Upload BolmoForCausalLM
Browse files- configuration_bolmo.py +1 -1
- modeling_bolmo.py +3 -3
- tokenization_bolmo.py +301 -0
- utils_bolmo.py +127 -0
configuration_bolmo.py
CHANGED
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@@ -3,7 +3,7 @@ from typing import Any
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from transformers.configuration_utils import PretrainedConfig, layer_type_validation
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from transformers.modeling_rope_utils import rope_config_validation
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from
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class BolmoConfig(PretrainedConfig):
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r"""
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from transformers.configuration_utils import PretrainedConfig, layer_type_validation
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from transformers.modeling_rope_utils import rope_config_validation
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from .tokenization_bolmo import ByteTokenizerConfig
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class BolmoConfig(PretrainedConfig):
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r"""
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modeling_bolmo.py
CHANGED
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@@ -22,9 +22,9 @@ from transformers.utils import auto_docstring, can_return_tuple
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from transformers.utils.deprecation import deprecate_kwarg
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from transformers.utils.generic import check_model_inputs
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-
from
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from
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from
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from xlstm.xlstm_large.model import mLSTMLayer, mLSTMLayerConfig, mLSTMLayerStateType, soft_cap, mLSTMBackendConfig
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from transformers.utils.deprecation import deprecate_kwarg
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from transformers.utils.generic import check_model_inputs
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from .configuration_bolmo import BolmoConfig
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from .tokenization_bolmo import ByteTokenizerConfig
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from .utils_bolmo import compute_boundary_mask, pad_right, pad_left, MaskState
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from xlstm.xlstm_large.model import mLSTMLayer, mLSTMLayerConfig, mLSTMLayerStateType, soft_cap, mLSTMBackendConfig
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tokenization_bolmo.py
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@@ -0,0 +1,301 @@
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| 1 |
+
from dataclasses import dataclass, field
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from functools import lru_cache
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from typing import Optional
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from transformers import AutoTokenizer
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+
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+
# Source: https://github.com/openai/gpt-2/blob/master/src/encoder.py#L9
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# Also implemented in https://docs.rs/tokenizers/latest/src/tokenizers/pre_tokenizers/byte_level.rs.html#13-39
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_CHARS_TO_BYTES = {
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+
"Ā": 0, "ā": 1, "Ă": 2, "ă": 3, "Ą": 4, "ą": 5, "Ć": 6, "ć": 7, "Ĉ": 8,
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+
"ĉ": 9, "Ċ": 10, "ċ": 11, "Č": 12, "č": 13, "Ď": 14, "ď": 15, "Đ": 16,
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+
"đ": 17, "Ē": 18, "ē": 19, "Ĕ": 20, "ĕ": 21, "Ė": 22, "ė": 23, "Ę": 24,
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+
"ę": 25, "Ě": 26, "ě": 27, "Ĝ": 28, "ĝ": 29, "Ğ": 30, "ğ": 31, "Ġ": 32,
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+
"!": 33, '"': 34, "#": 35, "$": 36, "%": 37, "&": 38, "'": 39, "(": 40,
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| 14 |
+
")": 41, "*": 42, "+": 43, ",": 44, "-": 45, ".": 46, "/": 47, "0": 48,
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| 15 |
+
"1": 49, "2": 50, "3": 51, "4": 52, "5": 53, "6": 54, "7": 55, "8": 56,
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| 16 |
+
"9": 57, ":": 58, ";": 59, "<": 60, "=": 61, ">": 62, "?": 63, "@": 64,
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| 17 |
+
"A": 65, "B": 66, "C": 67, "D": 68, "E": 69, "F": 70, "G": 71, "H": 72,
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| 18 |
+
"I": 73, "J": 74, "K": 75, "L": 76, "M": 77, "N": 78, "O": 79, "P": 80,
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| 19 |
