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package llmc
import (
"fmt"
"os"
"path/filepath"
"runtime"
"go.jknobloc.com/x/dataset"
"go.jknobloc.com/x/llm"
)
func TokenizeAll(reader dataset.Reader, tok llm.Tokenizer, eot int) <-chan []uint32 {
texts := func(yield func(string) bool) {
for _, text := range reader.Texts() {
if !yield(text) {
return
}
}
}
return Pool(texts, max(1, runtime.NumCPU()-1), func(text string) []uint32 {
ids := tok.Tokenize(text)
tokens := make([]uint32, 0, len(ids)+1)
tokens = append(tokens, uint32(eot))
for _, id := range ids {
tokens = append(tokens, uint32(id))
}
return tokens
})
}
func WriteShards(path, name string, size int, docs <-chan []uint32) error {
if err := os.MkdirAll(path, os.ModePerm); err != nil {
return err
}
buffer := make([]uint32, 0, size)
shardIdx := 0
flush := func() error {
split := "train"
if shardIdx == 0 {
split = "val"
}
shardName := filepath.Join(path, fmt.Sprintf("%s_%s_%06d.bin", name, split, shardIdx))
d := DataFile[uint32]{
Model: GPT2,
Tokens: buffer,
}
if n, err := Serialize(&d, shardName); err != nil {
return err
} else {
fmt.Printf("wrote %s (%d tokens)\n", filepath.Base(shardName), n)
}
buffer = buffer[:0]
shardIdx++
return nil
}
for tokens := range docs {
for len(tokens) > 0 {
space := size - len(buffer)
if space >= len(tokens) {
buffer = append(buffer, tokens...)
break
}
buffer = append(buffer, tokens[:space]...)
tokens = tokens[space:] // carry remainder
if err := flush(); err != nil {
return err
}
}
}
if len(buffer) > 0 {
return flush()
}
return nil
}
|
