mirror of
https://github.com/facebookresearch/blt.git
synced 2025-02-22 13:02:14 +00:00
Remove byte tokenizer and add config args to switch between byte/patch packing
Summary: Test Plan: ``` python -m bytelatent.train config=../internal-blt/configs/entropy_model.yaml logging.wandb=null checkpoint.dump.every=1000 checkpoint.eval.every=100000 eval=null pytest bytelatent/ ```
This commit is contained in:
parent
fc3399ef40
commit
2655e4cf82
|
@ -14,7 +14,11 @@ from bytelatent.data.iterators.abstract_iterator import StatefulIterator
|
|||
from bytelatent.data.iterators.arrow_iterator import ArrowFileIterator
|
||||
from bytelatent.data.iterators.looping_iterator import LoopingIterator
|
||||
from bytelatent.data.iterators.multiprocess_iterator import MultiprocessIterator
|
||||
from bytelatent.data.iterators.packing_iterator import PackingArgs, PackingIterator
|
||||
from bytelatent.data.iterators.packing_iterator import (
|
||||
PackingArgs,
|
||||
PackingIterator,
|
||||
PackingMode,
|
||||
)
|
||||
from bytelatent.data.iterators.preprocess_iterator import PreprocessIterator
|
||||
from bytelatent.data.iterators.sampling_iterator import SamplingIterator
|
||||
from bytelatent.data.iterators.sequence_iterator import (
|
||||
|
@ -134,6 +138,7 @@ class DataloaderArgs(BaseModel):
|
|||
buffer_size: int = 64
|
||||
file_format: str = "arrow"
|
||||
|
||||
packing_mode: PackingMode = PackingMode.PATCHING
|
||||
pad_to_max_length: bool = True
|
||||
max_encoder_seq_length: int = 12288
|
||||
enable_byte_ngrams: bool = False
|
||||
|
@ -202,7 +207,7 @@ class DataloaderArgs(BaseModel):
|
|||
max_length=self.max_encoder_seq_length,
|
||||
pad_to_max_length=self.pad_to_max_length,
|
||||
enable_byte_ngrams=self.enable_byte_ngrams,
|
||||
tokenizer_name=self.tokenizer_args.name,
|
||||
packing_mode=self.packing_mode,
|
||||
)
|
||||
packing_iterator = PackingIterator(sampling_iterator, packing_args=packing_args)
|
||||
if self.load_async:
|
||||
|
|
|
@ -71,6 +71,7 @@ data:
|
|||
root_dir: ???
|
||||
sources:
|
||||
dclm_baseline_1.0: 1.0
|
||||
packing_mode: patching
|
||||
batch_size: 2
|
||||
prefetch_size: 64
|
||||
seq_len: 4096
|
||||
|
|
|
@ -39,6 +39,7 @@ data:
|
|||
root_dir: ???
