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hugot.go
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hugot.go
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package hugot
import (
"context"
"errors"
"fmt"
"slices"
util "github.com/knights-analytics/hugot/utils"
ort "github.com/yalue/onnxruntime_go"
"github.com/knights-analytics/hugot/pipelines"
)
// Session allows for the creation of new pipelines and holds the pipeline already created.
type Session struct {
featureExtractionPipelines pipelineMap[*pipelines.FeatureExtractionPipeline]
tokenClassificationPipelines pipelineMap[*pipelines.TokenClassificationPipeline]
textClassificationPipelines pipelineMap[*pipelines.TextClassificationPipeline]
zeroShotClassificationPipelines pipelineMap[*pipelines.ZeroShotClassificationPipeline]
ortOptions *ort.SessionOptions
}
type pipelineMap[T pipelines.Pipeline] map[string]T
func (m pipelineMap[T]) Destroy() error {
var err error
for _, p := range m {
err = p.Destroy()
}
return err
}
func (m pipelineMap[T]) GetStats() []string {
var stats []string
for _, p := range m {
stats = append(stats, p.GetStats()...)
}
return stats
}
// FeatureExtractionConfig is the configuration for a feature extraction pipeline
type FeatureExtractionConfig = pipelines.PipelineConfig[*pipelines.FeatureExtractionPipeline]
// FeatureExtractionOption is an option for a feature extraction pipeline
type FeatureExtractionOption = pipelines.PipelineOption[*pipelines.FeatureExtractionPipeline]
// TextClassificationConfig is the configuration for a text classification pipeline
type TextClassificationConfig = pipelines.PipelineConfig[*pipelines.TextClassificationPipeline]
// type ZSCConfig = pipelines.PipelineConfig[*pipelines.ZeroShotClassificationPipeline]
type ZeroShotClassificationConfig = pipelines.PipelineConfig[*pipelines.ZeroShotClassificationPipeline]
// TextClassificationOption is an option for a text classification pipeline
type TextClassificationOption = pipelines.PipelineOption[*pipelines.TextClassificationPipeline]
// TokenClassificationConfig is the configuration for a token classification pipeline
type TokenClassificationConfig = pipelines.PipelineConfig[*pipelines.TokenClassificationPipeline]
// TokenClassificationOption is an option for a token classification pipeline
type TokenClassificationOption = pipelines.PipelineOption[*pipelines.TokenClassificationPipeline]
// NewSession is the main entrypoint to hugot and is used to create a new hugot session object.
// ortLibraryPath should be the path to onnxruntime.so. If it's the empty string, hugot will try
// to load the library from the default location (/usr/lib/onnxruntime.so).
// A new session must be destroyed when it's not needed any more to avoid memory leaks. See the Destroy method.
// Note moreover that there can be at most one hugot session active (i.e., the Session object is a singleton),
// otherwise NewSession will return an error.
