Package com.google.cloud.automl.v1beta1

Class BatchPredictInputConfig.Builder

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

 The format of input depends on the ML problem of the model used for
 prediction. As input source the
 [gcs_source][google.cloud.automl.v1beta1.InputConfig.gcs_source]
 is expected, unless specified otherwise.

 The formats are represented in EBNF with commas being literal and with
 non-terminal symbols defined near the end of this comment. The formats
 are:

  *  For Image Classification:
         CSV file(s) with each line having just a single column:
           GCS_FILE_PATH
           which leads to image of up to 30MB in size. Supported
           extensions: .JPEG, .GIF, .PNG. This path is treated as the ID in
           the Batch predict output.
         Three sample rows:
           gs://folder/image1.jpeg
           gs://folder/image2.gif
           gs://folder/image3.png

  *  For Image Object Detection:
         CSV file(s) with each line having just a single column:
           GCS_FILE_PATH
           which leads to image of up to 30MB in size. Supported
           extensions: .JPEG, .GIF, .PNG. This path is treated as the ID in
           the Batch predict output.
         Three sample rows:
           gs://folder/image1.jpeg
           gs://folder/image2.gif
           gs://folder/image3.png
  *  For Video Classification:
         CSV file(s) with each line in format:
           GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END
           GCS_FILE_PATH leads to video of up to 50GB in size and up to 3h
           duration. Supported extensions: .MOV, .MPEG4, .MP4, .AVI.
           TIME_SEGMENT_START and TIME_SEGMENT_END must be within the
           length of the video, and end has to be after the start.
         Three sample rows:
           gs://folder/video1.mp4,10,40
           gs://folder/video1.mp4,20,60
           gs://folder/vid2.mov,0,inf

  *  For Video Object Tracking:
         CSV file(s) with each line in format:
           GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END
           GCS_FILE_PATH leads to video of up to 50GB in size and up to 3h
           duration. Supported extensions: .MOV, .MPEG4, .MP4, .AVI.
           TIME_SEGMENT_START and TIME_SEGMENT_END must be within the
           length of the video, and end has to be after the start.
         Three sample rows:
           gs://folder/video1.mp4,10,240
           gs://folder/video1.mp4,300,360
           gs://folder/vid2.mov,0,inf
  *  For Text Classification:
         CSV file(s) with each line having just a single column:
           GCS_FILE_PATH | TEXT_SNIPPET
         Any given text file can have size upto 128kB.
         Any given text snippet content must have 60,000 characters or less.
         Three sample rows:
           gs://folder/text1.txt
           "Some text content to predict"
           gs://folder/text3.pdf
         Supported file extensions: .txt, .pdf

  *  For Text Sentiment:
         CSV file(s) with each line having just a single column:
           GCS_FILE_PATH | TEXT_SNIPPET
         Any given text file can have size upto 128kB.
         Any given text snippet content must have 500 characters or less.
         Three sample rows:
           gs://folder/text1.txt
           "Some text content to predict"
           gs://folder/text3.pdf
         Supported file extensions: .txt, .pdf

  * For Text Extraction
         .JSONL (i.e. JSON Lines) file(s) which either provide text in-line or
         as documents (for a single BatchPredict call only one of the these
         formats may be used).
         The in-line .JSONL file(s) contain per line a proto that
           wraps a temporary user-assigned TextSnippet ID (string up to 2000
           characters long) called "id", a TextSnippet proto (in
           json representation) and zero or more TextFeature protos. Any given
           text snippet content must have 30,000 characters or less, and also
           be UTF-8 NFC encoded (ASCII already is). The IDs provided should be
           unique.
         The document .JSONL file(s) contain, per line, a proto that wraps a
           Document proto with input_config set. Only PDF documents are
           supported now, and each document must be up to 2MB large.
         Any given .JSONL file must be 100MB or smaller, and no more than 20
         files may be given.
         Sample in-line JSON Lines file (presented here with artificial line
         breaks, but the only actual line break is denoted by \n):
           {
             "id": "my_first_id",
             "text_snippet": { "content": "dog car cat"},
             "text_features": [
               {
                 "text_segment": {"start_offset": 4, "end_offset": 6},
                 "structural_type": PARAGRAPH,
                 "bounding_poly": {
                   "normalized_vertices": [
                     {"x": 0.1, "y": 0.1},
                     {"x": 0.1, "y": 0.3},
                     {"x": 0.3, "y": 0.3},
                     {"x": 0.3, "y": 0.1},
                   ]
                 },
               }
             ],
           }\n
           {
             "id": "2",
             "text_snippet": {
               "content": "An elaborate content",
               "mime_type": "text/plain"
             }
           }
         Sample document JSON Lines file (presented here with artificial line
         breaks, but the only actual line break is denoted by \n).:
           {
             "document": {
               "input_config": {
                 "gcs_source": { "input_uris": [ "gs://folder/document1.pdf" ]
                 }
               }
             }
           }\n
           {
             "document": {
               "input_config": {
                 "gcs_source": { "input_uris": [ "gs://folder/document2.pdf" ]
                 }
               }
             }
           }

