torch-levenberg-marquardt

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1.2.1 torch_levenberg_marquardt-1.2.1-py3-none-any.whl

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Project: torch-levenberg-marquardt
Version: 1.2.1
Filename: torch_levenberg_marquardt-1.2.1-py3-none-any.whl
Download: [link]
Size: 24412
MD5: 69d941e1790f062a125d06f6a2f58318
SHA256: f1e2092ddfa0fb3827a8e3f89be01f06c2c7bfe70b27bb87abf0d7da5c785aee
Uploaded: 2025-02-13 01:16:53 +0000

dist-info

METADATA

Metadata-Version: 2.2
Name: torch-levenberg-marquardt
Version: 1.2.1
Summary: PyTorch implementation of Levenberg-Marquardt training algorithm
Author-Email: Fabio Di Marco <fabiodimarco[at]hotmail.it>
Maintainer-Email: Fabio Di Marco <fabiodimarco[at]hotmail.it>
Project-Url: Home-page, https://github.com/fabiodimarco/torch-levenberg-marquardt
Project-Url: Bug Reports, https://github.com/fabiodimarco/torch-levenberg-marquardt/issues
Project-Url: Source, https://github.com/fabiodimarco/torch-levenberg-marquardt/
License: MIT License Copyright (c) 2024 Fabio Di Marco Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Keywords: pytorch,optimization,levenberg-marquardt,gauss-newton,training,numerical optimization,nonlinear least squares,second-order methods
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Python: >=3.9
Requires-Dist: torch (>=2.0.0)
Requires-Dist: numpy (>=1.22)
Requires-Dist: pytorch-lightning (>=1.9)
Requires-Dist: tqdm
Requires-Dist: torchmetrics (>=0.11.0)
Requires-Dist: black; extra == "dev"
Requires-Dist: flake8; extra == "dev"
Requires-Dist: importlib_metadata; extra == "dev"
Requires-Dist: coverage; extra == "test"
Provides-Extra: dev
Provides-Extra: test
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 16514 characters]

WHEEL

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Tag: py3-none-any

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top_level.txt

torch_levenberg_marquardt