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

package com.google.cloud.automl.v1beta1;

/**
 *
 *
 * <pre>
 * Request message for [PredictionService.BatchPredict][google.cloud.automl.v1beta1.PredictionService.BatchPredict].
 * </pre>
 *
 * Protobuf type {@code google.cloud.automl.v1beta1.BatchPredictRequest}
 */
public final class BatchPredictRequest extends com.google.protobuf.GeneratedMessageV3
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  /**
   *
   *
   * <pre>
   * Name of the model requested to serve the batch prediction.
   * </pre>
   *
   * <code>string name = 1;</code>
   */
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   *
   *
   * <pre>
   * Name of the model requested to serve the batch prediction.
   * </pre>
   *
   * <code>string name = 1;</code>
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  public static final int INPUT_CONFIG_FIELD_NUMBER = 3;
  private com.google.cloud.automl.v1beta1.BatchPredictInputConfig inputConfig_;
  /**
   *
   *
   * <pre>
   * Required. The input configuration for batch prediction.
   * </pre>
   *
   * <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
   */
  public boolean hasInputConfig() {
    return inputConfig_ != null;
  }
  /**
   *
   *
   * <pre>
   * Required. The input configuration for batch prediction.
   * </pre>
   *
   * <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
   */
  public com.google.cloud.automl.v1beta1.BatchPredictInputConfig getInputConfig() {
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  }
  /**
   *
   *
   * <pre>
   * Required. The input configuration for batch prediction.
   * </pre>
   *
   * <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
   */
  public com.google.cloud.automl.v1beta1.BatchPredictInputConfigOrBuilder
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  }

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  private com.google.cloud.automl.v1beta1.BatchPredictOutputConfig outputConfig_;
  /**
   *
   *
   * <pre>
   * Required. The Configuration specifying where output predictions should
   * be written.
   * </pre>
   *
   * <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
   */
  public boolean hasOutputConfig() {
    return outputConfig_ != null;
  }
  /**
   *
   *
   * <pre>
   * Required. The Configuration specifying where output predictions should
   * be written.
   * </pre>
   *
   * <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
   */
  public com.google.cloud.automl.v1beta1.BatchPredictOutputConfig getOutputConfig() {
    return outputConfig_ == null
        ? com.google.cloud.automl.v1beta1.BatchPredictOutputConfig.getDefaultInstance()
        : outputConfig_;
  }
  /**
   *
   *
   * <pre>
   * Required. The Configuration specifying where output predictions should
   * be written.
   * </pre>
   *
   * <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
   */
  public com.google.cloud.automl.v1beta1.BatchPredictOutputConfigOrBuilder
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  }

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  }

  public int getParamsCount() {
    return internalGetParams().getMap().size();
  }
  /**
   *
   *
   * <pre>
   * Additional domain-specific parameters for the predictions, any string must
   * be up to 25000 characters long.
   * *  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".
   * </pre>
   *
   * <code>map&lt;string, string&gt; params = 5;</code>
   */
  public boolean containsParams(java.lang.String key) {
    if (key == null) {
      throw new java.lang.NullPointerException();
    }
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  }
  /** Use {@link #getParamsMap()} instead. */
  @java.lang.Deprecated
  public java.util.Map<java.lang.String, java.lang.String> getParams() {
    return getParamsMap();
  }
  /**
   *
   *
   * <pre>
   * Additional domain-specific parameters for the predictions, any string must
   * be up to 25000 characters long.
   * *  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".
   * </pre>
   *
   * <code>map&lt;string, string&gt; params = 5;</code>
   */
  public java.util.Map<java.lang.String, java.lang.String> getParamsMap() {
    return internalGetParams().getMap();
  }
  /**
   *
   *
   * <pre>
   * Additional domain-specific parameters for the predictions, any string must
   * be up to 25000 characters long.
   * *  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".
   * </pre>
   *
   * <code>map&lt;string, string&gt; params = 5;</code>
   */
  public java.lang.String getParamsOrDefault(java.lang.String key, java.lang.String defaultValue) {
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    }
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  }
  /**
   *
   *
   * <pre>
   * Additional domain-specific parameters for the predictions, any string must
   * be up to 25000 characters long.
   * *  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".
   * </pre>
   *
   * <code>map&lt;string, string&gt; params = 5;</code>
   */
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  /**
   *
   *
   * <pre>
   * Request message for [PredictionService.BatchPredict][google.cloud.automl.v1beta1.PredictionService.BatchPredict].
   * </pre>
   *
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    /**
     *
     *
     * <pre>
     * Name of the model requested to serve the batch prediction.
     * </pre>
     *
     * <code>string name = 1;</code>
     */
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    /**
     *
     *
     * <pre>
     * Name of the model requested to serve the batch prediction.
     * </pre>
     *
     * <code>string name = 1;</code>
     */
    public com.google.protobuf.ByteString getNameBytes() {
      java.lang.Object ref = name_;
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        return (com.google.protobuf.ByteString) ref;
      }
    }
    /**
     *
     *
     * <pre>
     * Name of the model requested to serve the batch prediction.
     * </pre>
     *
     * <code>string name = 1;</code>
     */
    public Builder setName(java.lang.String value) {
      if (value == null) {
        throw new NullPointerException();
      }

