Package com.google.cloud.automl.v1

Class BatchPredictOutputConfig.Builder

  • All Implemented Interfaces:
    BatchPredictOutputConfigOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
    Enclosing class:
    BatchPredictOutputConfig
    public static final class BatchPredictOutputConfig.Builder
extends com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictOutputConfig.Builder>
implements BatchPredictOutputConfigOrBuilder
     Output configuration for BatchPredict Action.

 As destination the
 [gcs_destination][google.cloud.automl.v1.BatchPredictOutputConfig.gcs_destination]
 must be set unless specified otherwise for a domain. If gcs_destination is
 set then in the given directory a new directory is created. Its name
 will be
 "prediction-<model-display-name>-<timestamp-of-prediction-call>",
 where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. The contents
 of it depends on the ML problem the predictions are made for.

  *  For Image Classification:
         In the created directory files `image_classification_1.jsonl`,
         `image_classification_2.jsonl`,...,`image_classification_N.jsonl`
         will be created, where N may be 1, and depends on the
         total number of the successfully predicted images and annotations.
         A single image will be listed only once with all its annotations,
         and its annotations will never be split across files.
         Each .JSONL file will contain, per line, a JSON representation of a
         proto that wraps image's "ID" : "<id_value>" followed by a list of
         zero or more AnnotationPayload protos (called annotations), which
         have classification detail populated.
         If prediction for any image failed (partially or completely), then an
         additional `errors_1.jsonl`, `errors_2.jsonl`,..., `errors_N.jsonl`
         files will be created (N depends on total number of failed
         predictions). These files will have a JSON representation of a proto
         that wraps the same "ID" : "<id_value>" but here followed by
         exactly one
         [`google.rpc.Status`](https://github.com/googleapis/googleapis/blob/master/google/rpc/status.proto)
         containing only `code` and `message`fields.

  *  For Image Object Detection:
         In the created directory files `image_object_detection_1.jsonl`,
         `image_object_detection_2.jsonl`,...,`image_object_detection_N.jsonl`
         will be created, where N may be 1, and depends on the
         total number of the successfully predicted images and annotations.
         Each .JSONL file will contain, per line, a JSON representation of a
         proto that wraps image's "ID" : "<id_value>" followed by a list of
         zero or more AnnotationPayload protos (called annotations), which
         have image_object_detection detail populated. A single image will
         be listed only once with all its annotations, and its annotations
         will never be split across files.
         If prediction for any image failed (partially or completely), then
         additional `errors_1.jsonl`, `errors_2.jsonl`,..., `errors_N.jsonl`
         files will be created (N depends on total number of failed
         predictions). These files will have a JSON representation of a proto
         that wraps the same "ID" : "<id_value>" but here followed by
         exactly one
         [`google.rpc.Status`](https://github.com/googleapis/googleapis/blob/master/google/rpc/status.proto)
         containing only `code` and `message`fields.
  *  For Video Classification:
         In the created directory a video_classification.csv file, and a .JSON
         file per each video classification requested in the input (i.e. each
         line in given CSV(s)), will be created.

         The format of video_classification.csv is:
         GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END,JSON_FILE_NAME,STATUS
         where:
         GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END = matches 1 to 1
             the prediction input lines (i.e. video_classification.csv has
             precisely the same number of lines as the prediction input had.)
         JSON_FILE_NAME = Name of .JSON file in the output directory, which
             contains prediction responses for the video time segment.
         STATUS = "OK" if prediction completed successfully, or an error code
             with message otherwise. If STATUS is not "OK" then the .JSON file
             for that line may not exist or be empty.

         Each .JSON file, assuming STATUS is "OK", will contain a list of
         AnnotationPayload protos in JSON format, which are the predictions
         for the video time segment the file is assigned to in the
         video_classification.csv. All AnnotationPayload protos will have
         video_classification field set, and will be sorted by
         video_classification.type field (note that the returned types are
         governed by `classifaction_types` parameter in
         [PredictService.BatchPredictRequest.params][]).

  *  For Video Object Tracking:
         In the created directory a video_object_tracking.csv file will be
         created, and multiple files video_object_trackinng_1.json,
         video_object_trackinng_2.json,..., video_object_trackinng_N.json,
         where N is the number of requests in the input (i.e. the number of
         lines in given CSV(s)).

