crossfit
Multi Node Multi GPU Offline Inference and metric calculation library
Installation
Install this library using pip:
pip install crossfit
Installation from source (for cuda 12.x)
git clone https://github.com/rapidsai/crossfit.git
cd crossfit
pip install --extra-index-url https://pypi.nvidia.com ".[cuda12x]"
Usage
Usage instructions go here.
Development
To contribute to this library, first create a conda environment with the necessary dependencies:
cd crossfit
mamba env create -f conda/environments/cuda_dev.yaml
conda activate crossfit_dev
Now install the dependencies and test dependencies:
pip install -e '.[test]'
To run the tests:
pytest
Metadata
Release files for crossfit 0.0.9
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| crossfit-0.0.9.tar.gz | 97.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| crossfit-0.0.9-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 276.0 kB
Release files / crossfit-0.0.9.tar.gz
| Download URL | crossfit-0.0.9.tar.gz |
|---|---|
| Size | 97.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
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Release files / crossfit-0.0.9-py3-none-any.whl
| Download URL | crossfit-0.0.9-py3-none-any.whl |
|---|---|
| Size | 178.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
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