Bagua is a deep learning training acceleration framework for PyTorch. It provides a one-stop training acceleration solution, including faster distributed training compared to PyTorch DDP, faster dataloader, kernel fusion, and more.

bagua

__init__.py

bagua_define.py

distributed

launch.py

run.py

script

baguarun.py

service

autotune_service.py

autotune_system.py

autotune_task_manager.py

bayesian_optimizer.py

torch_api

algorithms

async_model_average.py

base.py

bytegrad.py

decentralized.py

gradient_allreduce.py

q_adam.py

bucket.py

checkpoint

checkpointing.py

communication.py

contrib

cache_loader.py

cached_dataset.py

fuse

optimizer.py

load_balancing_data_loader.py

sync_batchnorm.py

utils

redis_store.py

store.py

data_parallel

bagua_distributed.py

distributed.py

functional.py

env.py

model_parallel

experts.py

layer.py

sharded_moe.py

utils.py

tensor.py

version.py

bagua_core

.data

bagua-net

libnccl-net.so

_environment.py

bagua_core.cpython-39-x86_64-linux-gnu.so

bagua_install_deps.py

bagua_cuda113-0.9.2.data

scripts

bagua_sys_perf

bagua_cuda113-0.9.2.dist-info

LICENSE

METADATA

RECORD

WHEEL

entry_points.txt

top_level.txt

bagua_cuda113.libs

libhwloc-8a7ce5b6.so.5.7.5

libltdl-35340011.so.7.3.0

libmpi-d86d2ca3.so.40.10.3

libnuma-428e8baf.so.1.0.0

libopen-pal-f100aaec.so.40.10.3

libopen-rte-22dd953b.so.40.10.3

libz-4e3ca1c7.so.1.2.7

tests

internal

common_utils.py

compressor.py

multi_process.py

torch

_core.py

common_cuda.py

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bagua-cuda113

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