+
"Q": 81, "R": 82, "S": 83, "T": 84, "U": 85, "V": 86, "W": 87, "X": 88,
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| 20 |
+
"Y": 89, "Z": 90, "[": 91, "\\": 92, "]": 93, "^": 94, "_": 95, "`": 96,
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| 21 |
+
"a": 97, "b": 98, "c": 99, "d": 100, "e": 101, "f": 102, "g": 103,
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| 22 |
+
"h": 104, "i": 105, "j": 106, "k": 107, "l": 108, "m": 109, "n": 110,
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| 23 |
+
"o": 111, "p": 112, "q": 113, "r": 114, "s": 115, "t": 116, "u": 117,
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+
"v": 118, "w": 119, "x": 120, "y": 121, "z": 122, "{": 123, "|": 124,
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+
"}": 125, "~": 126, "ġ": 127, "Ģ": 128, "ģ": 129, "Ĥ": 130, "ĥ": 131,
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| 26 |
+
"Ħ": 132, "ħ": 133, "Ĩ": 134, "ĩ": 135, "Ī": 136, "ī": 137, "Ĭ": 138,
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+
"ĭ": 139, "Į": 140, "į": 141, "İ": 142, "ı": 143, "IJ": 144, "ij": 145,
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| 28 |
+
"Ĵ": 146, "ĵ": 147, "Ķ": 148, "ķ": 149, "ĸ": 150, "Ĺ": 151, "ĺ": 152,
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| 29 |
+
"Ļ": 153, "ļ": 154, "Ľ": 155, "ľ": 156, "Ŀ": 157, "ŀ": 158, "Ł": 159,
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| 30 |
+
"ł": 160, "¡": 161, "¢": 162, "£": 163, "¤": 164, "¥": 165, "¦": 166,
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| 31 |
+
"§": 167, "¨": 168, "©": 169, "ª": 170, "«": 171, "¬": 172, "Ń": 173,
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| 32 |
+
"®": 174, "¯": 175, "°": 176, "±": 177, "²": 178, "³": 179, "´": 180,
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| 33 |
+
"µ": 181, "¶": 182, "·": 183, "¸": 184, "¹": 185, "º": 186, "»": 187,
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| 34 |
+
"¼": 188, "½": 189, "¾": 190, "¿": 191, "À": 192, "Á": 193, "Â": 194,
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| 35 |
+
"Ã": 195, "Ä": 196, "Å": 197, "Æ": 198, "Ç": 199, "È": 200, "É": 201,
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| 36 |
+
"Ê": 202, "Ë": 203, "Ì": 204, "Í": 205, "Î": 206, "Ï": 207, "Ð": 208,
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| 37 |
+
"Ñ": 209, "Ò": 210, "Ó": 211, "Ô": 212, "Õ": 213, "Ö": 214, "×": 215,
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| 38 |
+
"Ø": 216, "Ù": 217, "Ú": 218, "Û": 219, "Ü": 220, "Ý": 221, "Þ": 222,
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| 39 |
+
"ß": 223, "à": 224, "á": 225, "â": 226, "ã": 227, "ä": 228, "å": 229,
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| 40 |
+
"æ": 230, "ç": 231, "è": 232, "é": 233, "ê": 234, "ë": 235, "ì": 236,
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| 41 |
+
"í": 237, "î": 238, "ï": 239, "ð": 240, "ñ": 241, "ò": 242, "ó": 243,
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| 42 |
+
"ô": 244, "õ": 245, "ö": 246, "÷": 247, "ø": 248, "ù": 249, "ú": 250,
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| 43 |
+
"û": 251, "ü": 252, "ý": 253, "þ": 254, "ÿ": 255,
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| 44 |
+
}
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_BYTES_TO_CHARS = {v: k for k, v in _CHARS_TO_BYTES.items()}
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+
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| 47 |
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def _bytes_to_chars(byte_sequence: bytes) -> str:
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return "".join(_BYTES_TO_CHARS[byte] for byte in byte_sequence)
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+
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| 50 |
+
def _chars_to_bytes(char_sequence: str) -> list:
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return list(bytes(_CHARS_TO_BYTES[char] for char in char_sequence))
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+
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| 53 |
+
@dataclass
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+
class ByteTokenizerConfig:
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+
vocab_size: int
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+
bos_token_id: int
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| 57 |
+
pad_token_id: int
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+
eos_token_id: int
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| 59 |
+
bpe_token_end_id: int
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+
special_tokens: list[str] = field(default_factory=lambda: [])
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+
special_tokens_first: bool = True
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+
original_identifier: Optional[str] = None
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+
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| 64 |
+
