Pass mask in packing_iterator, correctly handle last batch, fix masking
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This commit does/fixes the following:

1. Adds unit tests for byte and patch packing to ensure it works correctly
2. Fixes a bug where for batches that end up with <max_length number of bytes (e.g., short patches), the mask was including elements that had value pad_id. This fixes the mask by setting it to be !=pad_id, if its not specified.
3. Correctly handles the last batch, where previously it would crash. This didn't affect training since we had enough data and/or looped iterators, but for evaluation perplexity, it comes up if we validation on an entire file.
4. Correctly forward the mask if it exists for byte packing

Test Plan:

```
pytest bytelatent/
```

Testing these changes more thoroughly in a stacked PR that fixes evals
This commit is contained in:
Pedro Rodriguez 2025-02-22 01:23:16 +00:00
parent 2655e4cf82
commit 203bff3696
2 changed files with 359 additions and 40 deletions

View file

@ -119,12 +119,18 @@ def truncate_batch(
y = np.full((batch.y.shape[0], max_length), pad_id, dtype=batch.y.dtype) y = np.full((batch.y.shape[0], max_length), pad_id, dtype=batch.y.dtype)
y[:, : batch.y.shape[1]] = batch.y y[:, : batch.y.shape[1]] = batch.y
batch.y = y batch.y = y
if batch.mask is not None and batch.mask.shape[1] < max_length: if batch.mask is None:
mask = np.full( mask = batch.x != pad_id
(batch.mask.shape[0], max_length), False, dtype=batch.mask.dtype # Only set the mask if its actually doing anything
) if mask.sum() != batch.x.size:
mask[:, : batch.mask.shape[1]] = batch.mask batch.mask = mask
batch.mask = mask else:
if batch.mask.shape[1] < max_length:
mask = np.full(
(batch.mask.shape[0], max_length), False, dtype=batch.mask.dtype
)
mask[:, : batch.mask.shape[1]] = batch.mask
batch.mask = mask
assert batch.x.shape[1] <= max_length assert batch.x.shape[1] <= max_length
assert batch.y.shape[1] <= max_length assert batch.y.shape[1] <= max_length
@ -173,31 +179,46 @@ class PackingIterator(StatefulIterator[Batch, PackingIteratorState]):
batch_size = self.packing_args.batch_size batch_size = self.packing_args.batch_size
pad_id = self.packing_args.pad_id pad_id = self.packing_args.pad_id
seq_len = self.packing_args.seq_len seq_len = self.packing_args.seq_len
stop_iteration = False
tokens: list[list[int]] = []
masks: list[list[bool]] = []
while True: while True:
tokens: list[list[int]] = [] try:
masks: list[list[bool]] = [] for _ in range(self.packing_args.batch_size):
sequence = next(sequence_iter)
for _ in range(self.packing_args.batch_size): _tokens = sequence.tokens
sequence = next(sequence_iter) _mask = sequence.mask
_tokens = sequence.tokens assert (
_mask = sequence.mask sequence.patch_lengths is None
assert ( ), "patch_lengths should not be used in byte packing"
sequence.patch_lengths is None tokens.append(_tokens)
), "patch_lengths should not be used in byte packing" masks.append(_mask)
tokens.append(_tokens) except StopIteration:
masks.append(_mask) # At this point, there will be no new sequences, so we need to stop
# after yielding the already accumulated data (one batch).
# In this case, either:
# 1. We have a complete batch, so things go as normal
# 2. We have an incomplete batch, but due to creating a right sized batch,
# then filling the values in, this case is automatically handled.
stop_iteration = True
x = np.full((batch_size, seq_len), fill_value=pad_id) x = np.full((batch_size, seq_len), fill_value=pad_id)
y = np.full((batch_size, seq_len), fill_value=pad_id) y = np.full((batch_size, seq_len), fill_value=pad_id)
m = np.zeros((batch_size, seq_len), dtype=np.bool)
for i, tok_seq in enumerate(tokens): for i, tok_seq in enumerate(tokens):
