Metadata-Version: 2.4
Name: warpscale
Version: 0.1.1
Summary: Warpscale PyTorch training SDK
Project-URL: Homepage, https://warpscale.ai
Project-URL: Documentation, https://docs.warpscale.ai
Author-email: Orbit CI Inc <support@warpscale.ai>
License-Expression: Apache-2.0
License-File: LICENSE
Keywords: gpu,machine-learning,observability,pytorch,telemetry,training
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: System :: Monitoring
Requires-Python: >=3.9
Description-Content-Type: text/markdown

# warpscale

Python SDK to report PyTorch training progress to Warpscale.

## Install

```bash
pip install warpscale
```

## Use

```python
import warpscale

# Once, after dist.init_process_group().
warpscale.init(total_steps=40_000, total_epochs=3, framework="fsdp", precision="bf16")

# Call on every rank; rank 0 emits, the rest are no-ops.
for epoch in range(epochs):
    for batch in loader:
        ...                       # one optimizer step
        warpscale.step()
    warpscale.epoch()
    warpscale.checkpoint_started()
    save_checkpoint()             # incl. the async dcp.async_save tail
    warpscale.checkpoint_persisted()
```
