xref: /external/google-cloud-java/java-automl/proto-google-cloud-automl-v1/src/main/java/com/google/cloud/automl/v1/BatchPredictRequest.java

/*
 * Copyright 2020 Google LLC
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     https://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
// Generated by the protocol buffer compiler.  DO NOT EDIT!
// source: google/cloud/automl/v1/prediction_service.proto

package com.google.cloud.automl.v1;

/**
 *
 *
 * <pre>
 * Request message for [PredictionService.BatchPredict][google.cloud.automl.v1.PredictionService.BatchPredict].
 * </pre>
 *
 * Protobuf type {@code google.cloud.automl.v1.BatchPredictRequest}
 */
public final class BatchPredictRequest extends com.google.protobuf.GeneratedMessageV3
    implements
    // @@protoc_insertion_point(message_implements:google.cloud.automl.v1.BatchPredictRequest)
    BatchPredictRequestOrBuilder {
  private static final long serialVersionUID = 0L;
  // Use BatchPredictRequest.newBuilder() to construct.
  private BatchPredictRequest(com.google.protobuf.GeneratedMessageV3.Builder<?> builder) {
    super(builder);
  }

  private BatchPredictRequest() {
    name_ = "";
  }

  @java.lang.Override
  @SuppressWarnings({"unused"})
  protected java.lang.Object newInstance(UnusedPrivateParameter unused) {
    return new BatchPredictRequest();
  }

  @java.lang.Override
  public final com.google.protobuf.UnknownFieldSet getUnknownFields() {
    return this.unknownFields;
  }

  public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
    return com.google.cloud.automl.v1.PredictionServiceProto
        .internal_static_google_cloud_automl_v1_BatchPredictRequest_descriptor;
  }

  @SuppressWarnings({"rawtypes"})
  @java.lang.Override
  protected com.google.protobuf.MapField internalGetMapField(int number) {
    switch (number) {
      case 5:
        return internalGetParams();
      default:
        throw new RuntimeException("Invalid map field number: " + number);
    }
  }

  @java.lang.Override
  protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
      internalGetFieldAccessorTable() {
    return com.google.cloud.automl.v1.PredictionServiceProto
        .internal_static_google_cloud_automl_v1_BatchPredictRequest_fieldAccessorTable
        .ensureFieldAccessorsInitialized(
            com.google.cloud.automl.v1.BatchPredictRequest.class,
            com.google.cloud.automl.v1.BatchPredictRequest.Builder.class);
  }

  public static final int NAME_FIELD_NUMBER = 1;

  @SuppressWarnings("serial")
  private volatile java.lang.Object name_ = "";
  /**
   *
   *
   * <pre>
   * Required. Name of the model requested to serve the batch prediction.
   * </pre>
   *
   * <code>
   * string name = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
   * </code>
   *
   * @return The name.
   */
  @java.lang.Override
  public java.lang.String getName() {
    java.lang.Object ref = name_;
    if (ref instanceof java.lang.String) {
      return (java.lang.String) ref;
    } else {
      com.google.protobuf.ByteString bs = (com.google.protobuf.ByteString) ref;
      java.lang.String s = bs.toStringUtf8();
      name_ = s;
      return s;
    }
  }
  /**
   *
   *
   * <pre>
   * Required. Name of the model requested to serve the batch prediction.
   * </pre>
   *
   * <code>
   * string name = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
   * </code>
   *
   * @return The bytes for name.
   */
  @java.lang.Override
  public com.google.protobuf.ByteString getNameBytes() {
    java.lang.Object ref = name_;
    if (ref instanceof java.lang.String) {
      com.google.protobuf.ByteString b =
          com.google.protobuf.ByteString.copyFromUtf8((java.lang.String) ref);
      name_ = b;
      return b;
    } else {
      return (com.google.protobuf.ByteString) ref;
    }
  }

  public static final int INPUT_CONFIG_FIELD_NUMBER = 3;
  private com.google.cloud.automl.v1.BatchPredictInputConfig inputConfig_;
  /**
   *
   *
   * <pre>
   * Required. The input configuration for batch prediction.
   * </pre>
   *
   * <code>
   * .google.cloud.automl.v1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];
   * </code>
   *
   * @return Whether the inputConfig field is set.
   */
  @java.lang.Override
  public boolean hasInputConfig() {
    return inputConfig_ != null;
  }
  /**
   *
   *
   * <pre>
   * Required. The input configuration for batch prediction.
   * </pre>
   *
   * <code>
   * .google.cloud.automl.v1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];
   * </code>
   *
   * @return The inputConfig.
   */
  @java.lang.Override
  public com.google.cloud.automl.v1.BatchPredictInputConfig getInputConfig() {
    return inputConfig_ == null
        ? com.google.cloud.automl.v1.BatchPredictInputConfig.getDefaultInstance()
        : inputConfig_;
  }
  /**
   *
   *
   * <pre>
   * Required. The input configuration for batch prediction.
   * </pre>
   *
   * <code>
   * .google.cloud.automl.v1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];
   * </code>
   */
  @java.lang.Override
  public com.google.cloud.automl.v1.BatchPredictInputConfigOrBuilder getInputConfigOrBuilder() {
    return inputConfig_ == null
        ? com.google.cloud.automl.v1.BatchPredictInputConfig.getDefaultInstance()
        : inputConfig_;
  }

