Value Members

1.  final def !=(arg0: Any): Boolean

   Definition Classes

   AnyRef → Any

2.  final def ##(): Int

   Definition Classes

   AnyRef → Any

3.  final def ==(arg0: Any): Boolean

   Definition Classes

   AnyRef → Any

4.  final def asInstanceOf[T0]: T0

   Definition Classes

   Any

5.  def cacheFolder: String
6.  def clearCache(request: ResourceRequest): Unit
7.  def clearCache(name: String, language: Option[String] = None, folder: String = publicLoc): Unit
8.  def clone(): AnyRef

   Attributes

   protected[lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... ) @native()

9.  var communityDownloader: ResourceDownloader
10.  def downloadModel[TModel <: PipelineStage](reader: DefaultParamsReadable[TModel], request: ResourceRequest): TModel
11.  def downloadModel[TModel <: PipelineStage](reader: DefaultParamsReadable[TModel], name: String, language: Option[String] = None, folder: String = publicLoc): TModel
12.  def downloadModelDirectly(model: String, folder: String = publicLoc, unzip: Boolean = true): Unit

    Downloads a model from the default S3 bucket to the cache pretrained folder.

    Downloads a model from the default S3 bucket to the cache pretrained folder.

    model

    the name of the key in the S3 bucket or s3 URI

    folder

    the folder of the model

    unzip

    used to unzip the model, by default true

13.  def downloadPipeline(request: ResourceRequest): PipelineModel
14.  def downloadPipeline(name: String, language: Option[String] = None, folder: String = publicLoc): PipelineModel
15.  def downloadResource(request: ResourceRequest): String

    Loads resource to path

    Loads resource to path

    request

    Request for resource

    returns

    path of downloaded resource

16.  def downloadResource(name: String, language: Option[String] = None, folder: String = publicLoc): String

    Loads resource to path

    Loads resource to path

    name

    Name of Resource

    language

    Desired language of Resource

    folder

    Subfolder in s3 where to search model (e.g. medicine)

    returns

    path of downloaded resource

17.  final def eq(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

18.  def equals(arg0: Any): Boolean

    Definition Classes

    AnyRef → Any

19.  val fileSystem: FileSystem
20.  def finalize(): Unit

    Attributes

    protected[lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( classOf[java.lang.Throwable] )

21.  final def getClass(): Class[_]

    Definition Classes

    AnyRef → Any

    Annotations

    @native()

22.  def getDownloadSize(resourceRequest: ResourceRequest): String
23.  def getResourceDownloader(folder: String): ResourceDownloader
24.  def hashCode(): Int

    Definition Classes

    AnyRef → Any

    Annotations

    @native()

25.  final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

26.  lazy val libVersion: Version
27.  def listAvailableAnnotators(folder: String = publicLoc): List[String]
28.  def listPretrainedResources(folder: String, resourceType: ResourceType, lang: String, version: Version): List[String]
29.  def listPretrainedResources(folder: String, resourceType: ResourceType, version: Version): List[String]
30.  def listPretrainedResources(folder: String, resourceType: ResourceType, lang: String): List[String]
31.  def listPretrainedResources(folder: String, resourceType: ResourceType, annotator: Option[String] = None, lang: Option[String] = None, version: Option[Version] = None): List[String]

    Lists pretrained resource from metadata.json, depending on the set filters.

    Lists pretrained resource from metadata.json, depending on the set filters. The folder in the S3 location and the resourceType is necessary. The other filters are optional and will be ignored if not set.

    folder

    Folder in the S3 location

    resourceType

    Type of the Resource. Can Either ResourceType.MODEL, ResourceType.PIPELINE or ResourceType.NOT_DEFINED

    annotator

    Name of the model class

    lang

    Language of the model

    version

    Version that the model should be compatible with

    returns

    A list of the available resources

32.  def listPublicModels(): List[String]

    List all pretrained models in public name_lang

33.  def listPublicPipelines(): List[String]

    List all pretrained pipelines in public

34.  def listUnCategorizedResources(): List[String]

    Returns models or pipelines in metadata json which has not been categorized yet.