|
||||
sources:
|
||||
dclm_baseline_1.0: 1.0
|
||||
packing_mode: bytes
|
||||
batch_size: 2
|
||||
prefetch_size: 64
|
||||
# seqlen is in terms of patches and
|
||||
|
@ -55,7 +56,7 @@ data:
|
|||
# so pick the most efficient, so static
|
||||
patching_mode: byte
|
||||
tokenizer_args:
|
||||
name: bytes
|
||||
name: blt
|
||||
|
||||
profiling:
|
||||
run: false
|
||||
|
|
|
@ -1,4 +1,5 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
from enum import Enum
|
||||
from typing import Any
|
||||
|
||||
import numpy as np
|
||||
|
@ -12,6 +13,11 @@ from bytelatent.data.iterators.abstract_iterator import (
|
|||
from bytelatent.data.iterators.sampling_iterator import SamplingIteratorState
|
||||
|
||||
|
||||
class PackingMode(str, Enum):
|
||||
BYTES = "bytes"
|
||||
PATCHING = "patching"
|
||||
|
||||
|
||||
class PackingArgs(BaseModel):
|
||||
model_config = ConfigDict(extra="forbid")
|
||||
batch_size: int
|
||||
|
@ -20,7 +26,7 @@ class PackingArgs(BaseModel):
|
|||
max_length: int | None
|
||||
pad_to_max_length: bool
|
||||
enable_byte_ngrams: bool
|
||||
tokenizer_name: str
|
||||
packing_mode: PackingMode
|
||||
|
||||
|
||||
class PackingIteratorState(PydanticIteratorState):
|
||||
|
@ -155,10 +161,12 @@ class PackingIterator(StatefulIterator[Batch, PackingIteratorState]):
|
|||
)
|
||||
|
||||
def create_iter(self):
|
||||
if self.packing_args.tokenizer_name == "bytes":
|
||||
if self.packing_args.packing_mode == PackingMode.BYTES:
|
||||
return self._create_iter_from_bytes()
|
||||
else:
|
||||
elif self.packing_args.packing_mode == PackingMode.PATCHING:
|
||||
return self._create_iter_from_patch_lengths()
|
||||
else:
|
||||
raise ValueError(f"Invalid patching mode: {self.packing_args.packing_mode}")
|
||||
|
||||
def _create_iter_from_bytes(self):
|
||||
sequence_iter = self.sequence_iterator.create_iter()
|
||||
|
|
|
@ -5,7 +5,6 @@ from typing import Any
|
|||
from pydantic import BaseModel
|
||||
|
||||
from bytelatent.tokenizers.blt_tokenizer import BltTokenizer
|
||||
from bytelatent.tokenizers.byte_tokenizer import ByteTokenizer
|
||||
from bytelatent.tokenizers.tiktoken_tokenizer import TikTokenTokenizer
|
||||
|
||||
try:
|
||||
|
@ -55,8 +54,6 @@ class TokenizerArgs(BaseModel):
|
|||
init_kwargs = self.init_kwargs
|
||||
if self.name == "blt":
|
||||
return BltTokenizer(**init_kwargs)
|
||||
elif self.name == "bytes":
|
||||
return ByteTokenizer(**init_kwargs)
|
||||
elif self.name == "mock":
|
||||
return MockTokenizer(**init_kwargs)
|
||||
elif self.name == "sp":
|
||||
|
|
|
@ -1,35 +0,0 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
from bytelatent.tokenizers.abstract_tokenizer import Tokenizer
|
||||
|
||||
|
||||
class ByteTokenizer(Tokenizer):
|
||||
def __init__(self):
|
||||
self.bos_id = 256
|
||||
self.eos_id = 257
|
||||
self.n_words = 258
|
||||
|
||||
def encode(self, s: str, add_bos: bool = False, add_eos: bool = False):
|
||||
tokens = [self.bos_id] * add_bos + list(s.encode()) + [self.eos_id] * add_eos
|
||||
return tokens
|
||||
|
||||
def decode(self, tokens: list[int]):
|
||||
byte_tokens = bytes([t for t in tokens if t < 256])
|
||||
return byte_tokens.decode("utf-8", errors="backslashreplace")
|
||||
|
||||
def get_token_offsets(
|
||||
self, text: str, tokens: list[int] | None = None
|
||||
) -> tuple[list[str], list[int]]:
|
||||
if tokens is None:
|
||||
tokens = self.encode(text)
|
||||
|
||||
decoded_chars, offsets = [], []
|
||||
byte_pos = 0
|
||||
for token in tokens:
|
||||
if token < 256:
|
||||
char = bytes([token]).decode("utf-8", errors="ignore")
|
||||
if char:
|
||||
decoded_chars.append(char)
|
||||
offsets.append(byte_pos)
|
||||
byte_pos += len(char.encode("utf-8"))
|
||||
|
||||
return decoded_chars, offsets
|
Loading…
Reference in a new issue