Files
ollama/convert/tokenizer_test.go
2026-02-24 20:08:05 -08:00

426 lines
9.7 KiB
Go

package convert
import (
"io"
"io/fs"
"os"
"path/filepath"
"strings"
"testing"
"github.com/google/go-cmp/cmp"
)
func createTokenizerFS(t *testing.T, dir string, files map[string]io.Reader) fs.FS {
t.Helper()
for k, v := range files {
if err := func() error {
f, err := os.Create(filepath.Join(dir, k))
if err != nil {
return err
}
defer f.Close()
if _, err := io.Copy(f, v); err != nil {
return err
}
return nil
}(); err != nil {
t.Fatalf("unexpected error: %v", err)
}
}
return os.DirFS(dir)
}
func TestParseTokenizer(t *testing.T) {
cases := []struct {
name string
fsys fs.FS
specialTokenTypes []string
want *Tokenizer
}{
{
name: "string chat template",
fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
"tokenizer.json": strings.NewReader(`{}`),
"tokenizer_config.json": strings.NewReader(`{
"chat_template": "<default template>"
}`),
}),
want: &Tokenizer{
Vocabulary: &Vocabulary{Model: "gpt2"},
Pre: "default",
Template: "<default template>",
},
},
{
name: "list chat template",
fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
"tokenizer.json": strings.NewReader(`{}`),
"tokenizer_config.json": strings.NewReader(`{
"chat_template": [
{
"name": "default",
"template": "<default template>"
},
{
"name": "tools",
"template": "<tools template>"
}
]
}`),
}),
want: &Tokenizer{
Vocabulary: &Vocabulary{Model: "gpt2"},
Pre: "default",
Template: "<default template>",
},
},
{
name: "added tokens",
fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
"tokenizer.json": strings.NewReader(`{
"added_tokens": [
{
"id": 999,
"content": "<unused999>",
"special": false
}
]
}`),
}),
want: &Tokenizer{
Vocabulary: &Vocabulary{
Model: "gpt2",
Tokens: []string{"<unused999>"},
Scores: []float32{999},
Types: []int32{4},
},
Pre: "default",
},
},
{
name: "added tokens overlap vocab",
fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
"tokenizer.json": strings.NewReader(`{
"added_tokens": [
{
"id": 0,
"content": "<pad>",
"special": true
}
],
"model": {
"vocab": {
"<pad>": 0
}
}
}`),
}),
want: &Tokenizer{
Vocabulary: &Vocabulary{
Model: "gpt2",
Tokens: []string{"<pad>"},
Scores: []float32{0},
Types: []int32{3},
},
Pre: "default",
},
},
{
name: "special token types",
fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
"tokenizer.json": strings.NewReader(`{
"added_tokens": [
{
"id": 0,
"content": "<pad>",
"special": true
},
{
"id": 1,
"content": "<eos>",
"special": true
},
{
"id": 2,
"content": "<bos>",
"special": true
},
{
"id": 3,
"content": "<unk>",
"special": true
}
],
"model": {
"vocab": {
"<pad>": 0,
"<eos>": 1,
"<bos>": 2,
"<unk>": 3
}
}
}`),
"tokenizer_config.json": strings.NewReader(`{
"add_bos_token": true,
"add_eos_token": false,
"bos_token": "<bos>",
"eos_token": "<eos>",
"pad_token": "<pad>",
"unk_token": "<unk>"
}`),
}),
specialTokenTypes: []string{"pad", "eos", "bos", "unk"},
want: &Tokenizer{
Vocabulary: &Vocabulary{
Model: "gpt2",
Tokens: []string{"<pad>", "<eos>", "<bos>", "<unk>"},
Scores: []float32{0, 1, 2, 3},
Types: []int32{3, 3, 3, 3},
},
SpecialVocabulary: []*SpecialVocabulary{
{Type: "pad", Content: "<pad>", ID: 0, AddToken: false},
{Type: "eos", Content: "<eos>", ID: 1, AddToken: false},
{Type: "bos", Content: "<bos>", ID: 2, AddToken: true},
{Type: "unk", Content: "<unk>", ID: 3, AddToken: false},
},
Pre: "default",
},
},
{
name: "llama-bpe pretokenizer and control tokens",
fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
"tokenizer.json": strings.NewReader(`{
"added_tokens": [
{"id": 1, "content": "<|startoftext|>", "special": true},
{"id": 6, "content": "<|im_start|>", "special": true},
{"id": 7, "content": "<|im_end|>", "special": true},
{"id": 8, "content": "<|tool_list_start|>", "special": true},
{"id": 9, "content": "<|tool_list_end|>", "special": true},
{"id": 10, "content": "<|tool_call_start|>", "special": true},
