Value Members

1.  final def !=(arg0: Any): Boolean

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2.  final def ##(): Int

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3.  final def ==(arg0: Any): Boolean

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4.  final def asInstanceOf[T0]: T0

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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

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

    Downloads a resource from the default S3 bucket in the cache pretrained folder.

    Downloads a resource from the default S3 bucket in the cache pretrained folder.

    model

    the name of the key in the S3 bucket

    folder

    the language of the model

    returns

    the path to the downloaded file

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

    Loads resource to path

    Loads resource to path

    request

    Request for resource

    returns

    path of downloaded resource

17.  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

18.  def downloadS3Directory(path: String): URI

    Downloads the provided S3 path to a local temporary directory and returns the location of the folder.

    Downloads the provided S3 path to a local temporary directory and returns the location of the folder.

    path

    S3 URL to the resource

    returns

    URI of the local path to the temporary folder of the resource

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

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20.  def equals(arg0: Any): Boolean

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21.  val fileSystem: FileSystem
22.  def finalize(): Unit

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

23.  final def getClass(): Class[_]

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    @native()

24.  def getDownloadSize(resourceRequest: ResourceRequest): String
25.  def hashCode(): Int

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26.  final def isInstanceOf[T0]: Boolean

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27.  lazy val libVersion: Version
28.  def listAvailableAnnotators(folder: String = publicLoc): List[String]
29.  def listPretrainedResources(folder: String, resourceType: ResourceType, lang: String, version: Version): List[String]
30.  def listPretrainedResources(folder: String, resourceType: ResourceType, version: Version): List[String]
31.  def listPretrainedResources(folder: String, resourceType: ResourceType, lang: String): List[String]
32.  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

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

    List all pretrained models in public name_lang

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

    List all pretrained pipelines in public

35.  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

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

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37.  final def notify(): Unit

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    @native()

38.  final def notifyAll(): Unit

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    @native()

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

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59.  def toString(): String

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60.  final def wait(): Unit

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

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    @throws( ... )

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

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    @throws( ... ) @native()