func NewSession(options ...WithOption) (*Session, error) {
if ort.IsInitialized() {
return nil, errors.New("another session is currently active, and only one session can be active at one time")
}
session := &Session{
featureExtractionPipelines: map[string]*pipelines.FeatureExtractionPipeline{},
textClassificationPipelines: map[string]*pipelines.TextClassificationPipeline{},
tokenClassificationPipelines: map[string]*pipelines.TokenClassificationPipeline{},
zeroShotClassificationPipelines: map[string]*pipelines.ZeroShotClassificationPipeline{},
}
// set session options and initialise
if initialised, err := session.initialiseORT(options...); err != nil {
if initialised {
destroyErr := session.Destroy()
return nil, errors.Join(err, destroyErr)
}
return nil, err
}
return session, nil
}
func (s *Session) initialiseORT(options ...WithOption) (bool, error) {
// Collect options into a struct, so they can be applied in the correct order later
o := &ortOptions{}
for _, option := range options {
option(o)
}
// Set pre-initialisation options
if o.libraryPath != "" {
ortPathExists, err := util.FileSystem.Exists(context.Background(), o.libraryPath)
if err != nil {
return false, err
}
if !ortPathExists {
return false, fmt.Errorf("cannot find the ort library at: %s", o.libraryPath)
}
ort.SetSharedLibraryPath(o.libraryPath)
}
// Start OnnxRuntime
if err := ort.InitializeEnvironment(); err != nil {
return false, err
}
if o.telemetry {
if err := ort.EnableTelemetry(); err != nil {
return true, err
}
} else {
if err := ort.DisableTelemetry(); err != nil {
return true, err
}
}
// Create session options for use in all pipelines
sessionOptions, optionsError := ort.NewSessionOptions()
if optionsError != nil {
return true, optionsError
}
s.ortOptions = sessionOptions
if o.intraOpNumThreads != 0 {
if err := sessionOptions.SetIntraOpNumThreads(o.intraOpNumThreads); err != nil {
return true, err
}
}
if o.interOpNumThreads != 0 {
if err := sessionOptions.SetInterOpNumThreads(o.interOpNumThreads); err != nil {
return true, err
}
}
if o.cpuMemArenaSet {
if err := sessionOptions.SetCpuMemArena(o.cpuMemArena); err != nil {
return true, err
}
}
if o.memPatternSet {
if err := sessionOptions.SetMemPattern(o.memPattern); err != nil {
return true, err
}
}
if o.cudaOptionsSet {
cudaOptions, optErr := ort.NewCUDAProviderOptions()
if optErr != nil {
return true, optErr
}
if len(o.cudaOptions) > 0 {
optErr = cudaOptions.Update(o.cudaOptions)
if optErr != nil {
return true, optErr
}
}
if err := sessionOptions.AppendExecutionProviderCUDA(cudaOptions); err != nil {
return true, err
}
}
if o.coreMLOptionsSet {
if err := sessionOptions.AppendExecutionProviderCoreML(o.coreMLOptions); err != nil {
return true, err
}
}
if o.directMLOptionsSet {
if err := sessionOptions.AppendExecutionProviderDirectML(o.directMLOptions); err != nil {
return true, err
}
}
if o.openVINOOptionsSet {
if err := sessionOptions.AppendExecutionProviderOpenVINO(o.openVINOOptions); err != nil {
return true, err
}
}
if o.tensorRTOptionsSet {
tensorRTOptions, optErr := ort.NewTensorRTProviderOptions()
if optErr != nil {
return true, optErr
}
if len(o.cudaOptions) > 0 {
optErr = tensorRTOptions.Update(o.tensorRTOptions)
if optErr != nil {
return true, optErr
}
}
if err := sessionOptions.AppendExecutionProviderTensorRT(tensorRTOptions); err != nil {
return true, err
}
}
return true, nil
}
type pipelineNotFoundError struct {
pipelineName string
}
func (e *pipelineNotFoundError) Error() string {
return fmt.Sprintf("Pipeline with name %s not found", e.pipelineName)
}
// NewPipeline can be used to create a new pipeline of type T. The initialised pipeline will be returned and it
// will also be stored in the session object so that all created pipelines can be destroyed with session.Destroy()
// at once.