{"id": 11, "content": "<|tool_call_end|>", "special": true},
{"id": 12, "content": "<|tool_response_start|>", "special": true},
{"id": 13, "content": "<|tool_response_end|>", "special": true},
{"id": 396, "content": "<image>", "special": true},
{"id": 64400, "content": "<think>", "special": true},
{"id": 64401, "content": "</think>", "special": true}
],
"model": {
"vocab": {
"<|startoftext|>": 1,
"<|im_start|>": 6,
"<|im_end|>": 7,
"<|tool_list_start|>": 8,
"<|tool_list_end|>": 9,
"<|tool_call_start|>": 10,
"<|tool_call_end|>": 11,
"<|tool_response_start|>": 12,
"<|tool_response_end|>": 13,
"<image>": 396,
"<think>": 64400,
"</think>": 64401
}
},
"pre_tokenizer": {
"type": "Sequence",
"pretokenizers": [
{
"type": "Split",
"pattern": {
"Regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+"
},
"behavior": "Isolated",
"invert": false
},
{
"type": "ByteLevel",
"add_prefix_space": false,
"trim_offsets": true,
"use_regex": false
}
]
}
}`),
}),
want: &Tokenizer{
Vocabulary: &Vocabulary{
Model: "gpt2",
Tokens: []string{
"<|startoftext|>",
"<|im_start|>",
"<|im_end|>",
"<|tool_list_start|>",
"<|tool_list_end|>",
"<|tool_call_start|>",
"<|tool_call_end|>",
"<|tool_response_start|>",
"<|tool_response_end|>",
"<image>",
"<think>",
"</think>",
},
Scores: []float32{1, 6, 7, 8, 9, 10, 11, 12, 13, 396, 64400, 64401},
Types: []int32{3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3},
},
Pre: "llama-bpe",
},
},
{
name: "list string merges",
fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
"tokenizer.json": strings.NewReader(`{
"model": {
"merges": [
"a b",
"c d",
"e f"
]
}
}`),
}),
want: &Tokenizer{
Vocabulary: &Vocabulary{
Model: "gpt2",
},
Merges: []string{
"a b",
"c d",
"e f",
},
Pre: "default",
},
},
{
name: "list list string merges",
fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
"tokenizer.json": strings.NewReader(`{
"model": {
"merges": [
[
"a", "b"
],
[
"c", "d"
],
[
"e", "f"
]
]
}
}`),
}),
want: &Tokenizer{
Vocabulary: &Vocabulary{
Model: "gpt2",
},
Merges: []string{
"a b",
"c d",
"e f",
},
Pre: "default",
},
},
{
name: "generation config eos token ids",
fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
"tokenizer.json": strings.NewReader(`{
"added_tokens": [
{
"id": 0,
"content": "<bos>",
"special": true
},
{
"id": 1,
"content": "<eos>",
"special": true
},
{
"id": 2,
"content": "<eot>",
"special": true
},
{
"id": 3,
"content": "<eom>",
"special": true
}
],
"model": {
"vocab": {
"<bos>": 0,
"<eos>": 1,
"<eot>": 2,
"<eom>": 3
}
}
}`),
"tokenizer_config.json": strings.NewReader(`{
"add_bos_token": true,
"add_eos_token": false,
"bos_token": "<bos>",
"eos_token": "<eos>"
}`),
"generation_config.json": strings.NewReader(`{
"bos_token_id": 0,
"eos_token_id": [1, 2, 3]
}`),
}),
specialTokenTypes: []string{"pad", "eos", "bos", "unk"},
want: &Tokenizer{
Vocabulary: &Vocabulary{
Model: "gpt2",
Tokens: []string{"<bos>", "<eos>", "<eot>", "<eom>"},
Scores: []float32{0, 1, 2, 3},
Types: []int32{3, 3, 3, 3},
},
SpecialVocabulary: []*SpecialVocabulary{
{Type: "eos", Content: "<eos>", ID: 1, IDs: []int32{1, 2, 3}, AddToken: false},
{Type: "bos", Content: "<bos>", ID: 0, AddToken: true},
},
Pre: "default",
},
},
{
name: "qwen35 pretokenizer",
fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
"tokenizer.json": strings.NewReader(`{
"pre_tokenizer": {
"type": "Sequence",
"pretokenizers": [
{
"type": "Split",
"pattern": {
"Regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+"
}
}
]
}
}`),
}),
want: &Tokenizer{
Vocabulary: &Vocabulary{Model: "gpt2"},
Pre: "qwen35",
},
},
}
for _, tt := range cases {
t.Run(tt.name, func(t *testing.T) {
tokenizer, err := parseTokenizer(tt.fsys, tt.specialTokenTypes)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if diff := cmp.Diff(tt.want, tokenizer); diff != "" {
t.Errorf("unexpected tokenizer (-want +got):\n%s", diff)
}
})
}
}