      name_ = value;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Name of the model requested to serve the batch prediction.
     * </pre>
     *
     * <code>string name = 1;</code>
     */
    public Builder clearName() {

      name_ = getDefaultInstance().getName();
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      return this;
    }
    /**
     *
     *
     * <pre>
     * Name of the model requested to serve the batch prediction.
     * </pre>
     *
     * <code>string name = 1;</code>
     */
    public Builder setNameBytes(com.google.protobuf.ByteString value) {
      if (value == null) {
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      checkByteStringIsUtf8(value);

      name_ = value;
      onChanged();
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    }

    private com.google.cloud.automl.v1beta1.BatchPredictInputConfig inputConfig_;
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    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
     */
    public boolean hasInputConfig() {
      return inputConfigBuilder_ != null || inputConfig_ != null;
    }
    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
     */
    public com.google.cloud.automl.v1beta1.BatchPredictInputConfig getInputConfig() {
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        return inputConfigBuilder_.getMessage();
      }
    }
    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
     */
    public Builder setInputConfig(com.google.cloud.automl.v1beta1.BatchPredictInputConfig value) {
      if (inputConfigBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        inputConfig_ = value;
        onChanged();
      } else {
        inputConfigBuilder_.setMessage(value);
      }

      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
     */
    public Builder setInputConfig(
        com.google.cloud.automl.v1beta1.BatchPredictInputConfig.Builder builderForValue) {
      if (inputConfigBuilder_ == null) {
        inputConfig_ = builderForValue.build();
        onChanged();
      } else {
        inputConfigBuilder_.setMessage(builderForValue.build());
      }

      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
     */
    public Builder mergeInputConfig(com.google.cloud.automl.v1beta1.BatchPredictInputConfig value) {
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        if (inputConfig_ != null) {
          inputConfig_ =
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                  .mergeFrom(value)
                  .buildPartial();
        } else {
          inputConfig_ = value;
        }
        onChanged();
      } else {
        inputConfigBuilder_.mergeFrom(value);
      }

      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
     */
    public Builder clearInputConfig() {
      if (inputConfigBuilder_ == null) {
        inputConfig_ = null;
        onChanged();
      } else {
        inputConfig_ = null;
        inputConfigBuilder_ = null;
      }

      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
     */
    public com.google.cloud.automl.v1beta1.BatchPredictInputConfig.Builder getInputConfigBuilder() {

      onChanged();
      return getInputConfigFieldBuilder().getBuilder();
    }
    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
     */
    public com.google.cloud.automl.v1beta1.BatchPredictInputConfigOrBuilder
        getInputConfigOrBuilder() {
      if (inputConfigBuilder_ != null) {
        return inputConfigBuilder_.getMessageOrBuilder();
      } else {
        return inputConfig_ == null
            ? com.google.cloud.automl.v1beta1.BatchPredictInputConfig.getDefaultInstance()
            : inputConfig_;
      }
    }
    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3;</code>
     */
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.automl.v1beta1.BatchPredictInputConfig,
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                getInputConfig(), getParentForChildren(), isClean());
        inputConfig_ = null;
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    }

    private com.google.cloud.automl.v1beta1.BatchPredictOutputConfig outputConfig_;
    private com.google.protobuf.SingleFieldBuilderV3<
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        outputConfigBuilder_;
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
     */
    public boolean hasOutputConfig() {
      return outputConfigBuilder_ != null || outputConfig_ != null;
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
     */
    public com.google.cloud.automl.v1beta1.BatchPredictOutputConfig getOutputConfig() {
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            ? com.google.cloud.automl.v1beta1.BatchPredictOutputConfig.getDefaultInstance()
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      } else {
        return outputConfigBuilder_.getMessage();
      }
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
     */
    public Builder setOutputConfig(com.google.cloud.automl.v1beta1.BatchPredictOutputConfig value) {
      if (outputConfigBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        outputConfig_ = value;
        onChanged();
      } else {
        outputConfigBuilder_.setMessage(value);
      }