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| 65 |
+
@classmethod
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| 66 |
+
def bolmo(cls) -> "ByteTokenizerConfig":
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+
special_tokens = [
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| 68 |
+
"<pad>",
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| 69 |
+
"<bos>",
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| 70 |
+
"<eos>",
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| 71 |
+
"<bpe_token_end>",
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| 72 |
+
]
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| 73 |
+
|
| 74 |
+
return cls(
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| 75 |
+
# *2 to accomodate fused boundary tokens
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| 76 |
+
vocab_size=(len(special_tokens) + 256) * 2,
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| 77 |
+
special_tokens=special_tokens,
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| 78 |
+
bos_token_id=special_tokens.index("<bos>"),
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| 79 |
+
pad_token_id=special_tokens.index("<pad>"),
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| 80 |
+
eos_token_id=special_tokens.index("<bos>"),
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| 81 |
+
bpe_token_end_id=special_tokens.index("<bpe_token_end>"),
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| 82 |
+
original_identifier="allenai/dolma2-tokenizer",
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| 83 |
+
)
|
| 84 |
+
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| 85 |
+
def build(self):
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| 86 |
+
return ByteTokenizer(self)
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| 87 |
+
|
| 88 |
+
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| 89 |
+
class ByteTokenizer:
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| 90 |
+
TOKEN_ID_KEY = -1
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| 91 |
+
|
| 92 |
+
def __init__(self, tokenizer_config: ByteTokenizerConfig):
|
| 93 |
+
self.config = tokenizer_config
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| 94 |
+
self.hf_tokenizer = AutoTokenizer.from_pretrained(tokenizer_config.original_identifier)
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| 95 |
+
if self.config.special_tokens_first:
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| 96 |
+
self.offset = len(tokenizer_config.special_tokens)
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| 97 |
+
self.special_tokens_offset = 0
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| 98 |
+
else:
|
| 99 |
+
self.offset = 0
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| 100 |
+
self.special_tokens_offset = self.config.vocab_size - len(tokenizer_config.special_tokens)
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| 101 |
+
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| 102 |
+
self.byte_sequences = {}
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| 103 |
+
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| 104 |
+
for key, value in self.hf_tokenizer.get_vocab().items():
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| 105 |
+
if key in self.config.special_tokens:
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| 106 |
+
byte_sequence = [self.special_tokens_offset + self.config.special_tokens.index(key)]
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| 107 |
+
elif value == self.hf_tokenizer.eos_token_id and self.eos_token_id is not None:
|
| 108 |
+
byte_sequence = [self.eos_token_id]
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| 109 |
+
elif value == self.hf_tokenizer.bos_token_id and self.bos_token_id is not None:
|
| 110 |
+
byte_sequence = [self.bos_token_id]
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| 111 |
+
elif value == self.hf_tokenizer.pad_token_id and self.pad_token_id is not None:
|
| 112 |
+
byte_sequence = [self.pad_token_id]
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| 113 |
+
else:
|
| 114 |
+
byte_sequence = [self.offset + i for i in _chars_to_bytes(key)]
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| 115 |
+
|
| 116 |
+
assert self.byte_sequences.get(value) is None
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| 117 |
+
self.byte_sequences[value] = byte_sequence
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| 118 |
+
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| 119 |
+
self.byte_trie = {}
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| 120 |
+
|
| 121 |
+
for token_id, byte_sequence in self.byte_sequences.items():
|
| 122 |
+
current_dict = self.byte_trie
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| 123 |
+
for byte in byte_sequence[::-1]: # retrieved from the back so store in reverse order
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| 124 |
+
if byte not in current_dict:
|
| 125 |
+
current_dict[byte] = {}