x[i, : len(tok_seq)] = tok_seq x[i, : len(tok_seq)] = tok_seq
y[i, : len(tok_seq) - 1] = tok_seq[1:] y[i, : len(tok_seq) - 1] = tok_seq[1:]
batch = Batch(x=x, y=y) m[i, : len(tok_seq)] = masks[i]
batch = Batch(x=x, y=y, mask=m)
assert ( assert (
batch.mask is None or np.sum(x != pad_id) == batch.mask.sum() batch.mask is None or np.sum(x != pad_id) == batch.mask.sum()
), f"{np.sum(x != pad_id)} != {batch.mask.sum()}" ), f"{np.sum(x != pad_id)} != {batch.mask.sum()}"
tokens = []
masks = []
yield batch yield batch
if stop_iteration:
break
def _create_iter_from_patch_lengths(self): def _create_iter_from_patch_lengths(self):
sequence_iter = self.sequence_iterator.create_iter() sequence_iter = self.sequence_iterator.create_iter()
@ -207,29 +228,36 @@ class PackingIterator(StatefulIterator[Batch, PackingIteratorState]):
pad_to_max_length = self.packing_args.pad_to_max_length pad_to_max_length = self.packing_args.pad_to_max_length
enable_byte_ngrams = self.packing_args.enable_byte_ngrams enable_byte_ngrams = self.packing_args.enable_byte_ngrams
max_length = self.packing_args.max_length max_length = self.packing_args.max_length
assert max_length is not None
tokens: list[list[int]] = []
masks: list[list[bool]] = []
patch_lengths: list[list[int]] = []
stop_iteration = False
while True: while True:
tokens: list[list[int]] = [] try:
masks: list[list[bool]] = [] for _ in range(self.packing_args.batch_size):
patch_lengths: list[list[int]] = [] sequence = next(sequence_iter)
_tokens = sequence.tokens
_mask = sequence.mask
_patch_lengths = sequence.patch_lengths
assert (
_patch_lengths is not None
), "patch lengths are required for packing based on patches."
# Reminder: seq_len is in terms of patches
assert len(sequence.patch_lengths) == self.packing_args.seq_len
last_patch_length = 0
if _patch_lengths[0] > 1:
last_patch_length = _patch_lengths[-1]
_patch_lengths[0] -= 1
_patch_lengths = [1] + _patch_lengths[:-1]
tokens.append(_tokens[: len(_tokens) - last_patch_length])
masks.append(_mask[: len(_mask) - last_patch_length])
patch_lengths.append(_patch_lengths)
except StopIteration:
stop_iteration = True
for _ in range(self.packing_args.batch_size): if len(tokens) == 0 and stop_iteration:
sequence = next(sequence_iter) break
_tokens = sequence.tokens
_mask = sequence.mask
_patch_lengths = sequence.patch_lengths
assert (
_patch_lengths is not None
), "patch lengths are required for packing based on patches."
# Reminder: seq_len is in terms of patches
assert len(sequence.patch_lengths) == self.packing_args.seq_len
last_patch_length = 0
if _patch_lengths[0] > 1:
last_patch_length = _patch_lengths[-1]
_patch_lengths[0] -= 1
_patch_lengths = [1] + _patch_lengths[:-1]
tokens.append(_tokens[: len(_tokens) - last_patch_length])
masks.append(_mask[: len(_mask) - last_patch_length])
patch_lengths.append(_patch_lengths)
x_patch_lengths = np.array(patch_lengths) x_patch_lengths = np.array(patch_lengths)
# pad batch to same length # pad batch to same length
@ -257,6 +285,10 @@ class PackingIterator(StatefulIterator[Batch, PackingIteratorState]):
ngram_ids=ngram_ids, ngram_ids=ngram_ids,
mask=_merge_patch_seq_masks(batch_size, tok_seq_len, masks), mask=_merge_patch_seq_masks(batch_size, tok_seq_len, masks),
) )
tokens = []
masks = []
patch_lengths = []
assert ( assert (
x_patch_lengths.sum() == x.size + batch_size x_patch_lengths.sum() == x.size + batch_size
), f"{x_patch_lengths.sum()} != {x.size + batch_size}" ), f"{x_patch_lengths.sum()} != {x.size + batch_size}"
@ -277,3 +309,5 @@ class PackingIterator(StatefulIterator[Batch, PackingIteratorState]):
enable_byte_ngrams=enable_byte_ngrams, enable_byte_ngrams=enable_byte_ngrams,
) )
yield batch yield batch
if stop_iteration:
break

