Spaces:
Running
on
Zero
Running
on
Zero
File size: 6,911 Bytes
bcc039b fc3399e 63913e4 bcc039b fc3399e bcc039b fc3399e bcc039b 63913e4 bcc039b fc3399e bcc039b fc3399e bcc039b fc3399e bcc039b 63913e4 bcc039b 7622d28 bcc039b 7622d28 bcc039b 63913e4 bcc039b fc3399e bcc039b 7622d28 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from logging import getLogger
from typing import Any
import numpy as np
from pydantic import BaseModel, ConfigDict
from bytelatent.data.data_types import BltSequence
from bytelatent.data.iterators.abstract_iterator import (
PydanticIteratorState,
StatefulIterator,
)
from bytelatent.data.iterators.arrow_iterator import ArrowFileIterator
from bytelatent.data.iterators.limit_iterator import LimitIterator
from bytelatent.data.iterators.looping_iterator import LoopingIterator
from bytelatent.data.iterators.preprocess_iterator import (
PreprocessIterator,
PreprocessIteratorState,
)
logger = getLogger()
class SequencePackingArgs(BaseModel):
model_config = ConfigDict(extra="forbid")
output_seq_len: int
buffer_size: int
class SequenceIteratorState(PydanticIteratorState):
model_config = ConfigDict(extra="forbid")
sequence_packing_args: SequencePackingArgs
preprocess_iterator_state: PreprocessIteratorState
# If None, rng is disabled.
rng_state: dict[str, Any] | None
def build(self):
preprocess_iterator = self.preprocess_iterator_state.build()
return SequenceIterator(
preprocess_iterator,
sequence_packing_args=self.sequence_packing_args,
rng_state=self.rng_state,
)
def get_datafile(
iterator: PreprocessIterator | ArrowFileIterator | LoopingIterator | LimitIterator,
):
if isinstance(iterator, ArrowFileIterator):
return f"file={iterator.file_path} n_shards={len(iterator.dataset_files) if iterator.dataset_files is not None else None}"
elif isinstance(iterator, PreprocessIterator):
return get_datafile(iterator.arrow_iterator)
elif isinstance(iterator, LoopingIterator):
return get_datafile(iterator.file_iterator)
elif isinstance(iterator, LimitIterator):
return get_datafile(iterator.base_iterator)
else:
raise NotImplementedError()
class SequenceIterator(StatefulIterator):
def __init__(
self,
preprocess_iterator: PreprocessIterator,
*,
rng_state: dict[str, Any] | None,
sequence_packing_args: SequencePackingArgs,
):
self.preprocess_iterator = preprocess_iterator
self.sequence_packing_args = sequence_packing_args
self.output_seq_len = sequence_packing_args.output_seq_len
self.buffer_size = sequence_packing_args.buffer_size
if rng_state is None:
self.rng = None
else:
self.rng = np.random.default_rng()
self.rng.bit_generator.state = rng_state
def get_state(self):
# TODO: need to also perist the current shuffle buffer
return SequenceIteratorState(
sequence_packing_args=self.sequence_packing_args,
preprocess_iterator_state=self.preprocess_iterator.get_state(),
rng_state=None if self.rng is None else self.rng.bit_generator.state,
)
def create_iter(self):
example_iter = self.preprocess_iterator.create_iter()
n_buffer_patches = self.buffer_size * self.output_seq_len
patch_lengths: list[int] = []
tokens: list[int] = []
mask: list[bool] = []
first = True
logger.info(
"Starting first buffer for: %s",
get_datafile(self.preprocess_iterator),
)
for example in example_iter:
assert example.tokens is not None
assert example.mask is not None
if self.preprocess_iterator.add_patches:
assert example.patch_lengths is not None
assert len(example.tokens) == sum(example.patch_lengths)
else:
assert example.patch_lengths is None
assert len(example.tokens) != 0
assert len(example.mask) != 0
assert len(example.tokens) == len(example.mask)
tokens.extend(example.tokens)
mask.extend(example.mask)
if self.preprocess_iterator.add_patches:
patch_lengths.extend(example.patch_lengths)
else:
# This lets the rest of the code work as expected and just yield byte seqs
patch_lengths.extend([1] * len(example.tokens))
while len(patch_lengths) >= n_buffer_patches:
if first:
first = False
logger.info(
"First buffer complete for: %s",
get_datafile(self.preprocess_iterator),
)
x_patches = np.array(patch_lengths[:n_buffer_patches]).reshape(
self.buffer_size, self.output_seq_len
)
seq_tokens = []
seq_mask = []
start_id = 0
# We fix the number of patches and therefore global steps per batch
# so we have a variable number of tokens we need to account for
for num_tokens in x_patches.sum(axis=-1):
seq_tokens.append(tokens[start_id : start_id + num_tokens])
seq_mask.append(mask[start_id : start_id + num_tokens])
start_id += num_tokens
assert start_id == x_patches.sum()
# Remove what we just added from the buffer
patch_lengths = patch_lengths[n_buffer_patches:]
tokens = tokens[x_patches.sum() :]
mask = mask[x_patches.sum() :]
seq_patch_lengths: list[list[int]] = x_patches.tolist()
assert len(seq_patch_lengths) == self.buffer_size
if self.rng is None:
permutations = list(range(len(seq_patch_lengths)))
else:
permutations = self.rng.permutation(len(seq_patch_lengths))
for idx in permutations:
assert len(seq_patch_lengths[idx]) == self.output_seq_len
assert (
sum(seq_patch_lengths[idx])
== len(seq_tokens[idx])
== len(seq_mask[idx])
), f"{sum(seq_patch_lengths[idx])}, {len(seq_tokens[idx])} {len(seq_mask[idx])}, idx={idx}"
assert seq_patch_lengths[idx][0] > 0, f"{seq_patch_lengths[idx]}"
if self.preprocess_iterator.add_patches:
yield BltSequence(
tokens=seq_tokens[idx],
mask=seq_mask[idx],
patch_lengths=seq_patch_lengths[idx],
)
else:
yield BltSequence(
tokens=seq_tokens[idx],
mask=seq_mask[idx],
patch_lengths=None,
)
|