  public static final int OUTPUT_CONFIG_FIELD_NUMBER = 4;
  private com.google.cloud.automl.v1.BatchPredictOutputConfig outputConfig_;
  /**
   *
   *
   * <pre>
   * Required. The Configuration specifying where output predictions should
   * be written.
   * </pre>
   *
   * <code>
   * .google.cloud.automl.v1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];
   * </code>
   *
   * @return Whether the outputConfig field is set.
   */
  @java.lang.Override
  public boolean hasOutputConfig() {
    return outputConfig_ != null;
  }
  /**
   *
   *
   * <pre>
   * Required. The Configuration specifying where output predictions should
   * be written.
   * </pre>
   *
   * <code>
   * .google.cloud.automl.v1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];
   * </code>
   *
   * @return The outputConfig.
   */
  @java.lang.Override
  public com.google.cloud.automl.v1.BatchPredictOutputConfig getOutputConfig() {
    return outputConfig_ == null
        ? com.google.cloud.automl.v1.BatchPredictOutputConfig.getDefaultInstance()
        : outputConfig_;
  }
  /**
   *
   *
   * <pre>
   * Required. The Configuration specifying where output predictions should
   * be written.
   * </pre>
   *
   * <code>
   * .google.cloud.automl.v1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];
   * </code>
   */
  @java.lang.Override
  public com.google.cloud.automl.v1.BatchPredictOutputConfigOrBuilder getOutputConfigOrBuilder() {
    return outputConfig_ == null
        ? com.google.cloud.automl.v1.BatchPredictOutputConfig.getDefaultInstance()
        : outputConfig_;
  }

  public static final int PARAMS_FIELD_NUMBER = 5;

  private static final class ParamsDefaultEntryHolder {
    static final com.google.protobuf.MapEntry<java.lang.String, java.lang.String> defaultEntry =
        com.google.protobuf.MapEntry.<java.lang.String, java.lang.String>newDefaultInstance(
            com.google.cloud.automl.v1.PredictionServiceProto
                .internal_static_google_cloud_automl_v1_BatchPredictRequest_ParamsEntry_descriptor,
            com.google.protobuf.WireFormat.FieldType.STRING,
            "",
            com.google.protobuf.WireFormat.FieldType.STRING,
            "");
  }

  @SuppressWarnings("serial")
  private com.google.protobuf.MapField<java.lang.String, java.lang.String> params_;

  private com.google.protobuf.MapField<java.lang.String, java.lang.String> internalGetParams() {
    if (params_ == null) {
      return com.google.protobuf.MapField.emptyMapField(ParamsDefaultEntryHolder.defaultEntry);
    }
    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.
   * 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.
   * </pre>
   *
   * <code>map&lt;string, string&gt; params = 5;</code>
   */
  @java.lang.Override
  public boolean containsParams(java.lang.String key) {
    if (key == null) {
      throw new NullPointerException("map key");
    }
    return internalGetParams().getMap().containsKey(key);
  }
  /** Use {@link #getParamsMap()} instead. */
  @java.lang.Override
  @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.
   * 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.
   * </pre>
   *
   * <code>map&lt;string, string&gt; params = 5;</code>
   */
  @java.lang.Override
  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.
   * 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.
   * </pre>
   *
   * <code>map&lt;string, string&gt; params = 5;</code>
   */
  @java.lang.Override
  public /* nullable */ java.lang.String getParamsOrDefault(
      java.lang.String key,
      /* nullable */
      java.lang.String defaultValue) {
    if (key == null) {
      throw new NullPointerException("map key");
    }
    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.
   * 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.
   * </pre>
   *
   * <code>map&lt;string, string&gt; params = 5;</code>
   */
  @java.lang.Override
  public java.lang.String getParamsOrThrow(java.lang.String key) {
    if (key == null) {
      throw new NullPointerException("map key");
    }
    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);
  }

  private byte memoizedIsInitialized = -1;

