Documentation ¶
Index ¶
- type BasePipeline
- type ClassificationOutput
- type Entity
- type FeatureExtractionOutput
- type FeatureExtractionPipeline
- func (p *FeatureExtractionPipeline) Postprocess(batch PipelineBatch) (*FeatureExtractionOutput, error)
- func (p *FeatureExtractionPipeline) Run(inputs []string) (PipelineBatchOutput, error)
- func (p *FeatureExtractionPipeline) RunPipeline(inputs []string) (*FeatureExtractionOutput, error)
- func (p *FeatureExtractionPipeline) Validate() error
- type FeatureExtractionPipelineConfig
- type Pipeline
- type PipelineBatch
- type PipelineBatchOutput
- type PipelineConfig
- type PipelineOption
- func WithIgnoreLabels(ignoreLabels []string) PipelineOption[*TokenClassificationPipeline]
- func WithMultiLabel() PipelineOption[*TextClassificationPipeline]
- func WithNormalization() PipelineOption[*FeatureExtractionPipeline]
- func WithSigmoid() PipelineOption[*TextClassificationPipeline]
- func WithSimpleAggregation() PipelineOption[*TokenClassificationPipeline]
- func WithSingleLabel() PipelineOption[*TextClassificationPipeline]
- func WithSoftmax() PipelineOption[*TextClassificationPipeline]
- func WithoutAggregation() PipelineOption[*TokenClassificationPipeline]
- type TextClassificationOption
- type TextClassificationOutput
- type TextClassificationPipeline
- func (p *TextClassificationPipeline) Forward(batch PipelineBatch) (PipelineBatch, error)
- func (p *TextClassificationPipeline) Postprocess(batch PipelineBatch) (*TextClassificationOutput, error)
- func (p *TextClassificationPipeline) Run(inputs []string) (PipelineBatchOutput, error)
- func (p *TextClassificationPipeline) RunPipeline(inputs []string) (*TextClassificationOutput, error)
- func (p *TextClassificationPipeline) Validate() error
- type TextClassificationPipelineConfig
- type Timings
- type TokenClassificationOutput
- type TokenClassificationPipeline
- func (p *TokenClassificationPipeline) Aggregate(input TokenizedInput, preEntities []Entity) ([]Entity, error)
- func (p *TokenClassificationPipeline) GatherPreEntities(input TokenizedInput, output [][]float32) []Entity
- func (p *TokenClassificationPipeline) GroupEntities(entities []Entity) ([]Entity, error)
- func (p *TokenClassificationPipeline) Postprocess(batch PipelineBatch) (*TokenClassificationOutput, error)
- func (p *TokenClassificationPipeline) Run(inputs []string) (PipelineBatchOutput, error)
- func (p *TokenClassificationPipeline) RunPipeline(inputs []string) (*TokenClassificationOutput, error)
- func (p *TokenClassificationPipeline) Validate() error
- type TokenClassificationPipelineConfig
- type TokenizedInput
Constants ¶
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Variables ¶
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Functions ¶
This section is empty.
Types ¶
type BasePipeline ¶
type BasePipeline struct { ModelPath string OnnxFilename string PipelineName string OrtSession *ort.DynamicAdvancedSession OrtOptions *ort.SessionOptions Tokenizer *tokenizers.Tokenizer TokenizerOptions []tokenizers.EncodeOption InputsMeta []ort.InputOutputInfo OutputsMeta []ort.InputOutputInfo OutputDim int TokenizerTimings *Timings PipelineTimings *Timings // contains filtered or unexported fields }
BasePipeline is a basic pipeline type used for struct composition in the other pipelines.
func (*BasePipeline) Destroy ¶
func (p *BasePipeline) Destroy() error
func (*BasePipeline) Forward ¶
func (p *BasePipeline) Forward(batch PipelineBatch) (PipelineBatch, error)
Forward pass of the neural network on the tokenized input
func (*BasePipeline) GetOutputDim ¶
func (p *BasePipeline) GetOutputDim() int
func (*BasePipeline) GetStats ¶
func (p *BasePipeline) GetStats() []string
func (*BasePipeline) Preprocess ¶
func (p *BasePipeline) Preprocess(inputs []string) PipelineBatch
Preprocess the input strings in the batch
type ClassificationOutput ¶
type FeatureExtractionOutput ¶
type FeatureExtractionOutput struct {
Embeddings [][]float32
}
func (*FeatureExtractionOutput) GetOutput ¶ added in v0.0.5
func (t *FeatureExtractionOutput) GetOutput() []any
type FeatureExtractionPipeline ¶
type FeatureExtractionPipeline struct { BasePipeline Normalization bool }
func NewFeatureExtractionPipeline ¶
func NewFeatureExtractionPipeline(config PipelineConfig[*FeatureExtractionPipeline], ortOptions *ort.SessionOptions) (*FeatureExtractionPipeline, error)
NewFeatureExtractionPipeline Initialize a feature extraction pipeline
func (*FeatureExtractionPipeline) Postprocess ¶
func (p *FeatureExtractionPipeline) Postprocess(batch PipelineBatch) (*FeatureExtractionOutput, error)
Postprocess Parse the results of the forward pass into the output. Token embeddings are mean pooled.
