par-meta commited on
Commit
aeb95f1
·
unverified ·
1 Parent(s): ff36aa8

Remove byte tokenizer and add config args to switch between byte/patch packing (#68)

Browse files

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/
```

bytelatent/args.py CHANGED
@@ -14,14 +14,18 @@ from bytelatent.data.iterators.abstract_iterator import StatefulIterator
14
  from bytelatent.data.iterators.arrow_iterator import ArrowFileIterator
15
  from bytelatent.data.iterators.looping_iterator import LoopingIterator
16
  from bytelatent.data.iterators.multiprocess_iterator import MultiprocessIterator
17
- from bytelatent.data.iterators.packing_iterator import PackingArgs, PackingIterator
 
 
 
 
18
  from bytelatent.data.iterators.preprocess_iterator import PreprocessIterator
19
  from bytelatent.data.iterators.sampling_iterator import SamplingIterator
20
  from bytelatent.data.iterators.sequence_iterator import (
21
  SequenceIterator,
22
  SequencePackingArgs,
23
  )
24
- from bytelatent.data.patcher import PatcherArgs
25
  from bytelatent.distributed import DistributedArgs, EnvironmentArgs
26
  from bytelatent.metrics import LoggingArgs
27
  from bytelatent.model.blt import ByteLatentTransformerArgs
@@ -202,7 +206,11 @@ class DataloaderArgs(BaseModel):
202
  max_length=self.max_encoder_seq_length,
203
  pad_to_max_length=self.pad_to_max_length,
204
  enable_byte_ngrams=self.enable_byte_ngrams,
205
- tokenizer_name=self.tokenizer_args.name,
 
 
 
 
206
  )
207
  packing_iterator = PackingIterator(sampling_iterator, packing_args=packing_args)
208
  if self.load_async:
 
14
  from bytelatent.data.iterators.arrow_iterator import ArrowFileIterator
15
  from bytelatent.data.iterators.looping_iterator import LoopingIterator
16
  from bytelatent.data.iterators.multiprocess_iterator import MultiprocessIterator
17
+ from bytelatent.data.iterators.packing_iterator import (
18
+ PackingArgs,
19
+ PackingIterator,
20
+ PackingMode,
21
+ )
22
  from bytelatent.data.iterators.preprocess_iterator import PreprocessIterator
23
  from bytelatent.data.iterators.sampling_iterator import SamplingIterator
24
  from bytelatent.data.iterators.sequence_iterator import (
25
  SequenceIterator,
26
  SequencePackingArgs,
27
  )
28
+ from bytelatent.data.patcher import PatcherArgs, PatchingModeEnum
29
  from bytelatent.distributed import DistributedArgs, EnvironmentArgs
30
  from bytelatent.metrics import LoggingArgs
31
  from bytelatent.model.blt import ByteLatentTransformerArgs
 
206
  max_length=self.max_encoder_seq_length,
207
  pad_to_max_length=self.pad_to_max_length,
208
  enable_byte_ngrams=self.enable_byte_ngrams,
209
+ packing_mode=(
210
+ PackingMode.BYTES
211
+ if self.patcher_args.patching_mode == PatchingModeEnum.byte
212
+ else PackingMode.PATCHING
213
+ ),
214
  )
215
  packing_iterator = PackingIterator(sampling_iterator, packing_args=packing_args)
216
  if self.load_async:
bytelatent/configs/entropy_model.yaml CHANGED
@@ -55,7 +55,7 @@ data:
55
  # so pick the most efficient, so static
56
  patching_mode: byte
57
  tokenizer_args:
58
- name: bytes
59
 
60
  profiling:
61
  run: false
 
55
  # so pick the most efficient, so static
56
  patching_mode: byte
57
  tokenizer_args:
58
+ name: blt
59
 
60
  profiling:
61
  run: false
bytelatent/data/iterators/packing_iterator.py CHANGED
@@ -1,4 +1,5 @@
1
  # Copyright (c) Meta Platforms, Inc. and affiliates.
 
2
  from typing import Any
3
 
4
  import numpy as np
@@ -12,6 +13,11 @@ from bytelatent.data.iterators.abstract_iterator import (
12
  from bytelatent.data.iterators.sampling_iterator import SamplingIteratorState
13
 
14
 
 
 
 
 
 
15
  class PackingArgs(BaseModel):
16
  model_config = ConfigDict(extra="forbid")
17
  batch_size: int
@@ -20,7 +26,7 @@ class PackingArgs(BaseModel):
20
  max_length: int | None
21
  pad_to_max_length: bool
22
  enable_byte_ngrams: bool