         The format of video_object_tracking.csv is:
         GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END,JSON_FILE_NAME,STATUS
         where:
         GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END = matches 1 to 1
             the prediction input lines (i.e. video_object_tracking.csv has
             precisely the same number of lines as the prediction input had.)
         JSON_FILE_NAME = Name of .JSON file in the output directory, which
             contains prediction responses for the video time segment.
         STATUS = "OK" if prediction completed successfully, or an error
             code with message otherwise. If STATUS is not "OK" then the .JSON
             file for that line may not exist or be empty.

         Each .JSON file, assuming STATUS is "OK", will contain a list of
         AnnotationPayload protos in JSON format, which are the predictions
         for each frame of the video time segment the file is assigned to in
         video_object_tracking.csv. All AnnotationPayload protos will have
         video_object_tracking field set.
  *  For Text Classification:
         In the created directory files `text_classification_1.jsonl`,
         `text_classification_2.jsonl`,...,`text_classification_N.jsonl`
         will be created, where N may be 1, and depends on the
         total number of inputs and annotations found.

         Each .JSONL file will contain, per line, a JSON representation of a
         proto that wraps input text file (or document) in
         the text snippet (or document) proto and a list of
         zero or more AnnotationPayload protos (called annotations), which
         have classification detail populated. A single text file (or
         document) will be listed only once with all its annotations, and its
         annotations will never be split across files.

         If prediction for any input file (or document) failed (partially or
         completely), then additional `errors_1.jsonl`, `errors_2.jsonl`,...,
         `errors_N.jsonl` files will be created (N depends on total number of
         failed predictions). These files will have a JSON representation of a
         proto that wraps input file followed by exactly one
         [`google.rpc.Status`](https://github.com/googleapis/googleapis/blob/master/google/rpc/status.proto)
         containing only `code` and `message`.

  *  For Text Sentiment:
         In the created directory files `text_sentiment_1.jsonl`,
         `text_sentiment_2.jsonl`,...,`text_sentiment_N.jsonl`
         will be created, where N may be 1, and depends on the
         total number of inputs and annotations found.

         Each .JSONL file will contain, per line, a JSON representation of a
         proto that wraps input text file (or document) in
         the text snippet (or document) proto and a list of
         zero or more AnnotationPayload protos (called annotations), which
         have text_sentiment detail populated. A single text file (or
         document) will be listed only once with all its annotations, and its
         annotations will never be split across files.

         If prediction for any input file (or document) failed (partially or
         completely), then additional `errors_1.jsonl`, `errors_2.jsonl`,...,
         `errors_N.jsonl` files will be created (N depends on total number of
         failed predictions). These files will have a JSON representation of a
         proto that wraps input file followed by exactly one
         [`google.rpc.Status`](https://github.com/googleapis/googleapis/blob/master/google/rpc/status.proto)
         containing only `code` and `message`.

   *  For Text Extraction:
         In the created directory files `text_extraction_1.jsonl`,
         `text_extraction_2.jsonl`,...,`text_extraction_N.jsonl`
         will be created, where N may be 1, and depends on the
         total number of inputs and annotations found.
         The contents of these .JSONL file(s) depend on whether the input
         used inline text, or documents.
         If input was inline, then each .JSONL file will contain, per line,
           a JSON representation of a proto that wraps given in request text
           snippet's "id" (if specified), followed by input text snippet,
           and a list of zero or more
           AnnotationPayload protos (called annotations), which have
           text_extraction detail populated. A single text snippet will be
           listed only once with all its annotations, and its annotations will
           never be split across files.
         If input used documents, then each .JSONL file will contain, per
           line, a JSON representation of a proto that wraps given in request
           document proto, followed by its OCR-ed representation in the form
           of a text snippet, finally followed by a list of zero or more
           AnnotationPayload protos (called annotations), which have
           text_extraction detail populated and refer, via their indices, to
           the OCR-ed text snippet. A single document (and its text snippet)
           will be listed only once with all its annotations, and its
           annotations will never be split across files.
         If prediction for any text snippet failed (partially or completely),
         then additional `errors_1.jsonl`, `errors_2.jsonl`,...,
         `errors_N.jsonl` files will be created (N depends on total number of
         failed predictions). These files will have a JSON representation of a
         proto that wraps either the "id" : "<id_value>" (in case of inline)
         or the document proto (in case of document) but here followed by
         exactly one
         [`google.rpc.Status`](https://github.com/googleapis/googleapis/blob/master/google/rpc/status.proto)
         containing only `code` and `message`.

