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tokenizer: add SentencePiece-style BPE support (#15162)
* tokenizer: add SentencePiece-style BPE support Add WithSentencePieceNormalizer option to BytePairEncoding for models that use BPE with SentencePiece-style space markers (space to/from U+2581). NewBytePairEncoding is unchanged; the new NewBytePairEncodingWithOptions constructor accepts BPEOption functions. Decoding handles the reverse mapping of U+2581 back to spaces. * review comments
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@@ -14,20 +14,40 @@ import (
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)
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type BytePairEncoding struct {
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vocab *Vocabulary
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regexps []*regexp2.Regexp
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vocab *Vocabulary
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regexps []*regexp2.Regexp
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spaceToSpmSep bool // When true, normalize spaces to ▁ instead of GPT-2 byte-level encoding
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}
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var _ Tokenizer = (*BytePairEncoding)(nil)
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// BPEOption configures BytePairEncoding behavior
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type BPEOption func(*BytePairEncoding)
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// WithSentencePieceNormalizer enables ▁ space normalization instead of GPT-2 byte-level encoding.
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func WithSentencePieceNormalizer() BPEOption {
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return func(bpe *BytePairEncoding) {
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bpe.spaceToSpmSep = true
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}
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}
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func NewBytePairEncoding(vocab *Vocabulary, pretokenizer ...string) BytePairEncoding {
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return newBytePairEncoding(vocab, pretokenizer)
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}
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func NewBytePairEncodingWithOptions(vocab *Vocabulary, pretokenizer []string, opts ...BPEOption) BytePairEncoding {
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bpe := newBytePairEncoding(vocab, pretokenizer, opts...)
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return bpe
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}
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func newBytePairEncoding(vocab *Vocabulary, pretokenizer []string, opts ...BPEOption) BytePairEncoding {
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if len(pretokenizer) == 0 {
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// set default byte-level pretokenizer if none provided, e.g.
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// https://github.com/huggingface/tokenizer/blob/main/tokenizer/src/pre_tokenizer/byte_level.rs#L44
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pretokenizer = []string{`'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+`}
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}
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return BytePairEncoding{
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bpe := BytePairEncoding{
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vocab: vocab,
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regexps: slices.Collect(func(yield func(*regexp2.Regexp) bool) {
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for _, p := range pretokenizer {
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@@ -37,6 +57,12 @@ func NewBytePairEncoding(vocab *Vocabulary, pretokenizer ...string) BytePairEnco
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}
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}),
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}
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for _, opt := range opts {
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opt(&bpe)
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}
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return bpe
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}
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func (bpe BytePairEncoding) Vocabulary() *Vocabulary {
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@@ -136,28 +162,35 @@ func (bpe BytePairEncoding) Encode(s string, addSpecial bool) ([]int32, error) {
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for split := range bpe.split(frag.value) {
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// TODO: process splits concurrently
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var sb strings.Builder
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for _, b := range []byte(split) {
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r := rune(b)
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switch {
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case r == 0x00ad:
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r = 0x0143
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case r <= 0x0020:
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r = r + 0x0100
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case r >= 0x007f && r <= 0x00a0:
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r = r + 0x00a2
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var normalized string
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if bpe.spaceToSpmSep {
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// SentencePiece-style: replace spaces with ▁
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normalized = strings.ReplaceAll(split, " ", spmWhitespaceSep)
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} else {
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// GPT-2 byte-level: map bytes to shifted Unicode codepoints
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var sb strings.Builder
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for _, b := range []byte(split) {
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r := rune(b)
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switch {
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case r == 0x00ad:
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r = 0x0143
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case r <= 0x0020:
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r = r + 0x0100
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case r >= 0x007f && r <= 0x00a0:
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r = r + 0x00a2
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}
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sb.WriteRune(r)
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}
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sb.WriteRune(r)
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normalized = sb.String()
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}
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// short circuit if the fragment is in the vocabulary
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if id := bpe.vocab.Encode(sb.String()); id >= 0 {
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if id := bpe.vocab.Encode(normalized); id >= 0 {
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ids = append(ids, id)
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continue
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}
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runes := []rune(sb.String())
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runes := []rune(normalized)
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merges := make([]merge, len(runes))
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for r := range runes {
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merges[r] = merge{
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@@ -257,6 +290,8 @@ func (bpe BytePairEncoding) Decode(ids []int32) (string, error) {
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var sb strings.Builder
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for _, id := range ids {
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for _, r := range bpe.vocab.Decode(id) {
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// GPT-2 byte-level BPE uses Unicode chars in the 0x0100-0x0143
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// range to represent bytes. Remap them back to actual bytes.
