Files
ollama/convert/tokenizer.go
Daniel Hiltgen 56c735d871 runner: Remove CGO engines, use llama-server exclusively for GGML models
Remove the vendored GGML and llama.cpp backend, CGO runner, Go model
implementations, and sample.  llama-server (built from upstream llama.cpp via
FetchContent) is now the sole inference engine for GGUF-based models.
(Safetensor based models continue to run on the new MLX engine.)  This allows
us to more rapidly pick up new capabilities and fixes from llama.cpp as they
come out.

On windows this now requires recent AMD driver versions to support ROCm v7 as
llama.cpp currently does not support building against v6.
2026-04-20 08:44:02 -07:00

337 lines
7.7 KiB
Go

package convert
import (
"crypto/sha256"
"encoding/hex"
"encoding/json"
"errors"
"fmt"
"io/fs"
"log/slog"
"maps"
"os"
"slices"
"strings"
)
const (
_ int32 = iota
tokenTypeNormal
tokenTypeUnknown
tokenTypeControl
tokenTypeUserDefined
tokenTypeUnused
tokenTypeByte
)
type Tokenizer struct {
*Vocabulary
SpecialVocabulary []*SpecialVocabulary
Merges []string
Pre string
Template string
}
func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error) {
v, err := parseVocabulary(fsys)
if err != nil {
return nil, err
}
t := &Tokenizer{
Vocabulary: v,
Pre: "default",
}
addedTokens := make(map[string]token)
if f, err := fsys.Open("tokenizer.json"); errors.Is(err, os.ErrNotExist) {
} else if err != nil {
return nil, err
} else {
defer f.Close()
var tt tokenizer
if err := json.NewDecoder(f).Decode(&tt); err != nil {
return nil, err
}
for _, t := range tt.AddedTokens {
addedTokens[t.Content] = t
}
if len(tt.Model.Merges) == 0 {
// noop; merges is empty
} else if err := json.Unmarshal(tt.Model.Merges, &t.Merges); err == nil {
// noop; merges is []string
} else if merges, err := func() ([][]string, error) {
var merges [][]string
if err := json.Unmarshal(tt.Model.Merges, &merges); err != nil {
return nil, err
}
return merges, nil
}(); err == nil {
t.Merges = make([]string, len(merges))
for i := range merges {
t.Merges[i] = strings.Join(merges[i], " ")
}
} else {
return nil, fmt.Errorf("could not parse tokenizer merges. expected []string or [][]string: %w", err)
}
sha256sum := sha256.New()
for _, pt := range tt.PreTokenizer.PreTokenizers {
switch pt.Type {
case "Split":
if pt.Pattern.Regex != "" {
// create a checksum of all Split pretokenizers which should be sufficient
// to identify the pretokenizer
sha256sum.Write([]byte(pt.Pattern.Regex))
}
}
}
switch digest := hex.EncodeToString(sha256sum.Sum(nil)); digest {
case "d98f9631be1e9607a9848c26c1f9eac1aa9fc21ac6ba82a2fc0741af9780a48f":
t.Pre = "llama-bpe"
case "03df5c5863ad70781dcfdef491ead25140f895fe8010964be0daefe27be32b02":
t.Pre = "deepseek-llm"
case "21cde974d587f0d54dc8d56b183cc1e6239600172035c68fbd6d4b9f8da0576e":
t.Pre = "deepseek-coder"
case "1ff7f41064896984db5d1bb6ff64fa4bc29007d08c1b439e505b7392777a319e":
t.Pre = "qwen2"
case "00431aed57e696b747435f734d1e3b9b1bfd931a121fb5cac7129e97c181e9ba":
t.Pre = "qwen35"
case "2d1b8dc11e89af71459b36004f698ab3693f59fd84f63e8ec2b49564ab857420":
t.Pre = "gpt-4o"
case "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855":
// noop, empty pretokenizer
default:
slog.Warn("unknown pretokenizer, using default", "digest", digest)
}
}
if f, err := fsys.Open("tokenizer_config.json"); errors.Is(err, os.ErrNotExist) {
// noop
} else if err != nil {
return nil, err
} else {
defer f.Close()
var p map[string]json.RawMessage
if err := json.NewDecoder(f).Decode(&p); err != nil {
return nil, err
}
if template, ok := p["chat_template"]; ok {
var s []struct {
Name string `json:"name"`
Template string `json:"template"`
}
if err := json.Unmarshal(template, &t.Template); err == nil {
// noop
} else if err := json.Unmarshal(template, &s); err == nil {
for _, e := range s {
if e.Name == "default" {
t.Template = e.Template
break
}
}
} else {
