Package com.google.cloud.automl.v1

Class BatchPredictOutputConfig

java.lang.Object
com.google.protobuf.AbstractMessageLite
com.google.protobuf.AbstractMessage
com.google.protobuf.GeneratedMessage
com.google.cloud.automl.v1.BatchPredictOutputConfig
All Implemented Interfaces:
BatchPredictOutputConfigOrBuilder, com.google.protobuf.Message, com.google.protobuf.MessageLite, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Serializable
@Generated public final class BatchPredictOutputConfig extends com.google.protobuf.GeneratedMessage 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
See Also:

  • Field Details

    • GCS_DESTINATION_FIELD_NUMBER

      public static final int GCS_DESTINATION_FIELD_NUMBER
      See Also:

  • Method Details

    • getDescriptor

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

    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage

    • getDestinationCase

      public BatchPredictOutputConfig.DestinationCase getDestinationCase()
      Specified by:
      getDestinationCase in interface BatchPredictOutputConfigOrBuilder

    • 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.

    • getGcsDestinationOrBuilder

      public GcsDestinationOrBuilder getGcsDestinationOrBuilder()
       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:
      getGcsDestinationOrBuilder in interface BatchPredictOutputConfigOrBuilder

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage

    • writeTo

      public void writeTo(com.google.protobuf.CodedOutputStream output) throws IOException
      Specified by:
      writeTo in interface com.google.protobuf.MessageLite
      Overrides:
      writeTo in class com.google.protobuf.GeneratedMessage
      Throws:
      IOException

    • getSerializedSize

      public int getSerializedSize()
      Specified by:
      getSerializedSize in interface com.google.protobuf.MessageLite
      Overrides:
      getSerializedSize in class com.google.protobuf.GeneratedMessage

    • equals

      public boolean equals(Object obj)
      Specified by:
      equals in interface com.google.protobuf.Message
      Overrides:
      equals in class com.google.protobuf.AbstractMessage

    • hashCode

      public int hashCode()
      Specified by:
      hashCode in interface com.google.protobuf.Message
      Overrides:
      hashCode in class com.google.protobuf.AbstractMessage

    • parseFrom

      public static BatchPredictOutputConfig parseFrom(ByteBuffer data) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • parseFrom

      public static BatchPredictOutputConfig parseFrom(ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • parseFrom

      public static BatchPredictOutputConfig parseFrom(com.google.protobuf.ByteString data) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • parseFrom

      public static BatchPredictOutputConfig parseFrom(com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • parseFrom

      public static BatchPredictOutputConfig parseFrom(byte[] data) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • parseFrom

      public static BatchPredictOutputConfig parseFrom(byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • parseFrom

      public static BatchPredictOutputConfig parseFrom(InputStream input) throws IOException
      Throws:
      IOException

    • parseFrom

      public static BatchPredictOutputConfig parseFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException

    • parseDelimitedFrom

      public static BatchPredictOutputConfig parseDelimitedFrom(InputStream input) throws IOException
      Throws:
      IOException

    • parseDelimitedFrom

      public static BatchPredictOutputConfig parseDelimitedFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException

    • parseFrom

      public static BatchPredictOutputConfig parseFrom(com.google.protobuf.CodedInputStream input) throws IOException
      Throws:
      IOException

    • parseFrom

      public static BatchPredictOutputConfig parseFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException

    • newBuilderForType

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

    • newBuilder

      public static BatchPredictOutputConfig.Builder newBuilder()

    • newBuilder

      public static BatchPredictOutputConfig.Builder newBuilder(BatchPredictOutputConfig prototype)

    • toBuilder

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

    • newBuilderForType

      protected BatchPredictOutputConfig.Builder newBuilderForType(com.google.protobuf.AbstractMessage.BuilderParent parent)
      Overrides:
      newBuilderForType in class com.google.protobuf.AbstractMessage

    • getDefaultInstance

      public static BatchPredictOutputConfig getDefaultInstance()

    • parser

      public static com.google.protobuf.Parser<BatchPredictOutputConfig> parser()

    • getParserForType

      public com.google.protobuf.Parser<BatchPredictOutputConfig> getParserForType()
      Specified by:
      getParserForType in interface com.google.protobuf.Message
      Specified by:
      getParserForType in interface com.google.protobuf.MessageLite
      Overrides:
      getParserForType in class com.google.protobuf.GeneratedMessage

    • getDefaultInstanceForType

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