This release is a pre-release and may not be stable for production use.
distai
Package for the book Distributed AI Systems: A practical guide to building scalable training, inference, and serving systems for production AI.
Distributed PyTorch helpers for process setup, synchronized logging, and small model utilities.
Install
Install from PyPI:
pip install distai
Quick Usage
With torchrun (recommended)
torchrun --nproc_per_node=4 your_script.py
from distai import init_distributed, sync_print
rank, world_size, device, local_rank = init_distributed(use_cpu=False)
sync_print(f"Rank {rank} says hello", rank=rank, world_size=world_size)
Without torchrun
from distai import run_distributed
def my_worker(rank, world_size, device, local_rank):
print(f"Rank {rank} running on {device}")
run_distributed(my_worker, world_size=4, use_cpu=False)
See example_no_torchrun.py for a complete runnable example.
Public API
init_distributedsync_printrun_distributedget_node_infosetup_distributedcleanup_distributedget_resnet18_fashionmnistget_resnet18_cifar10
1 maintainer
Metadata
1 maintainer
Release files for distai 0.0.1.dev1
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