return nil, fmt.Errorf("invalid chat_template: %w", err)
}
}
for _, st := range specialTokenTypes {
sv := SpecialVocabulary{Type: st}
if bts, ok := p[fmt.Sprintf("add_%s_token", st)]; ok {
if err := json.Unmarshal(bts, &sv.AddToken); err != nil {
return nil, err
}
}
if bts, ok := p[fmt.Sprintf("%s_token", st)]; ok {
var content string
if err := json.Unmarshal(bts, &content); err != nil {
var mm map[string]any
if err := json.Unmarshal(bts, &mm); err != nil {
continue
}
content, ok = mm["content"].(string)
if !ok {
continue
}
}
sv.Content = content
}
if id, ok := addedTokens[sv.Content]; ok {
sv.ID = id.ID
t.SpecialVocabulary = append(t.SpecialVocabulary, &sv)
}
}
}
if f, err := fsys.Open("generation_config.json"); errors.Is(err, os.ErrNotExist) {
} else if err != nil {
return nil, err
} else {
defer f.Close()
var p map[string]json.RawMessage
if err := json.NewDecoder(f).Decode(&p); err != nil {
return nil, err
}
for _, st := range specialTokenTypes {
if bts, ok := p[fmt.Sprintf("%s_token_id", st)]; ok {
var ids []int32
if err := json.Unmarshal(bts, &ids); err != nil {
// value is not a list so the existing ID is used
continue
}
if i := slices.IndexFunc(t.SpecialVocabulary, func(sv *SpecialVocabulary) bool {
return sv.Type == st
}); i >= 0 {
t.SpecialVocabulary[i].IDs = ids
}
}
}
}
return t, nil
}
type tokenizer struct {
AddedTokens []token `json:"added_tokens"`
Model struct {
Type string `json:"type"`
Vocab map[string]int `json:"vocab"`
Merges json.RawMessage `json:"merges"`
} `json:"model"`
PreTokenizer struct {
PreTokenizers []struct {
Type string `json:"type"`
Behavior string `json:"behavior"`
Invert bool `json:"invert"`
AddPrefixSpace bool `json:"add_prefix_space"`
TrimOffsets bool `json:"trim_offsets"`
UseRegex bool `json:"use_regex"`
Pattern struct {
Regex string `json:"Regex"`
} `json:"pattern"`
} `json:"pretokenizers"`
} `json:"pre_tokenizer"`
}
type token struct {
ID int `json:"id"`
Content string `json:"content"`
Special bool `json:"special"`
UserDefined bool
}
type Vocabulary struct {
Model string
Tokens []string
Scores []float32
Types []int32
}
func parseVocabularyFromTokenizer(fsys fs.FS) (*Vocabulary, error) {
f, err := fsys.Open("tokenizer.json")
if err != nil {
return nil, err
}
defer f.Close()
var t tokenizer
if err := json.NewDecoder(f).Decode(&t); err != nil {
return nil, err
}
tokens := make(map[int]token, len(t.Model.Vocab))
for k, v := range t.Model.Vocab {
tokens[v] = token{
ID: v,
Content: k,
}
}
for _, token := range t.AddedTokens {
token.UserDefined = true
tokens[token.ID] = token
}
v := Vocabulary{Model: "gpt2"}
for _, k := range slices.Sorted(maps.Keys(tokens)) {
token := tokens[k]
v.Tokens = append(v.Tokens, token.Content)
v.Scores = append(v.Scores, float32(token.ID))
switch {
case token.Special:
v.Types = append(v.Types, tokenTypeControl)
case token.UserDefined:
v.Types = append(v.Types, tokenTypeUserDefined)
default:
v.Types = append(v.Types, tokenTypeNormal)
}
}
return &v, nil
}
func parseVocabulary(fsys fs.FS) (*Vocabulary, error) {
patterns := []struct {
Pattern string
Func func(fs.FS) (*Vocabulary, error)
}{
{"tokenizer.model", parseSentencePiece},
{"tokenizer.json", parseVocabularyFromTokenizer},
}
for _, pattern := range patterns {
if _, err := fs.Stat(fsys, pattern.Pattern); errors.Is(err, os.ErrNotExist) {
continue
} else if err != nil {
return nil, err
}
return pattern.Func(fsys)
}
return nil, errors.New("unknown tokenizer format")
}
type SpecialVocabulary struct {
Type string
ID int
Content string
AddToken bool
// IDs is populated by generation_config.json
IDs []int32
}
func (sv SpecialVocabulary) Key() string {
switch t := sv.Type; t {
case "bos", "eos", "cls", "mask":
return t
case "unk":
return "unknown"
case "sep":
//nolint:misspell // this is an upstream typo
return "seperator"
case "pad":
return "padding"
}
panic("unknown special vocabulary type")
}