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package llm
import (
"fmt"
"sync"
"time"
"go.jknobloc.com/x/dataset"
"go.jknobloc.com/x/tui"
)
func (e *Evaluator[R]) Run(title string, data dataset.Reader, window, stride int) error {
devices := make([]int, len(e.models))
for i := range len(devices) {
devices[i] = i
}
devicePool := newPool(devices...)
var wg sync.WaitGroup
for range e.numWorkers {
wg.Add(1)
go func() {
defer wg.Done()
for b := range e.jobs {
device := devicePool.Acquire()
func() {
defer devicePool.Release(device)
defer func() {
if r := recover(); r != nil {
fmt.Println("HOUSTON") // TODO handle
}
}()
e.execute(&b, device)
}()
e.completed.Add(int64(b.Size()))
}
}()
}
pb := tui.NewProgressBar(title, 20, 0, time.Now())
pb.Start(1*time.Second, func() int {
return int(e.completed.Load())
})
s := 0 // skipped
n := 0 // total
defer func() {
fmt.Printf("skipped %d of %d texts\n", s, n)
}()
defer pb.Close()
for d := range data.Texts("text") {
tokens := toInt64(e.tokenizer.Tokenize(d))
if len(tokens) == 0 {
n++
s++
continue
}
e.schedule(n, tokens, window, stride, e.batchSize)
pb.SetTotal(pb.Total() + e.estimateJobs(tokens, window, stride))
n++
}
close(e.jobs)
wg.Wait()
close(e.results)
return nil
}
func (e *Evaluator[R]) estimateJobs(tokens []int64, window, stride int) int {
if len(tokens) < window {
return 0
}
windows := ((len(tokens) - window) / stride) + 1
// jobs := (windows + batchSize - 1) / e.batchSize
return windows
}
func (e *Evaluator[R]) schedule(uid int, tokens []int64, contextSize, stride, batchSize int) {
b := newBatch(batchSize)
seen := 1 // first token as context
n := 0
// for i := 0; i+contextSize <= len(tokens); i += stride {
for i := 0; i < len(tokens); i += stride {
if b.Size() == batchSize {
e.jobs <- *b
b = newBatch(batchSize)
}
j := min(i+contextSize, len(tokens))
if j-i < contextSize {
break // don't add jobs with partial windows
}
// if j < seen {
// break // don't add jobs with no new tokens
// }
b.AddJob(Job{
Document: uid,
Position: n,
Tokens: tokens[i:j],
Seen: seen - i,
})
seen = i + contextSize
n++
}
if b.Size() > 0 {
e.jobs <- *b
}
e.scheduled.Add(int64(n))
}
func (e *Evaluator[R]) execute(j *batch, device int) {
if j.Size() != 1 {
panic("unimplemented")
}
job := j.jobs[0]
if job.Seen < 1 {
panic("empty context")
}
m := e.models[device]
logits := make([][]float32, 0, len(job.Tokens))
if _, err := m.Generate(job.Tokens, 0, &logits); err != nil {
panic(err) // TODO handle
}
l := logits[job.Seen-1 : len(logits)-1]
t := toInt(job.Tokens[job.Seen:])
r := e.callback(job, l, t)
e.results <- r
return
}
|