23
- tokenizer_name: str
24
 
25
 
26
  class PackingIteratorState(PydanticIteratorState):
@@ -155,10 +161,12 @@ class PackingIterator(StatefulIterator[Batch, PackingIteratorState]):
155
  )
156
 
157
  def create_iter(self):
158
- if self.packing_args.tokenizer_name == "bytes":
159
  return self._create_iter_from_bytes()
160
- else:
161
  return self._create_iter_from_patch_lengths()
 
 
162
 
163
  def _create_iter_from_bytes(self):
164
  sequence_iter = self.sequence_iterator.create_iter()
 
1
  # Copyright (c) Meta Platforms, Inc. and affiliates.
2
+ from enum import Enum
3
  from typing import Any
4
 
5
  import numpy as np
 
13
  from bytelatent.data.iterators.sampling_iterator import SamplingIteratorState
14
 
15
 
16
+ class PackingMode(str, Enum):
17
+ BYTES = "bytes"
18
+ PATCHING = "patching"
19
+
20
+
21
  class PackingArgs(BaseModel):
22
  model_config = ConfigDict(extra="forbid")
23
  batch_size: int
 
26
  max_length: int | None
27
  pad_to_max_length: bool
28
  enable_byte_ngrams: bool
29
+ packing_mode: PackingMode
30
 
31
 
32
  class PackingIteratorState(PydanticIteratorState):
 
161
  )
162
 
163
  def create_iter(self):
164
+ if self.packing_args.packing_mode == PackingMode.BYTES:
165
  return self._create_iter_from_bytes()
166
+ elif self.packing_args.packing_mode == PackingMode.PATCHING:
167
  return self._create_iter_from_patch_lengths()
168
+ else:
169
+ raise ValueError(f"Invalid patching mode: {self.packing_args.packing_mode}")
170
 
171
  def _create_iter_from_bytes(self):
172
  sequence_iter = self.sequence_iterator.create_iter()
bytelatent/tokenizers/build_tokenizer.py CHANGED
@@ -5,7 +5,6 @@ from typing import Any
5
  from pydantic import BaseModel
6
 
7
  from bytelatent.tokenizers.blt_tokenizer import BltTokenizer
8
- from bytelatent.tokenizers.byte_tokenizer import ByteTokenizer
9
  from bytelatent.tokenizers.tiktoken_tokenizer import TikTokenTokenizer
10
 
11
  try:
@@ -55,8 +54,6 @@ class TokenizerArgs(BaseModel):
55
  init_kwargs = self.init_kwargs
56
  if self.name == "blt":
57
  return BltTokenizer(**init_kwargs)
58
- elif self.name == "bytes":
59
- return ByteTokenizer(**init_kwargs)
60
  elif self.name == "mock":
61
  return MockTokenizer(**init_kwargs)
62
  elif self.name == "sp":
 
5
  from pydantic import BaseModel
6
 
7
  from bytelatent.tokenizers.blt_tokenizer import BltTokenizer
 
8
  from bytelatent.tokenizers.tiktoken_tokenizer import TikTokenTokenizer
9
 
10
  try:
 
54
  init_kwargs = self.init_kwargs
55
  if self.name == "blt":
56
  return BltTokenizer(**init_kwargs)
 
 
57
  elif self.name == "mock":
58
  return MockTokenizer(**init_kwargs)
59
  elif self.name == "sp":
bytelatent/tokenizers/byte_tokenizer.py DELETED
@@ -1,35 +0,0 @@
1
- # Copyright (c) Meta Platforms, Inc. and affiliates.
2
- from bytelatent.tokenizers.abstract_tokenizer import Tokenizer
3
-
4
-
5
- class ByteTokenizer(Tokenizer):
6
- def __init__(self):
7
- self.bos_id = 256
8
- self.eos_id = 257
9
- self.n_words = 258
10
-
11
- def encode(self, s: str, add_bos: bool = False, add_eos: bool = False):
12
- tokens = [self.bos_id] * add_bos + list(s.encode()) + [self.eos_id] * add_eos
13
- return tokens
14
-
15
- def decode(self, tokens: list[int]):
16
- byte_tokens = bytes([t for t in tokens if t < 256])
17
- return byte_tokens.decode("utf-8", errors="backslashreplace")
18
-
19
- def get_token_offsets(
20
- self, text: str, tokens: list[int] | None = None
21
- ) -> tuple[list[str], list[int]]:
22
- if tokens is None:
23
- tokens = self.encode(text)
24
-
25
- decoded_chars, offsets = [], []
26
- byte_pos = 0
27
- for token in tokens:
28
- if token < 256:
29
- char = bytes([token]).decode("utf-8", errors="ignore")
30
- if char:
31
- decoded_chars.append(char)
32
- offsets.append(byte_pos)
33
- byte_pos += len(char.encode("utf-8"))
34
-
35
- return decoded_chars, offsets