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switch {
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case r == 0x0100:
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// this produces 0x00 aka NULL
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@@ -267,6 +302,15 @@ func (bpe BytePairEncoding) Decode(ids []int32) (string, error) {
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r = r - 0x0100
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case r > 0x0120 && r <= 0x0142:
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r = r - 0x00a2
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case r > 0x0143:
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// Non-GPT2 rune (e.g., SentencePiece-style BPE).
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// Handle ▁ as word separator, otherwise write the rune as-is.
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if r == 0x2581 { // ▁ (LOWER ONE EIGHTH BLOCK)
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sb.WriteByte(' ')
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} else {
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sb.WriteRune(r)
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}
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continue
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}
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// NOTE: not using WriteRune here because it writes the UTF-8
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@@ -239,6 +239,186 @@ func TestLlama(t *testing.T) {
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})
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}
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// spmBPE builds a SentencePiece-style BPE tokenizer for testing.
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//
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// Models that use SentencePiece BPE differ from GPT-2 BPE in how they
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// handle spaces: the vocabulary stores ▁ (U+2581) instead of GPT-2's
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// shifted-byte encoding (0x0100–0x0143). Without WithSentencePieceNormalizer,
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// spaces are mapped through the GPT-2 byte table which produces wrong token
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// IDs for any vocabulary that uses ▁-prefixed tokens. The decode path has
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// the inverse problem: high codepoints like CJK characters and ▁ itself
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// would be mangled by the GPT-2 reverse mapping instead of being passed
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// through (or converted to spaces in the ▁ case).
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func spmBPE(t testing.TB) BytePairEncoding {
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t.Helper()
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tokens := []string{
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// Control tokens (low IDs, as in real SentencePiece vocabs)
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"<pad>", // 0
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"<eos>", // 1
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"<bos>", // 2
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"<|start>", // 3 - asymmetric open/close special tokens
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"<end|>", // 4
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"<|q>", // 5 - short special token (like <|"|>)
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// ▁-prefixed word tokens (the core of what SPM BPE changes)
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"▁hello", // 6
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"▁world", // 7
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"hello", // 8
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"▁Run", // 9
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"▁a", // 10
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// Punctuation and structure
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",", // 11
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"!", // 12
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":", // 13
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"{", // 14
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"}", // 15
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// Whitespace separator
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"▁", // 16
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// Subword tokens used in tool-declaration-like patterns
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"description", // 17
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"▁command", // 18
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"declaration", // 19
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// Unicode token for decode passthrough testing (must be > U+0143
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// to exercise the SPM decode path rather than GPT-2 byte reversal)
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"▁中文", // 20
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}
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types := make([]int32, len(tokens))
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for i := range types {
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types[i] = TOKEN_TYPE_NORMAL
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}
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types[0] = TOKEN_TYPE_CONTROL // <pad>
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types[1] = TOKEN_TYPE_CONTROL // <eos>
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types[2] = TOKEN_TYPE_CONTROL // <bos>
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types[3] = TOKEN_TYPE_USER_DEFINED // <|start>
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types[4] = TOKEN_TYPE_USER_DEFINED // <end|>
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types[5] = TOKEN_TYPE_USER_DEFINED // <|q>
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return NewBytePairEncodingWithOptions(
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&Vocabulary{
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Values: tokens,
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Types: types,
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BOS: []int32{2},
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EOS: []int32{1},
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AddBOS: false,
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},
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// Empty pretokenizer list: falls back to the default pattern.
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// Real SentencePiece BPE models are configured this way.
