a9ea9ba4a0
Please note: 1. I have manually tested the TFP release for python 3.10. 2. TFP does not define the set of python version that it is compatible with. This change should be followed up with the following changes: * Define the set of python version that TFP is compatible with. * Setup a Python package building test. * Release TFP so that projects depending on TFP can support Python 3.11 PiperOrigin-RevId: 572297305
39 lines
1.4 KiB
Text
39 lines
1.4 KiB
Text
# Requirements for Tensorflow Privacy.
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#
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# If you add a dependency here, also add the dependency to setup.py.
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#
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# * For packages that have a stable release, we use a version that is
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# compatible with that release (e.g. `~=x.y`). See
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# https://peps.python.org/pep-0440/#compatible-release for more information.
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# * For packages that do not have a stable release, we use a version that
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# matches a release that has been tested (e.g. `==x.y.z`). See
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# https://peps.python.org/pep-0440/#version-matching for more information.
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#
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# This assumes that the packages follows Semantic Versioning, see
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# https://semver.org/. If a package follows a different versioning scheme or
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# requires unique handling, we use a different version specifier and comment the
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# versioning scheme or reasoning.
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#
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# Note: As of 2022-08-17 there is bug in `pip` when multiple packages use the
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# compatible release operator `~=` to specify a version and one of those
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# versions ends in `0`. See https://github.com/pypa/pip/issues/9613 for more
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# information. In this case, use the equivalent clause `>=x.0,==x.*` instead of
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# `~=x.0`.
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absl-py>=1.0,==1.*
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attrs>=21.4
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dm-tree==0.1.8
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dp-accounting==0.4.3
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immutabledict~=2.2
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matplotlib~=3.3
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numpy~=1.21
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packaging~=22.0
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pandas~=1.4
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scikit-learn>=1.0,==1.*
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scipy~=1.9
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statsmodels~=0.13
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tensorflow-datasets~=4.5
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tensorflow-estimator~=2.4
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tensorflow-probability~=0.22.0
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tensorflow~=2.4
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tf-models-official~=2.13
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