ResourceDownloader

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 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

    

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18. def equals(arg0: Any): Boolean

    

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19. val fileSystem: FileSystem

    

20. def finalize(): Unit

    

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21. final def getClass(): Class[_]

    

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22. def getDownloadSize(name: String, language: Option[String] = None, folder: String = publicLoc): String

    

23. def hashCode(): Int

    

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24. final def isInstanceOf[T0]: Boolean

    

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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

    

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35. final def notify(): Unit

    

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36. final def notifyAll(): Unit

    

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37. var publicDownloader: ResourceDownloader

    

38. val publicLoc: String

    

39. def publicResourceString(annotator: Option[String] = None, lang: Option[String] = None, version: Option[String] = Some(Build.version), resourceType: ResourceType): String

    

40. def resetResourceDownloader(): Unit

    

    Reset the cache and recreate ResourceDownloader S3 credentials

41. def s3Bucket: String

    

42. def s3BucketCommunity: String

    

43. def s3Path: String

    

44. def showAvailableAnnotators(folder: String = publicLoc): Unit

    

45. 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"

46. 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

47. 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

48. 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"

49. 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

50. 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

51. 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

52. def showString(list: List[String], resourceType: ResourceType): String

    

53. def showUnCategorizedResources(lang: String, version: String): Unit

    

54. def showUnCategorizedResources(lang: String): Unit

    

55. lazy val sparkVersion: Version

    

56. final def synchronized[T0](arg0: ⇒ T0): T0

    

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57. def toString(): String

    

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58. final def wait(): Unit

    

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

    

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60. final def wait(arg0: Long): Unit

    

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