  @java.lang.Override
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    byte isInitialized = memoizedIsInitialized;
    if (isInitialized == 1) return true;
    if (isInitialized == 0) return false;

    memoizedIsInitialized = 1;
    return true;
  }

  @java.lang.Override
  public void writeTo(com.google.protobuf.CodedOutputStream output) throws java.io.IOException {
    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) {
      com.google.protobuf.GeneratedMessageV3.writeString(output, 1, name_);
    }
    if (inputConfig_ != null) {
      output.writeMessage(3, getInputConfig());
    }
    if (outputConfig_ != null) {
      output.writeMessage(4, getOutputConfig());
    }
    com.google.protobuf.GeneratedMessageV3.serializeStringMapTo(
        output, internalGetParams(), ParamsDefaultEntryHolder.defaultEntry, 5);
    getUnknownFields().writeTo(output);
  }

  @java.lang.Override
  public int getSerializedSize() {
    int size = memoizedSize;
    if (size != -1) return size;

    size = 0;
    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) {
      size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, name_);
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    if (inputConfig_ != null) {
      size += com.google.protobuf.CodedOutputStream.computeMessageSize(3, getInputConfig());
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    if (outputConfig_ != null) {
      size += com.google.protobuf.CodedOutputStream.computeMessageSize(4, getOutputConfig());
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    for (java.util.Map.Entry<java.lang.String, java.lang.String> entry :
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  @java.lang.Override
  public boolean equals(final java.lang.Object obj) {
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     *
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     * <pre>
     * Required. Name of the model requested to serve the batch prediction.
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     *
     * <code>
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     *
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    /**
     *
     *
     * <pre>
     * Required. Name of the model requested to serve the batch prediction.
     * </pre>
     *
     * <code>
     * string name = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
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     *
     *
     * <pre>
     * Required. Name of the model requested to serve the batch prediction.
     * </pre>
     *
     * <code>
     * string name = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
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     *
     * @return This builder for chaining.
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    /**
     *
     *
     * <pre>
     * Required. Name of the model requested to serve the batch prediction.
     * </pre>
     *
     * <code>
     * string name = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
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     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];
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     *
     *
     * <pre>
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     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];
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     *
     * @return The inputConfig.
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    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];
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    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];
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     */
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    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>
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     */
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    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>
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     */
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      return this;
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    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];
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    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];
     * </code>
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    /**
     *
     *
     * <pre>
     * Required. The input configuration for batch prediction.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];
     * </code>
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    private com.google.protobuf.SingleFieldBuilderV3<
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    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];
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     * @return Whether the outputConfig field is set.
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    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];
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     *
     * @return The outputConfig.
     */
    public com.google.cloud.automl.v1.BatchPredictOutputConfig getOutputConfig() {
      if (outputConfigBuilder_ == null) {
        return outputConfig_ == null
            ? com.google.cloud.automl.v1.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.v1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];
     * </code>
     */
    public Builder setOutputConfig(com.google.cloud.automl.v1.BatchPredictOutputConfig value) {
      if (outputConfigBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        outputConfig_ = value;
      } else {
        outputConfigBuilder_.setMessage(value);
      }
      bitField0_ |= 0x00000004;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];
     * </code>
     */
    public Builder setOutputConfig(
        com.google.cloud.automl.v1.BatchPredictOutputConfig.Builder builderForValue) {
      if (outputConfigBuilder_ == null) {
        outputConfig_ = builderForValue.build();
      } else {
        outputConfigBuilder_.setMessage(builderForValue.build());
      }
      bitField0_ |= 0x00000004;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];
     * </code>
     */
    public Builder mergeOutputConfig(com.google.cloud.automl.v1.BatchPredictOutputConfig value) {
      if (outputConfigBuilder_ == null) {
        if (((bitField0_ & 0x00000004) != 0)
            && outputConfig_ != null
            && outputConfig_
                != com.google.cloud.automl.v1.BatchPredictOutputConfig.getDefaultInstance()) {
          getOutputConfigBuilder().mergeFrom(value);
        } else {
          outputConfig_ = value;
        }
      } else {
        outputConfigBuilder_.mergeFrom(value);
      }
      bitField0_ |= 0x00000004;
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];
     * </code>
     */
    public Builder clearOutputConfig() {
      bitField0_ = (bitField0_ & ~0x00000004);
      outputConfig_ = null;
      if (outputConfigBuilder_ != null) {
        outputConfigBuilder_.dispose();
        outputConfigBuilder_ = null;
      }
      onChanged();
      return this;
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];
     * </code>
     */
    public com.google.cloud.automl.v1.BatchPredictOutputConfig.Builder getOutputConfigBuilder() {
      bitField0_ |= 0x00000004;
      onChanged();
      return getOutputConfigFieldBuilder().getBuilder();
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];
     * </code>
     */
    public com.google.cloud.automl.v1.BatchPredictOutputConfigOrBuilder getOutputConfigOrBuilder() {
      if (outputConfigBuilder_ != null) {
        return outputConfigBuilder_.getMessageOrBuilder();
      } else {
        return outputConfig_ == null
            ? com.google.cloud.automl.v1.BatchPredictOutputConfig.getDefaultInstance()
            : outputConfig_;
      }
    }
    /**
     *
     *
     * <pre>
     * Required. The Configuration specifying where output predictions should
     * be written.
     * </pre>
     *
     * <code>
     * .google.cloud.automl.v1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];
     * </code>
     */
    private com.google.protobuf.SingleFieldBuilderV3<
            com.google.cloud.automl.v1.BatchPredictOutputConfig,
            com.google.cloud.automl.v1.BatchPredictOutputConfig.Builder,
            com.google.cloud.automl.v1.BatchPredictOutputConfigOrBuilder>
        getOutputConfigFieldBuilder() {
      if (outputConfigBuilder_ == null) {
        outputConfigBuilder_ =
            new com.google.protobuf.SingleFieldBuilderV3<
                com.google.cloud.automl.v1.BatchPredictOutputConfig,
                com.google.cloud.automl.v1.BatchPredictOutputConfig.Builder,
                com.google.cloud.automl.v1.BatchPredictOutputConfigOrBuilder>(
                getOutputConfig(), getParentForChildren(), isClean());
        outputConfig_ = null;
      }
      return outputConfigBuilder_;
    }

