ezpz

KO | EN

gitlite — search

#python #hacktoberfest #ai #typescript #go #android #linux #java #awesome #kubernetes #awesome-list #vue #security #open-source

(★ 39)

Write once, run anywhere; ezpz 🍋

ezpz 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# 🍋 ezpz

> Write once, run anywhere.

`ezpz` makes distributed PyTorch launches portable across any supported
hardware {NVIDIA, AMD, Intel, MPS, CPU} with **zero code changes**.

## Features

- **Multi-hardware** — automatic device detection and backend selection
  (CUDA/NCCL, XPU/CCL, MPS, CPU/Gloo)
- **Zero code changes** — same script runs on a laptop, a single GPU, or a
  thousand-node supercomputer
- **HPC integration** — native PBS and SLURM support with automatic hostfile
  discovery and rank assignment
- **Metric tracking** — built-in `History` class for recording, plotting, and
  saving training metrics
- **CLI tools** — `ezpz launch`, `ezpz test`, `ezpz doctor` for launching
  jobs, smoke-testing, and diagnostics

## Quick Install

```bash
uv pip install git+https://github.com/saforem2/ezpz
```

## Quick Start

```python
import torch
import ezpz

rank = ezpz.setup_torch()           # auto-detects device + backend
device = ezpz.get_torch_device()
model = torch.nn.Linear(128, 10).to(device)
model = ezpz.wrap_model(model)       # FSDP (default)

# Multi-dim parallelism (TP/PP/CP) on XPU? Use ezpz.init_device_mesh_safe
# instead of torch's init_device_mesh — works around xccl's missing
# split_group on Aurora/Sunspot. See https://ezpz.cool/troubleshooting/.
```

```bash
# Same command everywhere -- Mac laptop, NVIDIA cluster, Intel Aurora:
ezpz launch python3 train.py
```

For a side-by-side diff against the equivalent raw-torch boilerplate, see
the [API Cheat Sheet](https://ezpz.cool/quickstart/#api-cheat-sheet).

## CLI

```bash
ezpz launch python3 train.py    # launch distributed training
ezpz submit -N 2 -q debug -- python3 train.py   # submit batch job to PBS/SLURM
ezpz test                       # smoke-test your setup
ezpz benchmark                  # run + compare example benchmarks
ezpz doctor                     # diagnose environment issues
```

## Why ezpz?

Compared to the alternatives:

- **vs raw `torchrun` / `mpirun` / `srun`**: one launcher that detects your
  scheduler, builds the right command, and works on a laptop too.
- **vs `accelerate`**: lower surface area, no config files, designed for
  HPC schedulers from the ground up rather than retrofitted.
- **vs `DeepSpeed`**: not an alternative — `ezpz` wraps your distributed
  init so you can still use DeepSpeed (or anything else) underneath.

See the [full comparison](https://ezpz.cool/compare/) for details.

## Documentation

Full documentation is available at [**ezpz.cool**](https://ezpz.cool).

Useful entry points:

- 🏃‍♂️ [Quickstart](https://ezpz.cool/quickstart/) — install → script → launch in 5 minutes
- 🎓 [Distributed Training Tutorial](https://ezpz.cool/guides/distributed-training/) — progressive hello-world → FSDP+TP
- 🍳 [Recipes](https://ezpz.cool/recipes/) — copy-pasteable patterns (checkpointing, gradient accumulation, MFU tracking)
- 🔧 [Troubleshooting](https://ezpz.cool/troubleshooting/) — XPU FSDP2 hangs, NCCL/CCL errors, scheduler issues
- 📝 [Examples](https://ezpz.cool/examples/) — runnable end-to-end (FSDP, ViT, Diffusion, HF Trainer)

ezpz

ezpz 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

ezpz

ezpz 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README