Class BatchPredictInputConfig.Builder (2.22.0)

public static final class BatchPredictInputConfig.Builder extends 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 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 or

    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' display_name-s (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: all columns having TIME_SERIES_AVAILABLE_PAST_ONLY 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'

    display_name-s (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: all columns having

    TIME_SERIES_AVAILABLE_PAST_ONLY 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

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public BatchPredictInputConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
BatchPredictInputConfig.Builder
Overrides

build()

public BatchPredictInputConfig build()
Returns
TypeDescription
BatchPredictInputConfig

buildPartial()

public BatchPredictInputConfig buildPartial()
Returns
TypeDescription
BatchPredictInputConfig

clear()

public BatchPredictInputConfig.Builder clear()
Returns
TypeDescription
BatchPredictInputConfig.Builder
Overrides

clearBigquerySource()

public BatchPredictInputConfig.Builder clearBigquerySource()

The BigQuery location for the input content.

.google.cloud.automl.v1beta1.BigQuerySource bigquery_source = 2;

Returns
TypeDescription
BatchPredictInputConfig.Builder

clearField(Descriptors.FieldDescriptor field)

public BatchPredictInputConfig.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
BatchPredictInputConfig.Builder
Overrides

clearGcsSource()

public BatchPredictInputConfig.Builder clearGcsSource()

The Google Cloud Storage location for the input content.

.google.cloud.automl.v1beta1.GcsSource gcs_source = 1;

Returns
TypeDescription
BatchPredictInputConfig.Builder

clearOneof(Descriptors.OneofDescriptor oneof)

public BatchPredictInputConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
BatchPredictInputConfig.Builder
Overrides

clearSource()

public BatchPredictInputConfig.Builder clearSource()
Returns
TypeDescription
BatchPredictInputConfig.Builder

clone()

public BatchPredictInputConfig.Builder clone()
Returns
TypeDescription
BatchPredictInputConfig.Builder
Overrides

getBigquerySource()

public BigQuerySource getBigquerySource()

The BigQuery location for the input content.

.google.cloud.automl.v1beta1.BigQuerySource bigquery_source = 2;

Returns
TypeDescription
BigQuerySource

The bigquerySource.

getBigquerySourceBuilder()

public BigQuerySource.Builder getBigquerySourceBuilder()

The BigQuery location for the input content.

.google.cloud.automl.v1beta1.BigQuerySource bigquery_source = 2;

Returns
TypeDescription
BigQuerySource.Builder

getBigquerySourceOrBuilder()

public BigQuerySourceOrBuilder getBigquerySourceOrBuilder()

The BigQuery location for the input content.

.google.cloud.automl.v1beta1.BigQuerySource bigquery_source = 2;

Returns
TypeDescription
BigQuerySourceOrBuilder

getDefaultInstanceForType()

public BatchPredictInputConfig getDefaultInstanceForType()
Returns
TypeDescription
BatchPredictInputConfig

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

getGcsSource()

public GcsSource getGcsSource()

The Google Cloud Storage location for the input content.

.google.cloud.automl.v1beta1.GcsSource gcs_source = 1;

Returns
TypeDescription
GcsSource

The gcsSource.

getGcsSourceBuilder()

public GcsSource.Builder getGcsSourceBuilder()

The Google Cloud Storage location for the input content.

.google.cloud.automl.v1beta1.GcsSource gcs_source = 1;

Returns
TypeDescription
GcsSource.Builder

getGcsSourceOrBuilder()

public GcsSourceOrBuilder getGcsSourceOrBuilder()

The Google Cloud Storage location for the input content.

.google.cloud.automl.v1beta1.GcsSource gcs_source = 1;

Returns
TypeDescription
GcsSourceOrBuilder

getSourceCase()

public BatchPredictInputConfig.SourceCase getSourceCase()
Returns
TypeDescription
BatchPredictInputConfig.SourceCase

hasBigquerySource()

public boolean hasBigquerySource()

The BigQuery location for the input content.

.google.cloud.automl.v1beta1.BigQuerySource bigquery_source = 2;

Returns
TypeDescription
boolean

Whether the bigquerySource field is set.

hasGcsSource()

public boolean hasGcsSource()

The Google Cloud Storage location for the input content.

.google.cloud.automl.v1beta1.GcsSource gcs_source = 1;

Returns
TypeDescription
boolean

Whether the gcsSource field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeBigquerySource(BigQuerySource value)

public BatchPredictInputConfig.Builder mergeBigquerySource(BigQuerySource value)

The BigQuery location for the input content.

.google.cloud.automl.v1beta1.BigQuerySource bigquery_source = 2;

Parameter
NameDescription
valueBigQuerySource
Returns
TypeDescription
BatchPredictInputConfig.Builder

mergeFrom(BatchPredictInputConfig other)

public BatchPredictInputConfig.Builder mergeFrom(BatchPredictInputConfig other)
Parameter
NameDescription
otherBatchPredictInputConfig
Returns
TypeDescription
BatchPredictInputConfig.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public BatchPredictInputConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
BatchPredictInputConfig.Builder
Overrides
Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public BatchPredictInputConfig.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
BatchPredictInputConfig.Builder
Overrides

mergeGcsSource(GcsSource value)

public BatchPredictInputConfig.Builder mergeGcsSource(GcsSource value)

The Google Cloud Storage location for the input content.

.google.cloud.automl.v1beta1.GcsSource gcs_source = 1;

Parameter
NameDescription
valueGcsSource
Returns
TypeDescription
BatchPredictInputConfig.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final BatchPredictInputConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
BatchPredictInputConfig.Builder
Overrides

setBigquerySource(BigQuerySource value)

public BatchPredictInputConfig.Builder setBigquerySource(BigQuerySource value)

The BigQuery location for the input content.

.google.cloud.automl.v1beta1.BigQuerySource bigquery_source = 2;

Parameter
NameDescription
valueBigQuerySource
Returns
TypeDescription
BatchPredictInputConfig.Builder

setBigquerySource(BigQuerySource.Builder builderForValue)

public BatchPredictInputConfig.Builder setBigquerySource(BigQuerySource.Builder builderForValue)

The BigQuery location for the input content.

.google.cloud.automl.v1beta1.BigQuerySource bigquery_source = 2;

Parameter
NameDescription
builderForValueBigQuerySource.Builder
Returns
TypeDescription
BatchPredictInputConfig.Builder

setField(Descriptors.FieldDescriptor field, Object value)

public BatchPredictInputConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
BatchPredictInputConfig.Builder
Overrides

setGcsSource(GcsSource value)

public BatchPredictInputConfig.Builder setGcsSource(GcsSource value)

The Google Cloud Storage location for the input content.

.google.cloud.automl.v1beta1.GcsSource gcs_source = 1;

Parameter
NameDescription
valueGcsSource
Returns
TypeDescription
BatchPredictInputConfig.Builder

setGcsSource(GcsSource.Builder builderForValue)

public BatchPredictInputConfig.Builder setGcsSource(GcsSource.Builder builderForValue)

The Google Cloud Storage location for the input content.

.google.cloud.automl.v1beta1.GcsSource gcs_source = 1;

Parameter
NameDescription
builderForValueGcsSource.Builder
Returns
TypeDescription
BatchPredictInputConfig.Builder

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public BatchPredictInputConfig.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
BatchPredictInputConfig.Builder
Overrides

setUnknownFields(UnknownFieldSet unknownFields)

public final BatchPredictInputConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
BatchPredictInputConfig.Builder
Overrides