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fastwonn

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0.0.9 fastwonn-0.0.9-py3-none-any.whl

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Project: fastwonn
Version: 0.0.9
Filename: fastwonn-0.0.9-py3-none-any.whl
Download: [link]
Size: 7863
MD5: 51b3bcb54ff1e958f402b98e6ac7e1ef
SHA256: 27eb05868663617dd9e5179dac6d4cddbce5a060b736dfd97c344b26b77b0aa0
Uploaded: 2024-07-08 01:38:02 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt · zip-safe

METADATA

Metadata-Version: 2.1
Name: fastwonn
Version: 0.0.9
Summary: Fast, GPU-friendly, differentiable computation of Intrinsic Dimension via Maximum Likelihood, the TwoNN algorithm, and everything in between!
Author: Emanuele Ballarin
Author-Email: emanuele[at]ballarin.cc
Home-Page: https://github.com/emaballarin/fastwonn
License: MIT
Keywords: Deep Learning,Differentiable Programming,Intrinsic Dimension,Machine Learning,Manifold Learning,Maximum Likelihood Estimation,PyTorch,TwoNN
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Environment :: Console
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.10
Requires-Dist: torch (>=2)
Requires-Dist: torchsort (>=0.1.9)
Requires-Dist: faiss-cpu (>=1.8.0); extra == "faiss-cpu"
Requires-Dist: faiss-gpu-cu11 (>=1.8.0.2); extra == "faiss-gpu-newer-cu11"
Requires-Dist: faiss-gpu-cu12 (>=1.8.0.2); extra == "faiss-gpu-newer-cu12"
Requires-Dist: faiss-gpu (>=1.7.2); extra == "faiss-gpu-older"
Requires-Dist: keopscore (>=2.2.3); extra == "keops"
Requires-Dist: pykeops (>=2.2.3); extra == "keops"
Provides-Extra: faiss_cpu
Provides-Extra: faiss_gpu_newer_cu11
Provides-Extra: faiss_gpu_newer_cu12
Provides-Extra: faiss_gpu_older
Provides-Extra: keops
Description-Content-Type: text/markdown
[Description omitted; length: 681 characters]

WHEEL

Wheel-Version: 1.0
Generator: setuptools (70.2.0)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
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fastwonn-0.0.9.dist-info/RECORD — —

top_level.txt

fastwonn

zip-safe