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0.9.6a1 auDeep-0.9.6a1-py3-none-any.whl

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Project: auDeep
Version: 0.9.6a1
Filename: auDeep-0.9.6a1-py3-none-any.whl
Download: [link]
Size: 169492
MD5: b2da5ab22377cc5031276017dbd1761f
SHA256: 8a8d04f39ef708d85fb589527b8c5113459f575d6fab8424776a189afc87f8ac
Uploaded: 2021-01-24 12:30:45 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt · entry_points.txt · namespace_packages.txt

METADATA

Metadata-Version: 2.1
Name: auDeep
Version: 0.9.6a1
Summary: auDeep is a Python toolkit for unsupervised feature learning with deep neural networks (DNNs)
Author: Maurice Gerczuk
Author-Email: maurice.gerczuk[at]informatik.uni-augsburg.de
Home-Page: https://github.com/auDeep/auDeep
Project-Url: Source, https://github.com/auDeep/auDeep/
Project-Url: Tracker, https://github.com/auDeep/auDeep/issues
License: GPLv3+
Keywords: machine-learning audio-analysis science research
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: GPU :: NVIDIA CUDA :: 10.0
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3.7
Platform: Any
Requires-Dist: cliff (<3.4,>=3.3)
Requires-Dist: liac-arff (>=2.4)
Requires-Dist: matplotlib (>=3.2)
Requires-Dist: netCDF4 (==1.4.2)
Requires-Dist: pandas (<1.2,>=1.0)
Requires-Dist: pysoundfile (>=0.9)
Requires-Dist: scipy (>=1.4)
Requires-Dist: scikit-learn (>=0.23)
Requires-Dist: xarray (==0.10.0)
Requires-Dist: tensorflow-gpu (<2,>=1.15.2)
Description-Content-Type: text/markdown
[Description omitted; length: 1516 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.36.2)
Root-Is-Purelib: true
Tag: py3-none-any

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top_level.txt

audeep

entry_points.txt

[audeep.commands]
export = audeep.cli.export:Export
f-rae generate = audeep.cli.generate:GenerateFrequencyAutoencoder
f-rae train = audeep.cli.train:TrainFrequencyAutoencoder
ft-rae generate = audeep.cli.generate:GenerateFrequencyTimeAutoencoder
ft-rae train = audeep.cli.train:TrainFrequencyTimeAutoencoder
fuse = audeep.cli.fuse:FuseDataSets
fuse chunks = audeep.cli.fuse:FuseChunks
import = audeep.cli.import_data:Import
inspect netcdf = audeep.cli.inspect:InspectNetCDF
inspect raw = audeep.cli.inspect:InspectRaw
mlp evaluate = audeep.cli.evaluate:MLPEvaluation
mlp predict = audeep.cli.predict:MLPPrediction
modify = audeep.cli.modify:Modify
preprocess = audeep.cli.extract_spectrograms:ExtractSpectrograms
svm evaluate = audeep.cli.evaluate:SVMEvaluation
svm predict = audeep.cli.predict:SVMPrediction
t-rae generate = audeep.cli.generate:GenerateTimeAutoencoder
t-rae train = audeep.cli.train:TrainTimeAutoencoder
upsample = audeep.cli.upsample:Upsample
validate = audeep.cli.validate:Validate
visualize tsne = audeep.cli.visualize:VisualizeTSNE
[console_scripts]
audeep = audeep.main:main

namespace_packages.txt

[empty]