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| 126 |
+
current_dict = current_dict[byte]
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| 127 |
+
current_dict[ByteTokenizer.TOKEN_ID_KEY] = token_id
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| 128 |
+
|
| 129 |
+
@property
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| 130 |
+
def bos_token_id(self):
|
| 131 |
+
return self.config.bos_token_id
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| 132 |
+
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| 133 |
+
@property
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| 134 |
+
def eos_token_id(self):
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| 135 |
+
return self.config.eos_token_id
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| 136 |
+
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| 137 |
+
@property
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| 138 |
+
def pad_token_id(self):
|
| 139 |
+
return self.config.pad_token_id
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| 140 |
+
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| 141 |
+
@property
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| 142 |
+
def bpe_token_end_id(self):
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| 143 |
+
return self.config.bpe_token_end_id
|
| 144 |
+
|
| 145 |
+
def expand_byte_ids(self, byte_ids: list[int], n_last: Optional[int] = None) -> list[int]:
|
| 146 |
+
# search in the byte tree for the longest matching token at every byte position
|
| 147 |
+
expanded_ids = []
|
| 148 |
+
for i in range(len(byte_ids)):
|
| 149 |
+
if n_last is not None and i < len(byte_ids) - n_last:
|
| 150 |
+
continue
|
| 151 |
+
|
| 152 |
+
current_dict = self.byte_trie
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| 153 |
+
current_expansion = None
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| 154 |
+
|
| 155 |
+
for i in range(i, -1, -1):
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| 156 |
+
byte = byte_ids[i]
|
| 157 |
+
|
| 158 |
+
if byte == self.bpe_token_end_id:
|
| 159 |
+
# skip bpe token end markers, needed for generation
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| 160 |
+
continue
|
| 161 |
+
|
| 162 |
+
if byte >= self.offset + 256:
|
| 163 |
+
# ignore fused boundary
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| 164 |
+
byte -= self.offset + 256
|
| 165 |
+
|
| 166 |
+
try:
|
| 167 |
+
current_dict = current_dict[byte]
|
| 168 |
+
if ByteTokenizer.TOKEN_ID_KEY in current_dict:
|
| 169 |
+
current_expansion = current_dict[ByteTokenizer.TOKEN_ID_KEY]
|
| 170 |
+
except KeyError:
|
| 171 |
+
assert current_expansion is not None
|
| 172 |
+
break
|
| 173 |
+
|
| 174 |
+
expanded_ids.append(current_expansion)
|
| 175 |
+
|
| 176 |
+
return expanded_ids
|
| 177 |
+
|
| 178 |
+
def patch_ids_to_byte_ids(self, input_ids: list[int]):
|
| 179 |
+
return [byte_token_id for token_id in input_ids for byte_token_id in self.byte_sequences[token_id]]
|
| 180 |
+
|
| 181 |
+
def encode(self, string: str, add_special_tokens=False):
|
| 182 |
+
input_ids = self.hf_tokenizer.encode(string, add_special_tokens=add_special_tokens)
|
| 183 |
+
return self.patch_ids_to_byte_ids(input_ids)
|
| 184 |
+
|
| 185 |
+
def decode(self, tokens: list[int]) -> str:
|
| 186 |
+
return self.decode_to_bytes(tokens).decode("utf-8", errors="replace")
|
| 187 |
+
|
| 188 |
+
def decode_to_bytes(self, tokens: list[int]) -> bytes:
|
| 189 |
+
tokens_without_boundary = []
|
| 190 |
+
for token in tokens:
|
| 191 |
+
if token >= (self.offset + 256):
|
| 192 |
+
token -= self.offset + 256
|
| 193 |
+
|
| 194 |
+
tokens_without_boundary.append(token)
|
| 195 |
+
|
| 196 |
+
utf8_bytes = [min(token - self.offset, 255) for token in tokens_without_boundary if token >= self.offset]
|
| 197 |
+
return bytes(utf8_bytes)
|
| 198 |
+
|
| 199 |
+
def get_tokens_and_patch_lengths(self, original_input_ids: list[int], add_bos=False, strip_pad=False, skip_last=False):
|
| 200 |
+
if add_bos and self.bos_token_id is not None:
|
| 201 |
+
byte_tokens = [self.bos_token_id]
|
| 202 |
+
patch_lengths = [1]
|
| 203 |
+
else:
|
| 204 |
+
byte_tokens = []
|
| 205 |
+
patch_lengths = []
|
| 206 |
+
|
| 207 |
+
for idx, token in enumerate(original_input_ids):
|
| 208 |
+
# optionally skip last token to keep the length the same if add_bos=True
|
| 209 |
+
if skip_last and idx == len(original_input_ids) - 1:
|
| 210 |
+
break
|
| 211 |
+
|
| 212 |
+
token_byte_tokens = self.patch_ids_to_byte_ids([int(token)])
|
| 213 |
+
|
| 214 |
+
if strip_pad and all(t == self.pad_token_id for t in token_byte_tokens):
|
| 215 |
+
# skip padding tokens
|
| 216 |
+
continue
|
| 217 |
+
|
| 218 |
+
patch_lengths.append(len(token_byte_tokens))
|
| 219 |
+
byte_tokens.extend(token_byte_tokens)
|
| 220 |
+
|
| 221 |
+
return byte_tokens, patch_lengths
|
| 222 |
+
|
| 223 |
+
@lru_cache(maxsize=1024)
|
| 224 |
+
def _is_spacelike(self, token_id: int) -> bool:
|
| 225 |
+
"""
|
| 226 |
+
Check if a token ID is spacelike.