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[]string{},
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WithSentencePieceNormalizer(),
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)
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}
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func TestSentencePieceBPE(t *testing.T) {
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tok := spmBPE(t)
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// Test 1: Space-to-▁ normalization and roundtrip.
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//
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// This is the core behavior that WithSentencePieceNormalizer enables.
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// Without it, " hello" would be byte-mapped through the GPT-2 table
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// (producing Ġhello or similar shifted codepoints) which would never
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// match the ▁-prefixed vocab entry.
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t.Run("spm space normalization roundtrip", func(t *testing.T) {
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t.Parallel()
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cases := map[string][]int32{
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"hello": {8}, // no space → no ▁ prefix → "hello"(8)
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" hello": {6}, // leading space → "▁hello"(6)
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"hello, world!": {8, 11, 7, 12}, // pretokenizer splits punctuation;
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// " world" normalizes to "▁world"
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}
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for input, wantIDs := range cases {
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ids, err := tok.Encode(input, false)
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if err != nil {
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t.Fatalf("Encode(%q): %v", input, err)
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}
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if diff := cmp.Diff(wantIDs, ids); diff != "" {
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t.Errorf("Encode(%q) mismatch (-want +got):\n%s", input, diff)
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}
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got, err := tok.Decode(ids)
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if err != nil {
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t.Fatalf("Decode(%v): %v", ids, err)
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}
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if got != input {
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t.Errorf("roundtrip %q: Decode(Encode) = %q", input, got)
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}
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}
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})
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// Test 2: Special tokens interleaved with SPM-normalized text.
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//
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// This mimics tool declaration patterns like:
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// <|tool>declaration:bash{description:<|"|>Run a command<|"|>}<tool|>
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// where special tokens (<|tool>, <|"|>, <tool|>) must be extracted
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// first, then the remaining text fragments go through SPM normalization.
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// Without the SPM normalizer, the text between special tokens would be
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// encoded with GPT-2 byte mapping, producing entirely wrong IDs.
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t.Run("special tokens with spm text fragments", func(t *testing.T) {
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t.Parallel()
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// Pattern: <|start>declaration:description:<|q>Run a command<|q>}<end|>
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input := "<|start>declaration:description:<|q> Run a command<|q>}<end|>"
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ids, err := tok.Encode(input, false)
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if err != nil {
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t.Fatal(err)
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}
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// Special tokens should be extracted as single IDs, and the text
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// between them should be SPM-normalized (spaces → ▁).
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want := []int32{
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3, // <|start>
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19, // "declaration" (text fragment, no leading space)
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13, // ":"
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17, // "description"
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13, // ":"
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5, // <|q>
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9, // "▁Run" (space before "Run" becomes ▁)
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10, // "▁a"
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18, // "▁command"
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5, // <|q>
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15, // "}"
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4, // <end|>
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}
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if diff := cmp.Diff(want, ids); diff != "" {
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t.Errorf("mismatch (-want +got):\n%s", diff)
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}
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})
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// Test 3: Decode handles non-GPT2 Unicode correctly.
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//
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// GPT-2 BPE decode reverses the byte→codepoint shift for runes in
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// 0x0100–0x0143. But SentencePiece vocabs store real Unicode (CJK,
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// accented chars, etc.) which have codepoints well above 0x0143.
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// Without the > 0x0143 passthrough in Decode, these would be mangled
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// by the GPT-2 reverse mapping (e.g., written as raw bytes instead
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// of the original characters).
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t.Run("decode non-gpt2 unicode passthrough", func(t *testing.T) {
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t.Parallel()
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cases := map[string][]int32{
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" 中文": {20}, // ▁→space, then CJK passes through as-is
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}
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for want, ids := range cases {
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got, err := tok.Decode(ids)
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if err != nil {
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t.Fatalf("Decode(%v): %v", ids, err)
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}
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if got != want {
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t.Errorf("Decode(%v) = %q, want %q", ids, got, want)
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}
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}
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})
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}
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func BenchmarkBytePairEncoding(b *testing.B) {
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tokenizer := llama(b)
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bts, err := os.ReadFile(filepath.Join("testdata", "war-and-peace.txt"))
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