  *  For Tables:
         Either
         [gcs_source][google.cloud.automl.v1beta1.InputConfig.gcs_source] or

 [bigquery_source][google.cloud.automl.v1beta1.InputConfig.bigquery_source].
         GCS case:
           CSV file(s), each by itself 10GB or smaller and total size must be
           100GB or smaller, where first file must have a header containing
           column names. If the first row of a subsequent file is the same as
           the header, then it is also treated as a header. All other rows
           contain values for the corresponding columns.
           The column names must contain the model's

 [input_feature_column_specs'][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs]

 [display_name-s][google.cloud.automl.v1beta1.ColumnSpec.display_name]
           (order doesn't matter). The columns corresponding to the model's
           input feature column specs must contain values compatible with the
           column spec's data types. Prediction on all the rows, i.e. the CSV
           lines, will be attempted. For FORECASTING

 [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]:
           all columns having

 [TIME_SERIES_AVAILABLE_PAST_ONLY][google.cloud.automl.v1beta1.ColumnSpec.ForecastingMetadata.ColumnType]
           type will be ignored.
           First three sample rows of a CSV file:
             "First Name","Last Name","Dob","Addresses"

 "John","Doe","1968-01-22","[{"status":"current","address":"123_First_Avenue","city":"Seattle","state":"WA","zip":"11111","numberOfYears":"1"},{"status":"previous","address":"456_Main_Street","city":"Portland","state":"OR","zip":"22222","numberOfYears":"5"}]"

 "Jane","Doe","1980-10-16","[{"status":"current","address":"789_Any_Avenue","city":"Albany","state":"NY","zip":"33333","numberOfYears":"2"},{"status":"previous","address":"321_Main_Street","city":"Hoboken","state":"NJ","zip":"44444","numberOfYears":"3"}]}
         BigQuery case:
           An URI of a BigQuery table. The user data size of the BigQuery
           table must be 100GB or smaller.
           The column names must contain the model's

 [input_feature_column_specs'][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs]

 [display_name-s][google.cloud.automl.v1beta1.ColumnSpec.display_name]
           (order doesn't matter). The columns corresponding to the model's
           input feature column specs must contain values compatible with the
           column spec's data types. Prediction on all the rows of the table
           will be attempted. For FORECASTING

 [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]:
           all columns having

 [TIME_SERIES_AVAILABLE_PAST_ONLY][google.cloud.automl.v1beta1.ColumnSpec.ForecastingMetadata.ColumnType]
           type will be ignored.

  Definitions:
  GCS_FILE_PATH = A path to file on GCS, e.g. "gs://folder/video.avi".
  TEXT_SNIPPET = A content of a text snippet, UTF-8 encoded, enclosed within
                 double quotes ("")
  TIME_SEGMENT_START = TIME_OFFSET
                       Expresses a beginning, inclusive, of a time segment
                       within an
                       example that has a time dimension (e.g. video).
  TIME_SEGMENT_END = TIME_OFFSET
                     Expresses an end, exclusive, of a time segment within
                     an example that has a time dimension (e.g. video).
  TIME_OFFSET = A number of seconds as measured from the start of an
                example (e.g. video). Fractions are allowed, up to a
                microsecond precision. "inf" is allowed and it means the end
                of the example.