View file

@ -0,0 +1,285 @@
import numpy as np
from bytelatent.data.data_types import BltSequence
from bytelatent.data.iterators.abstract_iterator import StatefulIterator
from bytelatent.data.iterators.packing_iterator import (
PackingArgs,
PackingIterator,
PackingMode,
)
class DummySequenceIterator(StatefulIterator):
def __init__(
self,
*,
seq_len: int,
n_seqs: int,
patch_lengths: list[int] | None = None,
pad_id: int = 0,
):
self.seq_len = seq_len
self.n_seqs = n_seqs
self.patch_lengths = patch_lengths
self.pad_id = pad_id
def get_state(self):
raise NotImplementedError()
def create_iter(self):
for i in range(self.n_seqs):
if self.patch_lengths is None:
tokens = np.arange(
i * self.seq_len + 1, (i + 1) * self.seq_len + 1
).tolist()
mask = [True] * self.seq_len # type: ignore
assert len(tokens) == self.seq_len
else:
n = sum(self.patch_lengths)
tokens = np.arange(i * n + 1, (i + 1) * n + 1).tolist()
assert len(tokens) == n
mask = [True] * n
assert len(mask) == len(tokens)
yield BltSequence(
tokens=tokens,
mask=mask,
patch_lengths=self.patch_lengths,
)
def create_bytes_iter(*, seq_len: int, n_seqs: int, batch_size: int, pad_id: int):
sequence_iterator = DummySequenceIterator(seq_len=seq_len, n_seqs=n_seqs)
packing_iterator = PackingIterator(
sequence_iterator,
packing_args=PackingArgs(
batch_size=batch_size,
seq_len=seq_len,
pad_id=pad_id,
packing_mode=PackingMode.BYTES,
max_length=None,
pad_to_max_length=False,
enable_byte_ngrams=False,
),
)
return packing_iterator.create_iter()
def create_patches_iter(
*,
seq_len: int,
n_seqs: int,
batch_size: int,
pad_id: int,
patch_lengths: list[int] | None,
max_length: int,
):
sequence_iterator = DummySequenceIterator(
# seq_len=number of bytes, which for blt/patches, is max_length since seq_len is
# in terms of number of patches
seq_len=max_length,
n_seqs=n_seqs,
patch_lengths=patch_lengths,
)
packing_iterator = PackingIterator(
sequence_iterator,
packing_args=PackingArgs(
batch_size=batch_size,
seq_len=seq_len,
pad_id=pad_id,
packing_mode=PackingMode.PATCHING,
max_length=max_length,
pad_to_max_length=True,
enable_byte_ngrams=False,
),
)
return packing_iterator.create_iter()
def test_last_batch_correctness_bytes():
seq_len = 1024
n_seqs = 10
batch_size = 4
pad_id = 0
iterator = create_bytes_iter(
seq_len=seq_len, n_seqs=n_seqs, batch_size=batch_size, pad_id=pad_id
)
batches = []
n_nonpad = 0
n_nonmask = 0
for b in iterator:
assert b.x.shape[0] == batch_size
assert b.x.shape[1] == seq_len
n_nonpad += (b.x != pad_id).sum()
if b.mask is None:
n_nonmask += b.x.size
else:
n_nonmask += b.mask.sum()
batches.append(b)
assert len(batches) == 3
assert n_nonpad == n_nonmask == seq_len * n_seqs
# The second half of the last batch should be all pads
assert batches[-1].mask[2:].sum() == 0
def test_edgecase_batch_correctness_bytes():
seq_len = 1024
n_seqs = 10
batch_size = 12
pad_id = 0
iterator = create_bytes_iter(
seq_len=seq_len, n_seqs=n_seqs, batch_size=batch_size, pad_id=pad_id
)
batches = []
n_nonpad = 0
n_nonmask = 0
for b in iterator:
assert b.x.shape[0] == batch_size
assert b.x.shape[1] == seq_len
n_nonpad += (b.x != pad_id).sum()
if b.mask is None:
n_nonmask += b.x.size
else:
n_nonmask += b.mask.sum()
batches.append(b)
assert len(batches) == 1
