retry settings parameters. See the documentation on {@see} for example usage.
getIamPolicy
Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
Sample code:
$predictionServiceClient = new PredictionServiceClient();
try {
$resource = 'resource';
$response = $predictionServiceClient->getIamPolicy($resource);
} finally {
$predictionServiceClient->close();
}
resource
string
REQUIRED: The resource for which the policy is being requested. See the operation documentation for the appropriate value for this field.
optionalArgs
array
Optional.
↳ options
GetPolicyOptions
OPTIONAL: A GetPolicyOptions
object for specifying options to GetIamPolicy
.
↳ retrySettings
RetrySettings|array
Retry settings to use for this call. Can be a {@see} object, or an associative array of retry settings parameters. See the documentation on {@see} for example usage.
setIamPolicy
Sets the access control policy on the specified resource. Replaces any existing policy.
Can return NOT_FOUND
, INVALID_ARGUMENT
, and PERMISSION_DENIED
errors.
Sample code:
$predictionServiceClient = new PredictionServiceClient();
try {
$resource = 'resource';
$policy = new Policy();
$response = $predictionServiceClient->setIamPolicy($resource, $policy);
} finally {
$predictionServiceClient->close();
}
resource
string
REQUIRED: The resource for which the policy is being specified. See the operation documentation for the appropriate value for this field.
policy
Google\Cloud\Iam\V1\Policy
REQUIRED: The complete policy to be applied to the resource
. The size of the policy is limited to a few 10s of KB. An empty policy is a valid policy but certain Cloud Platform services (such as Projects) might reject them.
optionalArgs
array
Optional.
↳ updateMask
FieldMask
OPTIONAL: A FieldMask specifying which fields of the policy to modify. Only the fields in the mask will be modified. If no mask is provided, the following default mask is used: paths: "bindings, etag"
↳ retrySettings
RetrySettings|array
Retry settings to use for this call. Can be a {@see} object, or an associative array of retry settings parameters. See the documentation on {@see} for example usage.
testIamPermissions
Returns permissions that a caller has on the specified resource. If the
resource does not exist, this will return an empty set of
permissions, not a NOT_FOUND
error.
Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.
Sample code:
$predictionServiceClient = new PredictionServiceClient();
try {
$resource = 'resource';
$permissions = [];
$response = $predictionServiceClient->testIamPermissions($resource, $permissions);
} finally {
$predictionServiceClient->close();
}
resource
string
REQUIRED: The resource for which the policy detail is being requested. See the operation documentation for the appropriate value for this field.
permissions
string[]
The set of permissions to check for the resource
. Permissions with wildcards (such as ' ' or 'storage.
') are not allowed. For more information see IAM Overview
.
optionalArgs
array
Optional.
↳ retrySettings
RetrySettings|array
Retry settings to use for this call. Can be a {@see} object, or an associative array of retry settings parameters. See the documentation on {@see} for example usage.
Constants
SERVICE_NAME
Value: 'google.cloud.aiplatform.v1.PredictionService'
The name of the service.
SERVICE_ADDRESS
Value: 'aiplatform.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.
