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 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. final def eq(arg0: AnyRef): Boolean

    

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19. def equals(arg0: Any): Boolean

    

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20. val fileSystem: FileSystem

    

21. def finalize(): Unit

    

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

    

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23. def getDownloadSize(resourceRequest: ResourceRequest): String

    

24. def hashCode(): Int

    

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25. final def isInstanceOf[T0]: Boolean

    

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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

    

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36. final def notify(): Unit

    

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37. final def notifyAll(): Unit

    

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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

    

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58. def toString(): String

    

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59. final def wait(): Unit

    

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

    

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

    

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