assert n_nonpad == n_nonmask == seq_len * n_seqs
# The second half of the last batch should be all pads
assert batches[0].mask[10:].sum() == 0
def test_exact_batch_correctness_bytes():
seq_len = 1024
n_seqs = 12
batch_size = 4
pad_id = 0
iterator = create_bytes_iter(
seq_len=seq_len, n_seqs=n_seqs, batch_size=batch_size, pad_id=pad_id
)
batches = []
n_nonpad = 0
n_nonmask = 0
for b in iterator:
assert b.x.shape[0] == batch_size
assert b.x.shape[1] == seq_len
n_nonpad += (b.x != pad_id).sum()
if b.mask is None:
n_nonmask += b.x.size
else:
n_nonmask += b.mask.sum()
batches.append(b)
assert len(batches) == 4
assert n_nonpad == n_nonmask == seq_len * n_seqs
def test_exact_batch_correctness_patches():
# First patch length is forced to be 1
patch_lengths = [1, 255, 256, 256, 256]
# Recall: This is in terms of bytes
max_length = 1024
# Recall: This is in terms of patches
seq_len = 5
n_seqs = 12
batch_size = 4
pad_id = 0
iterator = create_patches_iter(
seq_len=seq_len,
n_seqs=n_seqs,
batch_size=batch_size,
pad_id=pad_id,
patch_lengths=patch_lengths,
max_length=max_length,
)
batches = []
n_nonpad = 0
n_nonmask = 0
for batch in iterator:
assert batch.x.shape[0] == batch_size
assert batch.x.shape[1] == max_length
n_nonpad += (batch.x != pad_id).sum()
if batch.mask is None:
n_nonmask += batch.x.size
else:
n_nonmask += batch.mask.sum()
batches.append(batch)
assert len(batches) == 3
# max_length - 1 is due to chopping off the last byte for
# having a y target
assert n_nonpad == n_nonmask == (max_length - 1) * n_seqs
def test_short_batch_correctness_patches():
# First patch length is forced to be 1
# Total=48
patch_lengths = [1, 11, 12, 12, 12]
# Recall: This is in terms of bytes
max_length = 1024
# Recall: This is in terms of patches
seq_len = 5
n_seqs = 12
batch_size = 4
pad_id = 0
iterator = create_patches_iter(
seq_len=seq_len,
n_seqs=n_seqs,
batch_size=batch_size,
pad_id=pad_id,
patch_lengths=patch_lengths,
max_length=max_length,
)
batches = []
n_nonpad = 0
n_nonmask = 0
for batch in iterator:
assert batch.x.shape[0] == batch_size
assert batch.x.shape[1] == max_length
n_nonpad += (batch.x != pad_id).sum()
if batch.mask is None:
n_nonmask += batch.x.size
else:
n_nonmask += batch.mask.sum()
batches.append(batch)
assert len(batches) == 3
# We'll still always have one byte chopped off the end
assert n_nonpad == n_nonmask == ((sum(patch_lengths) - 1) * n_seqs)
def test_long_batch_correctness_patches():
# First patch length is forced to be 1
# Total=48
patch_lengths = [1, 255, 256, 256, 1024]
# Recall: This is in terms of bytes
max_length = 1024
# Recall: This is in terms of patches
seq_len = 5
n_seqs = 12
batch_size = 4
pad_id = 0
iterator = create_patches_iter(
seq_len=seq_len,
n_seqs=n_seqs,
batch_size=batch_size,
pad_id=pad_id,
patch_lengths=patch_lengths,
max_length=max_length,
)
batches = []
n_nonpad = 0
n_nonmask = 0
for batch in iterator:
assert batch.x.shape[0] == batch_size
assert batch.x.shape[1] == max_length
n_nonpad += (batch.x != pad_id).sum()
if batch.mask is None:
n_nonmask += batch.x.size
else:
n_nonmask += batch.mask.sum()
batches.append(batch)
assert len(batches) == 3
# No chop here since the next byte is available
assert n_nonpad == n_nonmask == max_length * n_seqs