func NewPipeline[T pipelines.Pipeline](s *Session, pipelineConfig pipelines.PipelineConfig[T]) (T, error) {
var pipeline T
var err error
if pipelineConfig.Name == "" {
return pipeline, errors.New("a name for the pipeline is required")
}
_, getError := GetPipeline[T](s, pipelineConfig.Name)
var notFoundError *pipelineNotFoundError
if getError == nil {
return pipeline, fmt.Errorf("pipeline %s has already been initialised", pipelineConfig.Name)
} else if !errors.As(getError, ¬FoundError) {
return pipeline, getError
}
switch any(pipeline).(type) {
case *pipelines.TokenClassificationPipeline:
config := any(pipelineConfig).(pipelines.PipelineConfig[*pipelines.TokenClassificationPipeline])
pipelineInitialised, err := pipelines.NewTokenClassificationPipeline(config, s.ortOptions)
if err != nil {
return pipeline, err
}
s.tokenClassificationPipelines[config.Name] = pipelineInitialised
pipeline = any(pipelineInitialised).(T)
case *pipelines.TextClassificationPipeline:
config := any(pipelineConfig).(pipelines.PipelineConfig[*pipelines.TextClassificationPipeline])
pipelineInitialised, err := pipelines.NewTextClassificationPipeline(config, s.ortOptions)
if err != nil {
return pipeline, err
}
s.textClassificationPipelines[config.Name] = pipelineInitialised
pipeline = any(pipelineInitialised).(T)
case *pipelines.FeatureExtractionPipeline:
config := any(pipelineConfig).(pipelines.PipelineConfig[*pipelines.FeatureExtractionPipeline])
pipelineInitialised, err := pipelines.NewFeatureExtractionPipeline(config, s.ortOptions)
if err != nil {
return pipeline, err
}
s.featureExtractionPipelines[config.Name] = pipelineInitialised
pipeline = any(pipelineInitialised).(T)
case *pipelines.ZeroShotClassificationPipeline:
config := any(pipelineConfig).(pipelines.PipelineConfig[*pipelines.ZeroShotClassificationPipeline])
pipelineInitialised, err := pipelines.NewZeroShotClassificationPipeline(config, s.ortOptions)
if err != nil {
return pipeline, err
}
s.zeroShotClassificationPipelines[config.Name] = pipelineInitialised
pipeline = any(pipelineInitialised).(T)
default:
return pipeline, fmt.Errorf("not implemented")
}
return pipeline, err
}
// GetPipeline can be used to retrieve a pipeline of type T with the given name from the session
func GetPipeline[T pipelines.Pipeline](s *Session, name string) (T, error) {
var pipeline T
switch any(pipeline).(type) {
case *pipelines.TokenClassificationPipeline:
p, ok := s.tokenClassificationPipelines[name]
if !ok {
return pipeline, &pipelineNotFoundError{pipelineName: name}
}
return any(p).(T), nil
case *pipelines.TextClassificationPipeline:
p, ok := s.textClassificationPipelines[name]
if !ok {
return pipeline, &pipelineNotFoundError{pipelineName: name}
}
return any(p).(T), nil
case *pipelines.FeatureExtractionPipeline:
p, ok := s.featureExtractionPipelines[name]
if !ok {
return pipeline, &pipelineNotFoundError{pipelineName: name}
}
return any(p).(T), nil
case *pipelines.ZeroShotClassificationPipeline:
p, ok := s.zeroShotClassificationPipelines[name]
if !ok {
return pipeline, &pipelineNotFoundError{pipelineName: name}
}
return any(p).(T), nil
default:
return pipeline, errors.New("pipeline type not supported")
}
}
// Destroy deletes the hugot session and onnxruntime environment and all initialized pipelines, freeing memory.
// A hugot session should be destroyed when not neeeded any more, preferably with a defer() call.
func (s *Session) Destroy() error {
return errors.Join(
s.featureExtractionPipelines.Destroy(),
s.tokenClassificationPipelines.Destroy(),
s.textClassificationPipelines.Destroy(),
s.zeroShotClassificationPipelines.Destroy(),
s.ortOptions.Destroy(),
ort.DestroyEnvironment(),
)
}
// GetStats returns runtime statistics for all initialized pipelines for profiling purposes. We currently record for each pipeline:
// the total runtime of the tokenization step
// the number of batch calls to the tokenization step
// the average time per tokenization batch call
// the total runtime of the inference (i.e. onnxruntime) step
// the number of batch calls to the onnxruntime inference
// the average time per onnxruntime inference batch call
func (s *Session) GetStats() []string {
// slices.Concat() is not implemented in experimental x/exp/slices package
return slices.Concat(
s.tokenClassificationPipelines.GetStats(),
s.textClassificationPipelines.GetStats(),
s.featureExtractionPipelines.GetStats(),
s.zeroShotClassificationPipelines.GetStats(),
)
}