    Returns models or pipelines in metadata json which has not been categorized yet.

    returns

    list of models or pipelines which are not categorized in metadata json

35.  final def ne(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

36.  final def notify(): Unit

    Definition Classes

    AnyRef

    Annotations

    @native()

37.  final def notifyAll(): Unit

    Definition Classes

    AnyRef

    Annotations

    @native()

38.  var privateDownloader: ResourceDownloader
39.  var publicDownloader: ResourceDownloader
40.  val publicLoc: String
41.  def publicResourceString(annotator: Option[String] = None, lang: Option[String] = None, version: Option[String] = Some(Build.version), resourceType: ResourceType): String
42.  def resetResourceDownloader(): Unit

    Reset the cache and recreate ResourceDownloader S3 credentials

43.  def s3Bucket: String
44.  def s3BucketCommunity: String
45.  def s3Path: String
46.  def showAvailableAnnotators(folder: String = publicLoc): Unit
47.  def showPublicModels(annotator: String, lang: String, version: String): Unit

    Prints all pretrained models for a particular annotator, that are compatible with a version of Spark NLP.

    Prints all pretrained models for a particular annotator, that are compatible with a version of Spark NLP.

    annotator

    Name of the model class, for example "NerDLModel"

    lang

    Language of the pretrained models to display, for example "en"

    version

    Version of Spark NLP that the model should be compatible with, for example "3.2.3"

48.  def showPublicModels(annotator: String, lang: String): Unit

    Prints all pretrained models for a particular annotator model, that are compatible with this version of Spark NLP.

    Prints all pretrained models for a particular annotator model, that are compatible with this version of Spark NLP.

    annotator

    Name of the annotator class

    lang

    Language of the pretrained models to display

49.  def showPublicModels(annotator: String): Unit

    Prints all pretrained models for a particular annotator model, that are compatible with this version of Spark NLP.

    Prints all pretrained models for a particular annotator model, that are compatible with this version of Spark NLP.

    annotator

    Name of the annotator class

50.  def showPublicModels(annotator: Option[String] = None, lang: Option[String] = None, version: Option[String] = Some(Build.version)): Unit

    Prints all pretrained models for a particular annotator model, that are compatible with a version of Spark NLP.

    Prints all pretrained models for a particular annotator model, that are compatible with a version of Spark NLP. If any of the optional arguments are not set, the filter is not considered.

    annotator

    Name of the model class, for example "NerDLModel"

    lang

    Language of the pretrained models to display, for example "en"

    version

    Version of Spark NLP that the model should be compatible with, for example "3.2.3"

51.  def showPublicPipelines(lang: String, version: String): Unit

    Prints all Pipelines available for a language and a version of Spark NLP.

    Prints all Pipelines available for a language and a version of Spark NLP.

    lang

    Language of the Pipeline

    version

    Version of Spark NLP

52.  def showPublicPipelines(lang: String): Unit

    Prints all Pipelines available for a language and this version of Spark NLP.

    Prints all Pipelines available for a language and this version of Spark NLP.

    lang

    Language of the Pipeline

53.  def showPublicPipelines(lang: Option[String] = None, version: Option[String] = Some(Build.version)): Unit

    Prints all Pipelines available for a language and a version of Spark NLP.

    Prints all Pipelines available for a language and a version of Spark NLP. By default shows all languages and uses the current version of Spark NLP.

    lang

    Language of the Pipeline

    version

    Version of Spark NLP

54.  def showString(list: List[String], resourceType: ResourceType): String
55.  def showUnCategorizedResources(lang: String, version: String): Unit
56.  def showUnCategorizedResources(lang: String): Unit
57.  lazy val sparkVersion: Version
58.  final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes

    AnyRef

59.  def toString(): String

    Definition Classes

    AnyRef → Any

60.  final def wait(): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

61.  final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

62.  final def wait(arg0: Long): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... ) @native()