      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
     */
    public Builder setOutputConfig(
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      if (outputConfigBuilder_ == null) {
        outputConfig_ = builderForValue.build();
        onChanged();
      } else {
        outputConfigBuilder_.setMessage(builderForValue.build());
      }

      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
     */
    public Builder mergeOutputConfig(
        com.google.cloud.automl.v1beta1.BatchPredictOutputConfig value) {
      if (outputConfigBuilder_ == null) {
        if (outputConfig_ != null) {
          outputConfig_ =
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                  .mergeFrom(value)
                  .buildPartial();
        } else {
          outputConfig_ = value;
        }
        onChanged();
      } else {
        outputConfigBuilder_.mergeFrom(value);
      }

      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
     */
    public Builder clearOutputConfig() {
      if (outputConfigBuilder_ == null) {
        outputConfig_ = null;
        onChanged();
      } else {
        outputConfig_ = null;
        outputConfigBuilder_ = null;
      }

      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
     */
    public com.google.cloud.automl.v1beta1.BatchPredictOutputConfig.Builder
        getOutputConfigBuilder() {

      onChanged();
      return getOutputConfigFieldBuilder().getBuilder();
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
     */
    public com.google.cloud.automl.v1beta1.BatchPredictOutputConfigOrBuilder
        getOutputConfigOrBuilder() {
      if (outputConfigBuilder_ != null) {
        return outputConfigBuilder_.getMessageOrBuilder();
      } else {
        return outputConfig_ == null
            ? com.google.cloud.automl.v1beta1.BatchPredictOutputConfig.getDefaultInstance()
            : outputConfig_;
      }
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4;</code>
     */
    private com.google.protobuf.SingleFieldBuilderV3<
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        getOutputConfigFieldBuilder() {
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        return com.google.protobuf.MapField.emptyMapField(ParamsDefaultEntryHolder.defaultEntry);
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    private com.google.protobuf.MapField<java.lang.String, java.lang.String>
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      ;
      if (params_ == null) {
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      if (!params_.isMutable()) {
        params_ = params_.copy();
      }
      return params_;
    }

    public int getParamsCount() {
      return internalGetParams().getMap().size();
    }
    /**
     *
     *
     * <pre>
     * Additional domain-specific parameters for the predictions, any string must
     * be up to 25000 characters long.
     * *  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".
     * </pre>
     *
     * <code>map&lt;string, string&gt; params = 5;</code>
     */
    public boolean containsParams(java.lang.String key) {
      if (key == null) {
        throw new java.lang.NullPointerException();
      }
      return internalGetParams().getMap().containsKey(key);
    }
    /** Use {@link #getParamsMap()} instead. */
    @java.lang.Deprecated
    public java.util.Map<java.lang.String, java.lang.String> getParams() {
      return getParamsMap();
    }
    /**
     *
     *
     * <pre>
     * Additional domain-specific parameters for the predictions, any string must
     * be up to 25000 characters long.
     * *  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".
     * </pre>
     *
     * <code>map&lt;string, string&gt; params = 5;</code>
     */
    public java.util.Map<java.lang.String, java.lang.String> getParamsMap() {
      return internalGetParams().getMap();
    }
    /**
     *
     *
     * <pre>
     * Additional domain-specific parameters for the predictions, any string must
     * be up to 25000 characters long.
     * *  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".
     * </pre>
     *
     * <code>map&lt;string, string&gt; params = 5;</code>
     */
    public java.lang.String getParamsOrDefault(
        java.lang.String key, java.lang.String defaultValue) {
      if (key == null) {
        throw new java.lang.NullPointerException();
      }
      java.util.Map<java.lang.String, java.lang.String> map = internalGetParams().getMap();
      return map.containsKey(key) ? map.get(key) : defaultValue;
    }
    /**
     *
     *
     * <pre>
     * Additional domain-specific parameters for the predictions, any string must
     * be up to 25000 characters long.
     * *  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".
     * </pre>
     *
     * <code>map&lt;string, string&gt; params = 5;</code>
     */
    public java.lang.String getParamsOrThrow(java.lang.String key) {
      if (key == null) {
        throw new java.lang.NullPointerException();
      }
      java.util.Map<java.lang.String, java.lang.String> map = internalGetParams().getMap();
      if (!map.containsKey(key)) {
        throw new java.lang.IllegalArgumentException();
      }
      return map.get(key);
    }