    private com.google.protobuf.MapField<java.lang.String, java.lang.String> params_;

    private com.google.protobuf.MapField<java.lang.String, java.lang.String> internalGetParams() {
      if (params_ == null) {
        return com.google.protobuf.MapField.emptyMapField(ParamsDefaultEntryHolder.defaultEntry);
      }
      return params_;
    }

    private com.google.protobuf.MapField<java.lang.String, java.lang.String>
        internalGetMutableParams() {
      if (params_ == null) {
        params_ = com.google.protobuf.MapField.newMapField(ParamsDefaultEntryHolder.defaultEntry);
      }
      if (!params_.isMutable()) {
        params_ = params_.copy();
      }
      bitField0_ |= 0x00000008;
      onChanged();
      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.
     * 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.
     * </pre>
     *
     * <code>map&lt;string, string&gt; params = 5;</code>
     */
    @java.lang.Override
    public boolean containsParams(java.lang.String key) {
      if (key == null) {
        throw new NullPointerException("map key");
      }
      return internalGetParams().getMap().containsKey(key);
    }
    /** Use {@link #getParamsMap()} instead. */
    @java.lang.Override
    @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.
     * 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.
     * </pre>
     *
     * <code>map&lt;string, string&gt; params = 5;</code>
     */
    @java.lang.Override
    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.
     * 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.
     * </pre>
     *
     * <code>map&lt;string, string&gt; params = 5;</code>
     */
    @java.lang.Override
    public /* nullable */ java.lang.String getParamsOrDefault(
        java.lang.String key,
        /* nullable */
        java.lang.String defaultValue) {
      if (key == null) {
        throw new NullPointerException("map key");
      }
      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.
     * 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.
     * </pre>
     *
     * <code>map&lt;string, string&gt; params = 5;</code>
     */
    @java.lang.Override
    public java.lang.String getParamsOrThrow(java.lang.String key) {
      if (key == null) {
        throw new NullPointerException("map key");
      }
      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() {
      bitField0_ = (bitField0_ & ~0x00000008);
      internalGetMutableParams().getMutableMap().clear();
      return this;
    }
    /**
     *
     *
     * <pre>
     * 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.
     * </pre>
     *
     * <code>map&lt;string, string&gt; params = 5;</code>
     */
    public Builder removeParams(java.lang.String key) {
      if (key == null) {
        throw new NullPointerException("map key");
      }
      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() {
      bitField0_ |= 0x00000008;
      return internalGetMutableParams().getMutableMap();
    }
    /**
     *
     *
     * <pre>
     * 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.
     * </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 NullPointerException("map key");
      }
      if (value == null) {
        throw new NullPointerException("map value");
      }
      internalGetMutableParams().getMutableMap().put(key, value);
      bitField0_ |= 0x00000008;
      return this;
    }
    /**
     *
     *
     * <pre>
     * 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.
     * </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);
      bitField0_ |= 0x00000008;
      return this;
    }

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    @java.lang.Override
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    // @@protoc_insertion_point(builder_scope:google.cloud.automl.v1.BatchPredictRequest)
  }

  // @@protoc_insertion_point(class_scope:google.cloud.automl.v1.BatchPredictRequest)
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  static {
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  public static com.google.cloud.automl.v1.BatchPredictRequest getDefaultInstance() {
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          return builder.buildPartial();
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  public static com.google.protobuf.Parser<BatchPredictRequest> parser() {
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  }

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

  @java.lang.Override
  public com.google.cloud.automl.v1.BatchPredictRequest getDefaultInstanceForType() {
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}