|
| 227 |
+
"""
|
| 228 |
+
byte = token_id - self.offset
|
| 229 |
+
# see https://github.com/kjslag/spacebyte/blob/321111315c92bce0bc2f9f1630cb0bc82b897c57/spacebyte.py#L137-L145.
|
| 230 |
+
is_spacelike = (
|
| 231 |
+
(byte < ord('0')) |
|
| 232 |
+
((ord('9') < byte) & (byte < ord('A'))) |
|
| 233 |
+
((ord('Z') < byte) & (byte < ord('a'))) |
|
| 234 |
+
((ord('z') < byte) & (byte < 0b1000_0000)) |
|
| 235 |
+
(0b1100_0000 <= byte)
|
| 236 |
+
)
|
| 237 |
+
return is_spacelike
|
| 238 |
+
|
| 239 |
+
@lru_cache(maxsize=1024)
|
| 240 |
+
def _is_strict_spacelike(self, token_id: int) -> bool:
|
| 241 |
+
"""
|
| 242 |
+
Check if a token ID is strictly spacelike (only space, tab, newline, carriage return).
|
| 243 |
+
"""
|
| 244 |
+
byte = token_id - self.offset
|
| 245 |
+
return byte in {ord(' '), ord('\t'), ord('\n'), ord('\r')}
|
| 246 |
+
|
| 247 |
+
def get_space_patch_lengths(self, input_ids: list[int], max_patch_length: int = 16, kind: str = "strict_end_before_space") -> list[int]:
|
| 248 |
+
patch_lengths = []
|
| 249 |
+
current_length = 0
|
| 250 |
+
|
| 251 |
+
special_tokens = {self.bos_token_id, self.eos_token_id, self.pad_token_id}
|
| 252 |
+
|
| 253 |
+
all_spacelike = [self._is_spacelike(token) for token in input_ids]
|
| 254 |
+
|
| 255 |
+
if kind == "spacebyte":
|
| 256 |
+
for token_idx, token in enumerate(input_ids):
|
| 257 |
+
current_length += 1
|
| 258 |
+
|
| 259 |
+
spacelike = all_spacelike[token_idx]
|
| 260 |
+
previous_spacelike = all_spacelike[token_idx - 1] if token_idx > 0 else False
|
| 261 |
+
|
| 262 |
+
if (not previous_spacelike and spacelike) or current_length >= max_patch_length or token in special_tokens:
|
| 263 |
+
patch_lengths.append(current_length)
|
| 264 |
+
current_length = 0
|
| 265 |
+
elif kind == "spacebyte_end_before_space":
|
| 266 |
+
for token_idx, token in enumerate(input_ids):
|
| 267 |
+
current_length += 1
|
| 268 |
+
|
| 269 |
+
spacelike = all_spacelike[token_idx]
|
| 270 |
+
next_spacelike = all_spacelike[token_idx + 1] if token_idx < len(input_ids) - 1 else True
|
| 271 |
+
|
| 272 |
+
if (not spacelike and next_spacelike) or current_length >= max_patch_length or token in special_tokens:
|
| 273 |
+
patch_lengths.append(current_length)
|
| 274 |
+
current_length = 0
|
| 275 |
+
elif kind == "strict_end_before_space":
|
| 276 |
+
all_strict_spacelike = [self._is_strict_spacelike(token) for token in input_ids]
|
| 277 |
+
in_strict_prefix = True
|
| 278 |
+
|
| 279 |
+
for token_idx, token in enumerate(input_ids):
|
| 280 |
+
current_length += 1
|
| 281 |
+
|
| 282 |
+
spacelike = all_spacelike[token_idx]
|
| 283 |
+
strict_spacelike = all_strict_spacelike[token_idx]
|
| 284 |
+
next_spacelike = all_spacelike[token_idx + 1] if token_idx < len(input_ids) - 1 else True
|
| 285 |
+
next_strict_spacelike = all_strict_spacelike[token_idx + 1] if token_idx < len(input_ids) - 1 else True
