Packages

object ResourceDownloader

Linear Supertypes
AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. ResourceDownloader
  2. AnyRef
  3. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. Protected

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(classOf[java.lang.CloneNotSupportedException]) @HotSpotIntrinsicCandidate() @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: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  19. val fileSystem: FileSystem
  20. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @HotSpotIntrinsicCandidate() @native()
  21. def getDownloadSize(resourceRequest: ResourceRequest): String
  22. def getResourceDownloader(folder: String): ResourceDownloader
  23. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @HotSpotIntrinsicCandidate() @native()
  24. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  25. lazy val libVersion: Version
  26. def listAvailableAnnotators(folder: String = publicLoc): List[String]
  27. def listPretrainedResources(folder: String, resourceType: ResourceType, lang: String, version: Version): List[String]
  28. def listPretrainedResources(folder: String, resourceType: ResourceType, version: Version): List[String]
  29. def listPretrainedResources(folder: String, resourceType: ResourceType, lang: String): List[String]
  30. 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

  31. def listPublicModels(): List[String]

    List all pretrained models in public name_lang

  32. def listPublicPipelines(): List[String]

    List all pretrained pipelines in public

  33. 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

  34. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  35. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @HotSpotIntrinsicCandidate() @native()
  36. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @HotSpotIntrinsicCandidate() @native()
  37. var privateDownloader: ResourceDownloader
  38. var publicDownloader: ResourceDownloader
  39. val publicLoc: String
  40. def publicResourceString(annotator: Option[String] = None, lang: Option[String] = None, version: Option[String] = Some(Build.version), resourceType: ResourceType): String
  41. def resetResourceDownloader(): Unit

    Reset the cache and recreate ResourceDownloader S3 credentials

  42. def s3Bucket: String
  43. def s3BucketCommunity: String
  44. def s3Path: String
  45. def showAvailableAnnotators(folder: String = publicLoc): Unit
  46. 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"

  47. 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

  48. 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

  49. 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"

  50. 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

  51. 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

  52. 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

  53. def showString(list: List[String], resourceType: ResourceType): String
  54. def showUnCategorizedResources(lang: String, version: String): Unit
  55. def showUnCategorizedResources(lang: String): Unit
  56. lazy val sparkVersion: Version
  57. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  58. def toString(): String
    Definition Classes
    AnyRef → Any
  59. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  60. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  61. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable]) @Deprecated
    Deprecated

    (Since version 9)

Inherited from AnyRef

Inherited from Any

Ungrouped