Ported Starcoder and added some assertions

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goerch 2023-10-02 11:14:08 +02:00 committed by GitHub
parent 02b9ccfd60
commit 3d162cc8ad
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2 changed files with 14 additions and 41 deletions

View file

@ -20,28 +20,6 @@ if 'NO_LOCAL_GGUF' not in os.environ:
import gguf
def bytes_to_unicode():
# ref: https://github.com/openai/gpt-2/blob/master/src/encoder.py
"""
Returns list of utf-8 byte and a corresponding list of unicode strings.
The reversible bpe codes work on unicode strings.
This means you need a large # of unicode characters in your vocab if you want to avoid UNKs.
When you're at something like a 10B token dataset you end up needing around 5K for decent coverage.
This is a significant percentage of your normal, say, 32K bpe vocab.
To avoid that, we want lookup tables between utf-8 bytes and unicode strings.
And avoids mapping to whitespace/control characters the bpe code barfs on.
"""
bs = list(range(ord("!"), ord("~")+1))+list(range(ord("¡"), ord("¬")+1))+list(range(ord("®"), ord("ÿ")+1))
cs = bs[:]
n = 0
for b in range(2**8):
if b not in bs:
bs.append(b)
cs.append(2**8+n)
n += 1
return dict(zip(bs, (chr(n) for n in cs)))
def count_model_parts(dir_model: Path) -> int:
num_parts = 0
for filename in os.listdir(dir_model):
@ -117,6 +95,8 @@ gguf_writer.add_file_type(ftype)
print("gguf: get tokenizer metadata")
tokens: list[bytearray] = []
scores: list[float] = []
toktypes: list[int] = []
tokenizer_json_file = dir_model / 'tokenizer.json'
if not tokenizer_json_file.is_file():
@ -139,28 +119,15 @@ vocab_size = hparams["vocab_size"] if "vocab_size" in hparams else len(tokenizer
tokenizer = AutoTokenizer.from_pretrained(dir_model)
reverse_vocab = {id: encoded_tok for encoded_tok, id in tokenizer.vocab.items()}
byte_encoder = bytes_to_unicode()
byte_decoder = {v: k for k, v in byte_encoder.items()}
for i in range(vocab_size):
if i in reverse_vocab:
try:
text = bytearray([byte_decoder[c] for c in reverse_vocab[i]])
except KeyError:
text = bytearray()
for c in reverse_vocab[i]:
if ord(c) < 256: # single byte character
text.append(byte_decoder[ord(c)])
else: # multibyte special token character
text.extend(c.encode('utf-8'))
else:
print(f"Key {i} not in tokenizer vocabulary. Padding with an arbitrary token.")
pad_token = f"[PAD{i}]".encode("utf8")
text = bytearray(pad_token)
tokens.append(text)
tokens.append(reverse_vocab[i])
scores.append(0.0) # dummy
toktypes.append(gguf.TokenType.NORMAL)
gguf_writer.add_token_list(tokens)
gguf_writer.add_token_scores(scores)
gguf_writer.add_token_types(toktypes)
special_vocab = gguf.SpecialVocab(dir_model, load_merges = True)
special_vocab.add_to_gguf(gguf_writer)

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@ -405,12 +405,15 @@ static int codepoint_type(std::string utf8) {
static std::unordered_map<uint8_t, std::string> bytes_to_unicode_map_bpe() {
std::unordered_map<uint8_t, std::string> map;
for (int ch = u'!'; ch <= u'~'; ++ch) {
assert(0 <= ch && ch < 256);
map[ch] = codepoint_to_utf8(ch);
}
for (int ch = u'¡'; ch <= u'¬'; ++ch) {
assert(0 <= ch && ch < 256);
map[ch] = codepoint_to_utf8(ch);
}
for (int ch = u'®'; ch <= u'ÿ'; ++ch) {
assert(0 <= ch && ch < 256);
map[ch] = codepoint_to_utf8(ch);
}
auto n = 0;
@ -431,12 +434,15 @@ static std::string bytes_to_unicode_bpe(uint8_t byte) {
static std::unordered_map<std::string, uint8_t> unicode_to_bytes_map_bpe() {
std::unordered_map<std::string, uint8_t> map;
for (int ch = u'!'; ch <= u'~'; ++ch) {
assert(0 <= ch && ch < 256);
map[codepoint_to_utf8(ch)] = ch;
}
for (int ch = u'¡'; ch <= u'¬'; ++ch) {
assert(0 <= ch && ch < 256);
map[codepoint_to_utf8(ch)] = ch;
}
for (int ch = u'®'; ch <= u'ÿ'; ++ch) {
assert(0 <= ch && ch < 256);
map[codepoint_to_utf8(ch)] = ch;
}
auto n = 0;
@ -449,7 +455,7 @@ static std::unordered_map<std::string, uint8_t> unicode_to_bytes_map_bpe() {
return map;
}
static uint8_t unicode_to_bytes_bpe(const std::string& utf8) {
static uint8_t unicode_to_bytes_bpe(const std::string & utf8) {
static std::unordered_map<std::string, uint8_t> map = unicode_to_bytes_map_bpe();
return map.at(utf8);
}