  *  For Tables:
         Output depends on whether
         [gcs_destination][google.cloud.automl.v1p1beta.BatchPredictOutputConfig.gcs_destination]
         or
         [bigquery_destination][google.cloud.automl.v1p1beta.BatchPredictOutputConfig.bigquery_destination]
         is set (either is allowed).
         Google Cloud Storage case:
           In the created directory files `tables_1.csv`, `tables_2.csv`,...,
           `tables_N.csv` will be created, where N may be 1, and depends on
           the total number of the successfully predicted rows.
           For all CLASSIFICATION
           [prediction_type-s][google.cloud.automl.v1p1beta.TablesModelMetadata.prediction_type]:
             Each .csv file will contain a header, listing all columns'
             [display_name-s][google.cloud.automl.v1p1beta.ColumnSpec.display_name]
             given on input followed by M target column names in the format of
             "<[target_column_specs][google.cloud.automl.v1p1beta.TablesModelMetadata.target_column_spec]
             [display_name][google.cloud.automl.v1p1beta.ColumnSpec.display_name]>_<target
             value>_score" where M is the number of distinct target values,
             i.e. number of distinct values in the target column of the table
             used to train the model. Subsequent lines will contain the
             respective values of successfully predicted rows, with the last,
             i.e. the target, columns having the corresponding prediction
             [scores][google.cloud.automl.v1p1beta.TablesAnnotation.score].
           For REGRESSION and FORECASTING
           [prediction_type-s][google.cloud.automl.v1p1beta.TablesModelMetadata.prediction_type]:
             Each .csv file will contain a header, listing all columns'
             [display_name-s][google.cloud.automl.v1p1beta.display_name]
             given on input followed by the predicted target column with name
             in the format of
             "predicted_<[target_column_specs][google.cloud.automl.v1p1beta.TablesModelMetadata.target_column_spec]
             [display_name][google.cloud.automl.v1p1beta.ColumnSpec.display_name]>"
             Subsequent lines will contain the respective values of
             successfully predicted rows, with the last, i.e. the target,
             column having the predicted target value.
             If prediction for any rows failed, then an additional
             `errors_1.csv`, `errors_2.csv`,..., `errors_N.csv` will be
             created (N depends on total number of failed rows). These files
             will have analogous format as `tables_*.csv`, but always with a
             single target column having
             [`google.rpc.Status`](https://github.com/googleapis/googleapis/blob/master/google/rpc/status.proto)
             represented as a JSON string, and containing only `code` and
             `message`.
         BigQuery case:
           [bigquery_destination][google.cloud.automl.v1p1beta.OutputConfig.bigquery_destination]
           pointing to a BigQuery project must be set. In the given project a
           new dataset will be created with name
           `prediction_<model-display-name>_<timestamp-of-prediction-call>`
           where <model-display-name> will be made
           BigQuery-dataset-name compatible (e.g. most special characters will
           become underscores), and timestamp will be in
           YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset
           two tables will be created, `predictions`, and `errors`.
           The `predictions` table's column names will be the input columns'
           [display_name-s][google.cloud.automl.v1p1beta.ColumnSpec.display_name]
           followed by the target column with name in the format of
           "predicted_<[target_column_specs][google.cloud.automl.v1p1beta.TablesModelMetadata.target_column_spec]
           [display_name][google.cloud.automl.v1p1beta.ColumnSpec.display_name]>"
           The input feature columns will contain the respective values of
           successfully predicted rows, with the target column having an
           ARRAY of
           [AnnotationPayloads][google.cloud.automl.v1p1beta.AnnotationPayload],
           represented as STRUCT-s, containing
           [TablesAnnotation][google.cloud.automl.v1p1beta.TablesAnnotation].
           The `errors` table contains rows for which the prediction has
           failed, it has analogous input columns while the target column name
           is in the format of
           "errors_<[target_column_specs][google.cloud.automl.v1p1beta.TablesModelMetadata.target_column_spec]
           [display_name][google.cloud.automl.v1p1beta.ColumnSpec.display_name]>",
           and as a value has
           [`google.rpc.Status`](https://github.com/googleapis/googleapis/blob/master/google/rpc/status.proto)
           represented as a STRUCT, and containing only `code` and `message`.
    Protobuf type google.cloud.automl.v1.BatchPredictOutputConfig