|
| 286 |
+
|
| 287 |
+
if not strict_spacelike:
|
| 288 |
+
in_strict_prefix = False
|
| 289 |
+
|
| 290 |
+
if in_strict_prefix:
|
| 291 |
+
continue
|
| 292 |
+
|
| 293 |
+
if (spacelike != next_spacelike) or (strict_spacelike != next_strict_spacelike) or current_length >= max_patch_length or token in special_tokens:
|
| 294 |
+
patch_lengths.append(current_length)
|
| 295 |
+
in_strict_prefix = True
|
| 296 |
+
current_length = 0
|
| 297 |
+
|
| 298 |
+
if current_length > 0:
|
| 299 |
+
patch_lengths.append(current_length)
|
| 300 |
+
|
| 301 |
+
return patch_lengths
|
utils_bolmo.py
ADDED
|
@@ -0,0 +1,127 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import math
|
| 2 |
+
|
| 3 |
+
import torch
|
| 4 |
+
import torch.nn.functional as F
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
def compute_boundary_mask(boundary_logprobs: torch.Tensor, boundary_threshold: str) -> torch.Tensor:
|
| 8 |
+
if boundary_threshold.startswith("sample:"):
|
| 9 |
+
_, temperature = boundary_threshold.split(":")
|
| 10 |
+
temperature = float(temperature)
|
| 11 |
+
|
| 12 |
+
if temperature == 0:
|
| 13 |
+
return (boundary_logprobs > math.log(0.5))
|
| 14 |
+
elif temperature == 1:
|
| 15 |
+
return torch.bernoulli(torch.exp(boundary_logprobs)).to(torch.bool)
|
| 16 |
+
else:
|
| 17 |
+
raise NotImplementedError("Temperatures outside {0,1} are not implemented yet.")
|
| 18 |
+
elif boundary_threshold.startswith("topk:"):
|
| 19 |
+
_, topk = boundary_threshold.split(":")
|
| 20 |
+
topk = int(topk)
|
| 21 |
+
thresholds = torch.quantile(boundary_logprobs, dim=1, q=1 - (topk / boundary_logprobs.shape[1]))
|
| 22 |
+
return (boundary_logprobs >= thresholds.unsqueeze(-1))
|
| 23 |
+
elif boundary_threshold.startswith("topk_percent:"):
|
| 24 |
+
_, topk_percent = boundary_threshold.split(":")
|
| 25 |
+
topk_percent = float(topk_percent)
|
| 26 |
+
assert 0 <= topk_percent <= 1
|
| 27 |
+
thresholds = torch.quantile(boundary_logprobs, dim=1, q=1 - topk_percent)
|
| 28 |
+
return (boundary_logprobs >= thresholds.unsqueeze(-1))
|
| 29 |
+
else:
|
| 30 |
+
raise ValueError(f"Unknown boundary threshold: {boundary_threshold}")
|
| 31 |
+
|
| 32 |
+
|
| 33 |
+
def _pad(tensors: list[torch.Tensor], multiple_of: int, direction: str, value):
|
| 34 |
+
max_len = max(t.size(0) for t in tensors)
|
| 35 |
+
if multiple_of > 1:
|
| 36 |
+
# Round up max_len to the nearest multiple_of
|
| 37 |
+
max_len = ((max_len + multiple_of - 1) // multiple_of) * multiple_of
|
| 38 |
+
padded = []
|
| 39 |
+
for t in tensors:
|
| 40 |
+
if direction == "left":
|
| 41 |
+
pad_shape = (max_len - t.size(0), 0)
|
| 42 |
+
elif direction == "right":
|
| 43 |
+
pad_shape = (0, max_len - t.size(0))
|
| 44 |
+
else:
|
| 45 |
+
raise ValueError(f"Unknown direction: {direction}. Must be 'left' or 'right'.")