    public Builder clearParams() {
      internalGetMutableParams().getMutableMap().clear();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Additional domain-specific parameters for the predictions, any string must
     * be up to 25000 characters long.
     * *  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".
     * </pre>
     *
     * <code>map&lt;string, string&gt; params = 5;</code>
     */
    public Builder removeParams(java.lang.String key) {
      if (key == null) {
        throw new java.lang.NullPointerException();
      }
      internalGetMutableParams().getMutableMap().remove(key);
      return this;
    }
    /** Use alternate mutation accessors instead. */
    @java.lang.Deprecated
    public java.util.Map<java.lang.String, java.lang.String> getMutableParams() {
      return internalGetMutableParams().getMutableMap();
    }
    /**
     *
     *
     * <pre>
     * Additional domain-specific parameters for the predictions, any string must
     * be up to 25000 characters long.
     * *  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".
     * </pre>
     *
     * <code>map&lt;string, string&gt; params = 5;</code>
     */
    public Builder putParams(java.lang.String key, java.lang.String value) {
      if (key == null) {
        throw new java.lang.NullPointerException();
      }
      if (value == null) {
        throw new java.lang.NullPointerException();
      }
      internalGetMutableParams().getMutableMap().put(key, value);
      return this;
    }
    /**
     *
     *
     * <pre>
     * Additional domain-specific parameters for the predictions, any string must
     * be up to 25000 characters long.
     * *  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".
     * </pre>
     *
     * <code>map&lt;string, string&gt; params = 5;</code>
     */
    public Builder putAllParams(java.util.Map<java.lang.String, java.lang.String> values) {
      internalGetMutableParams().getMutableMap().putAll(values);
      return this;
    }

    @java.lang.Override
    public final Builder setUnknownFields(final com.google.protobuf.UnknownFieldSet unknownFields) {
      return super.setUnknownFields(unknownFields);
    }

    @java.lang.Override
    public final Builder mergeUnknownFields(
        final com.google.protobuf.UnknownFieldSet unknownFields) {
      return super.mergeUnknownFields(unknownFields);
    }

    // @@protoc_insertion_point(builder_scope:google.cloud.automl.v1beta1.BatchPredictRequest)
  }

  // @@protoc_insertion_point(class_scope:google.cloud.automl.v1beta1.BatchPredictRequest)
  private static final com.google.cloud.automl.v1beta1.BatchPredictRequest DEFAULT_INSTANCE;

  static {
    DEFAULT_INSTANCE = new com.google.cloud.automl.v1beta1.BatchPredictRequest();
  }

  public static com.google.cloud.automl.v1beta1.BatchPredictRequest getDefaultInstance() {
    return DEFAULT_INSTANCE;
  }

  private static final com.google.protobuf.Parser<BatchPredictRequest> PARSER =
      new com.google.protobuf.AbstractParser<BatchPredictRequest>() {
        @java.lang.Override
        public BatchPredictRequest parsePartialFrom(
            com.google.protobuf.CodedInputStream input,
            com.google.protobuf.ExtensionRegistryLite extensionRegistry)
            throws com.google.protobuf.InvalidProtocolBufferException {
          return new BatchPredictRequest(input, extensionRegistry);
        }
      };

  public static com.google.protobuf.Parser<BatchPredictRequest> parser() {
    return PARSER;
  }

  @java.lang.Override
  public com.google.protobuf.Parser<BatchPredictRequest> getParserForType() {
    return PARSER;
  }

  @java.lang.Override
  public com.google.cloud.automl.v1beta1.BatchPredictRequest getDefaultInstanceForType() {
    return DEFAULT_INSTANCE;
  }
}