    • Method Detail

      • getDescriptor

        public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictOutputConfig.Builder>

      • getDescriptorForType

        public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
        Specified by:
        getDescriptorForType in interface com.google.protobuf.Message.Builder
        Specified by:
        getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
        Overrides:
        getDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictOutputConfig.Builder>

      • getDefaultInstanceForType

        public BatchPredictOutputConfig getDefaultInstanceForType()
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

      • build

        public BatchPredictOutputConfig build()
        Specified by:
        build in interface com.google.protobuf.Message.Builder
        Specified by:
        build in interface com.google.protobuf.MessageLite.Builder

      • buildPartial

        public BatchPredictOutputConfig buildPartial()
        Specified by:
        buildPartial in interface com.google.protobuf.Message.Builder
        Specified by:
        buildPartial in interface com.google.protobuf.MessageLite.Builder

      • setRepeatedField

        public BatchPredictOutputConfig.Builder setRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                         int index,
                                                         Object value)
        Specified by:
        setRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictOutputConfig.Builder>

      • addRepeatedField

        public BatchPredictOutputConfig.Builder addRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                         Object value)
        Specified by:
        addRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictOutputConfig.Builder>

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictOutputConfig.Builder>

      • mergeFrom

        public BatchPredictOutputConfig.Builder mergeFrom​(com.google.protobuf.CodedInputStream input,
                                                  com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                           throws IOException
        Specified by:
        mergeFrom in interface com.google.protobuf.Message.Builder
        Specified by:
        mergeFrom in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        mergeFrom in class com.google.protobuf.AbstractMessage.Builder<BatchPredictOutputConfig.Builder>
        Throws:
        IOException

      • hasGcsDestination

        public boolean hasGcsDestination()
         Required. The Google Cloud Storage location of the directory where the output is to
 be written to.
        .google.cloud.automl.v1.GcsDestination gcs_destination = 1 [(.google.api.field_behavior) = REQUIRED];
        Specified by:
        hasGcsDestination in interface BatchPredictOutputConfigOrBuilder
        Returns:
        Whether the gcsDestination field is set.

      • getGcsDestination

        public GcsDestination getGcsDestination()
         Required. The Google Cloud Storage location of the directory where the output is to
 be written to.
        .google.cloud.automl.v1.GcsDestination gcs_destination = 1 [(.google.api.field_behavior) = REQUIRED];
        Specified by:
        getGcsDestination in interface BatchPredictOutputConfigOrBuilder
        Returns:
        The gcsDestination.

      • setGcsDestination

        public BatchPredictOutputConfig.Builder setGcsDestination​(GcsDestination value)
         Required. The Google Cloud Storage location of the directory where the output is to
 be written to.
        .google.cloud.automl.v1.GcsDestination gcs_destination = 1 [(.google.api.field_behavior) = REQUIRED];

      • setGcsDestination

        public BatchPredictOutputConfig.Builder setGcsDestination​(GcsDestination.Builder builderForValue)
         Required. The Google Cloud Storage location of the directory where the output is to
 be written to.
        .google.cloud.automl.v1.GcsDestination gcs_destination = 1 [(.google.api.field_behavior) = REQUIRED];

      • mergeGcsDestination

        public BatchPredictOutputConfig.Builder mergeGcsDestination​(GcsDestination value)
         Required. The Google Cloud Storage location of the directory where the output is to
 be written to.
        .google.cloud.automl.v1.GcsDestination gcs_destination = 1 [(.google.api.field_behavior) = REQUIRED];

      • clearGcsDestination

        public BatchPredictOutputConfig.Builder clearGcsDestination()
         Required. The Google Cloud Storage location of the directory where the output is to
 be written to.
        .google.cloud.automl.v1.GcsDestination gcs_destination = 1 [(.google.api.field_behavior) = REQUIRED];

      • getGcsDestinationBuilder

        public GcsDestination.Builder getGcsDestinationBuilder()
         Required. The Google Cloud Storage location of the directory where the output is to
 be written to.
        .google.cloud.automl.v1.GcsDestination gcs_destination = 1 [(.google.api.field_behavior) = REQUIRED];

      • setUnknownFields

        public final BatchPredictOutputConfig.Builder setUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        setUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictOutputConfig.Builder>

      • mergeUnknownFields

        public final BatchPredictOutputConfig.Builder mergeUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        mergeUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictOutputConfig.Builder>