  Errors:
  If any of the provided CSV files can't be parsed or if more than certain
  percent of CSV rows cannot be processed then the operation fails and
  prediction does not happen. Regardless of overall success or failure the
  per-row failures, up to a certain count cap, will be listed in
  Operation.metadata.partial_failures.
    Protobuf type google.cloud.automl.v1beta1.BatchPredictInputConfig

    • 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<BatchPredictInputConfig.Builder>

      • clear

        public BatchPredictInputConfig.Builder clear()
        Specified by:
        clear in interface com.google.protobuf.Message.Builder
        Specified by:
        clear in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        clear in class com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictInputConfig.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<BatchPredictInputConfig.Builder>

      • getDefaultInstanceForType

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

      • build

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

      • buildPartial

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

      • clone

        public BatchPredictInputConfig.Builder clone()
        Specified by:
        clone in interface com.google.protobuf.Message.Builder
        Specified by:
        clone in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        clone in class com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictInputConfig.Builder>

      • clearField

        public BatchPredictInputConfig.Builder clearField​(com.google.protobuf.Descriptors.FieldDescriptor field)
        Specified by:
        clearField in interface com.google.protobuf.Message.Builder
        Overrides:
        clearField in class com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictInputConfig.Builder>

      • clearOneof

        public BatchPredictInputConfig.Builder clearOneof​(com.google.protobuf.Descriptors.OneofDescriptor oneof)
        Specified by:
        clearOneof in interface com.google.protobuf.Message.Builder
        Overrides:
        clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictInputConfig.Builder>

      • setRepeatedField

        public BatchPredictInputConfig.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<BatchPredictInputConfig.Builder>

      • addRepeatedField

        public BatchPredictInputConfig.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<BatchPredictInputConfig.Builder>

      • isInitialized

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

      • mergeFrom

        public BatchPredictInputConfig.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<BatchPredictInputConfig.Builder>
        Throws:
        IOException

      • hasGcsSource

        public boolean hasGcsSource()
         The Google Cloud Storage location for the input content.
        .google.cloud.automl.v1beta1.GcsSource gcs_source = 1;
        Specified by:
        hasGcsSource in interface BatchPredictInputConfigOrBuilder
        Returns:
        Whether the gcsSource field is set.

      • setGcsSource

        public BatchPredictInputConfig.Builder setGcsSource​(GcsSource value)
         The Google Cloud Storage location for the input content.
        .google.cloud.automl.v1beta1.GcsSource gcs_source = 1;

      • mergeGcsSource

        public BatchPredictInputConfig.Builder mergeGcsSource​(GcsSource value)
         The Google Cloud Storage location for the input content.
        .google.cloud.automl.v1beta1.GcsSource gcs_source = 1;

      • clearGcsSource

        public BatchPredictInputConfig.Builder clearGcsSource()
         The Google Cloud Storage location for the input content.
        .google.cloud.automl.v1beta1.GcsSource gcs_source = 1;

      • getGcsSourceBuilder

        public GcsSource.Builder getGcsSourceBuilder()
         The Google Cloud Storage location for the input content.
        .google.cloud.automl.v1beta1.GcsSource gcs_source = 1;

      • hasBigquerySource

        public boolean hasBigquerySource()
         The BigQuery location for the input content.
        .google.cloud.automl.v1beta1.BigQuerySource bigquery_source = 2;
        Specified by:
        hasBigquerySource in interface BatchPredictInputConfigOrBuilder
        Returns:
        Whether the bigquerySource field is set.

      • clearBigquerySource

        public BatchPredictInputConfig.Builder clearBigquerySource()
         The BigQuery location for the input content.
        .google.cloud.automl.v1beta1.BigQuerySource bigquery_source = 2;

      • getBigquerySourceBuilder

        public BigQuerySource.Builder getBigquerySourceBuilder()
         The BigQuery location for the input content.
        .google.cloud.automl.v1beta1.BigQuerySource bigquery_source = 2;

      • setUnknownFields

        public final BatchPredictInputConfig.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<BatchPredictInputConfig.Builder>

      • mergeUnknownFields

        public final BatchPredictInputConfig.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<BatchPredictInputConfig.Builder>