func (*FeatureExtractionPipeline) Run ¶
func (p *FeatureExtractionPipeline) Run(inputs []string) (PipelineBatchOutput, error)
Run the pipeline on a string batch
func (*FeatureExtractionPipeline) RunPipeline ¶ added in v0.0.6
func (p *FeatureExtractionPipeline) RunPipeline(inputs []string) (*FeatureExtractionOutput, error)
func (*FeatureExtractionPipeline) Validate ¶ added in v0.0.5
func (p *FeatureExtractionPipeline) Validate() error
type FeatureExtractionPipelineConfig ¶ added in v0.1.1
type PipelineBatch ¶
type PipelineBatchOutput ¶ added in v0.0.5
type PipelineBatchOutput interface {
GetOutput() []any
}
type PipelineConfig ¶ added in v0.0.9
type PipelineConfig[T Pipeline] struct { ModelPath string Name string OnnxFilename string Options []PipelineOption[T] }
type PipelineOption ¶ added in v0.0.9
type PipelineOption[T Pipeline] func(eo T)
func WithIgnoreLabels ¶
func WithIgnoreLabels(ignoreLabels []string) PipelineOption[*TokenClassificationPipeline]
func WithMultiLabel ¶ added in v0.0.9
func WithMultiLabel() PipelineOption[*TextClassificationPipeline]
func WithNormalization ¶ added in v0.1.1
func WithNormalization() PipelineOption[*FeatureExtractionPipeline]
func WithSigmoid ¶ added in v0.0.9
func WithSigmoid() PipelineOption[*TextClassificationPipeline]
func WithSimpleAggregation ¶
func WithSimpleAggregation() PipelineOption[*TokenClassificationPipeline]
func WithSingleLabel ¶ added in v0.0.9
func WithSingleLabel() PipelineOption[*TextClassificationPipeline]
func WithSoftmax ¶ added in v0.0.9
func WithSoftmax() PipelineOption[*TextClassificationPipeline]
func WithoutAggregation ¶
func WithoutAggregation() PipelineOption[*TokenClassificationPipeline]
type TextClassificationOption ¶
type TextClassificationOption func(eo *TextClassificationPipeline)
type TextClassificationOutput ¶
type TextClassificationOutput struct {
ClassificationOutputs [][]ClassificationOutput
}
func (*TextClassificationOutput) GetOutput ¶ added in v0.0.5
func (t *TextClassificationOutput) GetOutput() []any
type TextClassificationPipeline ¶
type TextClassificationPipeline struct { BasePipeline IdLabelMap map[int]string AggregationFunctionName string ProblemType string }
func NewTextClassificationPipeline ¶
func NewTextClassificationPipeline(config PipelineConfig[*TextClassificationPipeline], ortOptions *ort.SessionOptions) (*TextClassificationPipeline, error)
NewTextClassificationPipeline initializes a new text classification pipeline
func (*TextClassificationPipeline) Forward ¶
func (p *TextClassificationPipeline) Forward(batch PipelineBatch) (PipelineBatch, error)
func (*TextClassificationPipeline) Postprocess ¶
func (p *TextClassificationPipeline) Postprocess(batch PipelineBatch) (*TextClassificationOutput, error)
func (*TextClassificationPipeline) Run ¶
func (p *TextClassificationPipeline) Run(inputs []string) (PipelineBatchOutput, error)
Run the pipeline on a string batch
func (*TextClassificationPipeline) RunPipeline ¶ added in v0.0.6
func (p *TextClassificationPipeline) RunPipeline(inputs []string) (*TextClassificationOutput, error)
func (*TextClassificationPipeline) Validate ¶ added in v0.0.5
func (p *TextClassificationPipeline) Validate() error
type TokenClassificationOutput ¶
type TokenClassificationOutput struct {
Entities [][]Entity
}
func (*TokenClassificationOutput) GetOutput ¶ added in v0.0.5
func (t *TokenClassificationOutput) GetOutput() []any
type TokenClassificationPipeline ¶
type TokenClassificationPipeline struct { BasePipeline IdLabelMap map[int]string AggregationStrategy string IgnoreLabels []string }
func NewTokenClassificationPipeline ¶
func NewTokenClassificationPipeline(config PipelineConfig[*TokenClassificationPipeline], ortOptions *ort.SessionOptions) (*TokenClassificationPipeline, error)
NewTokenClassificationPipeline Initializes a feature extraction pipeline
func (*TokenClassificationPipeline) Aggregate ¶
func (p *TokenClassificationPipeline) Aggregate(input TokenizedInput, preEntities []Entity) ([]Entity, error)
func (*TokenClassificationPipeline) GatherPreEntities ¶
func (p *TokenClassificationPipeline) GatherPreEntities(input TokenizedInput, output [][]float32) []Entity
GatherPreEntities from batch of logits to list of pre-aggregated outputs
func (*TokenClassificationPipeline) GroupEntities ¶
func (p *TokenClassificationPipeline) GroupEntities(entities []Entity) ([]Entity, error)
GroupEntities group together adjacent tokens with the same entity predicted
func (*TokenClassificationPipeline) Postprocess ¶
func (p *TokenClassificationPipeline) Postprocess(batch PipelineBatch) (*TokenClassificationOutput, error)
Postprocess function for a token classification pipeline
func (*TokenClassificationPipeline) Run ¶
func (p *TokenClassificationPipeline) Run(inputs []string) (PipelineBatchOutput, error)
Run the pipeline on a string batch
func (*TokenClassificationPipeline) RunPipeline ¶ added in v0.0.6
func (p *TokenClassificationPipeline) RunPipeline(inputs []string) (*TokenClassificationOutput, error)
func (*TokenClassificationPipeline) Validate ¶ added in v0.0.5
func (p *TokenClassificationPipeline) Validate() error