<?php
# Generated by the protocol buffer compiler.  DO NOT EDIT!
# source: google/cloud/automl/v1beta1/prediction_service.proto

namespace Google\Cloud\AutoMl\V1beta1;

use Google\Protobuf\Internal\GPBType;
use Google\Protobuf\Internal\RepeatedField;
use Google\Protobuf\Internal\GPBUtil;

/**
 * Request message for
 * [PredictionService.BatchPredict][google.cloud.automl.v1beta1.PredictionService.BatchPredict].
 *
 * Generated from protobuf message <code>google.cloud.automl.v1beta1.BatchPredictRequest</code>
 */
class BatchPredictRequest extends \Google\Protobuf\Internal\Message
{
    /**
     * Name of the model requested to serve the batch prediction.
     *
     * Generated from protobuf field <code>string name = 1;</code>
     */
    private $name = '';
    /**
     * Required. The input configuration for batch prediction.
     *
     * Generated from protobuf field <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
     */
    private $input_config = null;
    /**
     * Required. The Configuration specifying where output predictions should
     * be written.
     *
     * Generated from protobuf field <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
     */
    private $output_config = null;
    /**
     * 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 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.
     *
     * Generated from protobuf field <code>map<string, string> params = 5;</code>
     */
    private $params;

    /**
     * Constructor.
     *
     * @param array $data {
     *     Optional. Data for populating the Message object.
     *
     *     @type string $name
     *           Name of the model requested to serve the batch prediction.
     *     @type \Google\Cloud\AutoMl\V1beta1\BatchPredictInputConfig $input_config
     *           Required. The input configuration for batch prediction.
     *     @type \Google\Cloud\AutoMl\V1beta1\BatchPredictOutputConfig $output_config
     *           Required. The Configuration specifying where output predictions should
     *           be written.
     *     @type array|\Google\Protobuf\Internal\MapField $params
     *           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 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.
     * }
     */
    public function __construct($data = NULL) {
        \GPBMetadata\Google\Cloud\Automl\V1Beta1\PredictionService::initOnce();
        parent::__construct($data);
    }

    /**
     * Name of the model requested to serve the batch prediction.
     *
     * Generated from protobuf field <code>string name = 1;</code>
     * @return string
     */
    public function getName()
    {
        return $this->name;
    }

    /**
     * Name of the model requested to serve the batch prediction.
     *
     * Generated from protobuf field <code>string name = 1;</code>
     * @param string $var
     * @return $this
     */
    public function setName($var)
    {
        GPBUtil::checkString($var, True);
        $this->name = $var;

        return $this;
    }

    /**
     * Required. The input configuration for batch prediction.
     *
     * Generated from protobuf field <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
     * @return \Google\Cloud\AutoMl\V1beta1\BatchPredictInputConfig
     */
    public function getInputConfig()
    {
        return $this->input_config;
    }

    /**
     * Required. The input configuration for batch prediction.
     *
     * Generated from protobuf field <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
     * @param \Google\Cloud\AutoMl\V1beta1\BatchPredictInputConfig $var
     * @return $this
     */
    public function setInputConfig($var)
    {
        GPBUtil::checkMessage($var, \Google\Cloud\AutoMl\V1beta1\BatchPredictInputConfig::class);
        $this->input_config = $var;

        return $this;
    }

    /**
     * Required. The Configuration specifying where output predictions should
     * be written.
     *
     * Generated from protobuf field <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
     * @return \Google\Cloud\AutoMl\V1beta1\BatchPredictOutputConfig
     */
    public function getOutputConfig()
    {
        return $this->output_config;
    }

    /**
     * Required. The Configuration specifying where output predictions should
     * be written.
     *
     * Generated from protobuf field <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
     * @param \Google\Cloud\AutoMl\V1beta1\BatchPredictOutputConfig $var
     * @return $this
     */
    public function setOutputConfig($var)
    {
        GPBUtil::checkMessage($var, \Google\Cloud\AutoMl\V1beta1\BatchPredictOutputConfig::class);
        $this->output_config = $var;

        return $this;
    }

    /**
     * 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 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.
     *
     * Generated from protobuf field <code>map<string, string> params = 5;</code>
     * @return \Google\Protobuf\Internal\MapField
     */
    public function getParams()
    {
        return $this->params;
    }

    /**
     * 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 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.
     *
     * Generated from protobuf field <code>map<string, string> params = 5;</code>
     * @param array|\Google\Protobuf\Internal\MapField $var
     * @return $this
     */
    public function setParams($var)
    {
        $arr = GPBUtil::checkMapField($var, \Google\Protobuf\Internal\GPBType::STRING, \Google\Protobuf\Internal\GPBType::STRING);
        $this->params = $arr;

        return $this;
    }

}

