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[C++] fix helpers import #364

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Merged
mayank31398 merged 3 commits into from
Jan 30, 2026
Merged

[C++] fix helpers import #364

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e526a4d
drop _tied_weights_keys
mayank31398 Jan 30, 2026
5721d4c
drop _tied_weights_keys
mayank31398 Jan 30, 2026
d01c20c
drop _tied_weights_keys
mayank31398 Jan 30, 2026
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24 changes: 15 additions & 9 deletions lm_engine/data/megatron/utils/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,9 @@ class Split(Enum):
test = 2


_HELPERS = None


def compile_helpers() -> None:
"""Compile C++ helper functions at runtime. Make sure this is invoked on a single process."""

Expand All @@ -24,37 +27,40 @@ def compile_helpers() -> None:
build_directory = os.path.join(os.path.dirname(__file__), "build")
os.makedirs(build_directory, exist_ok=True)

if ProcessGroupManager.get_global_rank() == 0:
load_cpp_extension(
def _compile():
global _HELPERS
_HELPERS = load_cpp_extension(
"helpers",
sources=os.path.join(os.path.dirname(__file__), "helpers.cpp"),
extra_cflags=["-O3", "-Wall", "-shared", "-std=c++11", "-fPIC", "-fdiagnostics-color"],
build_directory=build_directory,
verbose=True,
)

if ProcessGroupManager.get_global_rank() == 0:
_compile()

Communication.barrier()

if ProcessGroupManager.get_global_rank() != 0:
_compile()


def build_blending_indices(
dataset_index: np.ndarray, dataset_sample_index: np.ndarray, weights: list[float], num_datasets: int, size: int
) -> None:
import helpers

helpers.build_blending_indices(dataset_index, dataset_sample_index, weights, num_datasets, size)
_HELPERS.build_blending_indices(dataset_index, dataset_sample_index, weights, num_datasets, size)


def build_sample_idx(
sizes: np.ndarray, doc_idx: np.ndarray, sequence_length: int, num_epochs: int, tokens_per_epoch: int
) -> np.ndarray:
import helpers

if doc_idx.dtype == np.int32:
log_rank_0(logging.INFO, f"using int32 for sample idx")
sample_idx = helpers.build_sample_idx_int32(sizes, doc_idx, sequence_length, num_epochs, tokens_per_epoch)
sample_idx = _HELPERS.build_sample_idx_int32(sizes, doc_idx, sequence_length, num_epochs, tokens_per_epoch)
elif doc_idx.dtype == np.int64:
log_rank_0(logging.INFO, f"using int64 for sample idx")
sample_idx = helpers.build_sample_idx_int64(sizes, doc_idx, sequence_length, num_epochs, tokens_per_epoch)
sample_idx = _HELPERS.build_sample_idx_int64(sizes, doc_idx, sequence_length, num_epochs, tokens_per_epoch)
else:
raise ValueError("unexpected dtype for doc_idx")

Expand Down
3 changes: 1 addition & 2 deletions lm_engine/train_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,6 @@

import torch
from torch.distributed import ReduceOp
from transformers import AutoConfig

from .enums import GradientCheckpointingMethod
from .hf_models import CommonConfig, is_custom_model
Expand Down Expand Up @@ -86,7 +85,7 @@ def _get_attention_flops(batch_size: int, sequence_length: int, hidden_size: int


def get_model_tflops(
config: AutoConfig | CommonConfig,
config: CommonConfig,
batch_size: int,
sequence_length: int,
gradient_checkpointing_method: GradientCheckpointingMethod | None,
Expand Down