|
| 46 |
+
padded.append(F.pad(t, pad_shape, value=value))
|
| 47 |
+
return torch.stack(padded, dim=0)
|
| 48 |
+
|
| 49 |
+
def pad_right(
|
| 50 |
+
tensors: list[torch.Tensor],
|
| 51 |
+
multiple_of: int = 128,
|
| 52 |
+
value=0,
|
| 53 |
+
):
|
| 54 |
+
return _pad(tensors, multiple_of, direction="right", value=value)
|
| 55 |
+
|
| 56 |
+
def pad_left(
|
| 57 |
+
tensors: list[torch.Tensor],
|
| 58 |
+
multiple_of: int = 128,
|
| 59 |
+
value=0,
|
| 60 |
+
):
|
| 61 |
+
return _pad(tensors, multiple_of, direction="left", value=value)
|
| 62 |
+
|
| 63 |
+
class MaskState:
|
| 64 |
+
def __init__(self, mask):
|
| 65 |
+
self.cpu_mask = mask.cpu()
|
| 66 |
+
|
| 67 |
+
self.mask = mask
|
| 68 |
+
self.inv_mask = ~mask
|
| 69 |
+
self._all = self.cpu_mask.all().item()
|
| 70 |
+
self._any = self.cpu_mask.any().item()
|
| 71 |
+
|
| 72 |
+
def any(self):
|
| 73 |
+
return self._any
|
| 74 |
+
|
| 75 |
+
def all(self):
|
| 76 |
+
return self._all
|
| 77 |
+
|
| 78 |
+
def selective_get(self, x, inv=False):
|
| 79 |
+
# try to avoid sync through nonzero on index
|
| 80 |
+
if inv:
|
| 81 |
+
if self.all():
|
| 82 |
+
return x[[]]
|
| 83 |
+
elif not self.any():
|
| 84 |
+
return x
|
| 85 |
+
else:
|
| 86 |
+
return x[self.inv_mask]
|
| 87 |
+
else:
|
| 88 |
+
if self.all():
|
| 89 |
+
return x
|
| 90 |
+
elif not self.any():
|
| 91 |
+
return x[[]]
|
| 92 |
+
else:
|
| 93 |
+
return x[self.mask]
|
| 94 |
+
|
| 95 |
+
def selective_put(self, x, out, inv=False):
|
| 96 |
+
# try to avoid sync through nonzero on index
|
| 97 |
+
if inv:
|
| 98 |
+
if self.all():
|
| 99 |
+
return
|
| 100 |
+
elif not self.any():
|
| 101 |
+
out.copy_(x)
|
| 102 |
+
else:
|
| 103 |
+
out[self.inv_mask] = x
|
| 104 |
+
else:
|
| 105 |
+
if self.all():
|
| 106 |
+
out.copy_(x)
|
| 107 |
+
elif not self.any():
|
| 108 |
+
return
|
| 109 |
+
else:
|
| 110 |
+
out[self.mask] = x
|
| 111 |
+
|
| 112 |
+
def selective_add(self, x, out, inv=False):
|
| 113 |
+
# try to avoid sync through nonzero on index
|
| 114 |
+
if inv:
|
| 115 |
+
if self.all():
|
| 116 |
+
return
|
| 117 |
+
elif not self.any():
|
| 118 |
+
out.add_(x)
|
| 119 |
+
else:
|
| 120 |
+
out[self.inv_mask] += x
|
| 121 |
+
else:
|
| 122 |
+
if self.all():
|
| 123 |
+
out.add_(x)
|
| 124 |
+
elif not self.any():
|
| 125 |
+
return
|
| 126 |
+
else:
|
| 127 |
+
out[self.mask] += x
|