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A conda-smithy repository for keras-tuner.

License: BSD 3-Clause "New" or "Revised" License

keras-tuner-feedstock's Introduction

About keras-tuner-feedstock

Feedstock license: BSD-3-Clause

Home: https://github.com/keras-team/keras-tuner

Package license: Apache-2.0

Summary: Hypertuner for Keras

Development: https://github.com/keras-team/keras-tuner

Documentation: https://keras-team.github.io/keras-tuner/

Current build status

All platforms:

Current release info

Name	Downloads	Version	Platforms

Installing keras-tuner

Installing keras-tuner from the conda-forge channel can be achieved by adding conda-forge to your channels with:

conda config --add channels conda-forge
conda config --set channel_priority strict

Once the conda-forge channel has been enabled, keras-tuner can be installed with conda:

conda install keras-tuner

or with mamba:

mamba install keras-tuner

It is possible to list all of the versions of keras-tuner available on your platform with conda:

conda search keras-tuner --channel conda-forge

or with mamba:

mamba search keras-tuner --channel conda-forge

Alternatively, mamba repoquery may provide more information:

# Search all versions available on your platform:
mamba repoquery search keras-tuner --channel conda-forge

# List packages depending on `keras-tuner`:
mamba repoquery whoneeds keras-tuner --channel conda-forge

# List dependencies of `keras-tuner`:
mamba repoquery depends keras-tuner --channel conda-forge

About conda-forge

conda-forge is a community-led conda channel of installable packages. In order to provide high-quality builds, the process has been automated into the conda-forge GitHub organization. The conda-forge organization contains one repository for each of the installable packages. Such a repository is known as a feedstock.

A feedstock is made up of a conda recipe (the instructions on what and how to build the package) and the necessary configurations for automatic building using freely available continuous integration services. Thanks to the awesome service provided by Azure, GitHub, CircleCI, AppVeyor, Drone, and TravisCI it is possible to build and upload installable packages to the conda-forge anaconda.org channel for Linux, Windows and OSX respectively.

To manage the continuous integration and simplify feedstock maintenance conda-smithy has been developed. Using the conda-forge.yml within this repository, it is possible to re-render all of this feedstock's supporting files (e.g. the CI configuration files) with conda smithy rerender.

For more information please check the conda-forge documentation.

Terminology

feedstock - the conda recipe (raw material), supporting scripts and CI configuration.

conda-smithy - the tool which helps orchestrate the feedstock. Its primary use is in the construction of the CI .yml files and simplify the management of many feedstocks.

conda-forge - the place where the feedstock and smithy live and work to produce the finished article (built conda distributions)

Updating keras-tuner-feedstock

If you would like to improve the keras-tuner recipe or build a new package version, please fork this repository and submit a PR. Upon submission, your changes will be run on the appropriate platforms to give the reviewer an opportunity to confirm that the changes result in a successful build. Once merged, the recipe will be re-built and uploaded automatically to the conda-forge channel, whereupon the built conda packages will be available for everybody to install and use from the conda-forge channel. Note that all branches in the conda-forge/keras-tuner-feedstock are immediately built and any created packages are uploaded, so PRs should be based on branches in forks and branches in the main repository should only be used to build distinct package versions.

In order to produce a uniquely identifiable distribution:

If the version of a package is not being increased, please add or increase the build/number.
If the version of a package is being increased, please remember to return the build/number back to 0.

Feedstock Maintainers

keras-tuner-feedstock's People

Contributors

Stargazers

Watchers

Forkers

regro-cf-autotick-bot rluria14 johnkyzer jennalipscomb conda-forge-linter anselmoo anacondarecipes anacondarecipes

keras-tuner-feedstock's Issues

Update dependency and add `pip check`

Solution to issue cannot be found in the documentation.

I checked the documentation.

Issue

Some of the dependencies of https://github.com/keras-team/keras-tuner/blob/master/setup.py are currently outdated in the currently used recipe.

Installed packages

# packages in environment at /Users/user/.pyenv/versions/miniconda3-latest/envs/feedstock:
#
# Name                    Version                   Build  Channel
beautifulsoup4            4.11.1             pyha770c72_0    conda-forge
brotlipy                  0.7.0           py310h8e9501a_1005    conda-forge
bzip2                     1.0.8                h3422bc3_4    conda-forge
ca-certificates           2022.12.7            h4653dfc_0    conda-forge
cctools                   973.0.1             hcbb26d4_11    conda-forge
cctools_osx-arm64         973.0.1             hef52d2f_11    conda-forge
certifi                   2022.12.7          pyhd8ed1ab_0    conda-forge
cffi                      1.15.1          py310h2399d43_3    conda-forge
chardet                   5.1.0           py310hbe9552e_0    conda-forge
charset-normalizer        2.1.1              pyhd8ed1ab_0    conda-forge
colorama                  0.4.6              pyhd8ed1ab_0    conda-forge
conda                     22.11.1         py310hbe9552e_1    conda-forge
conda-build               3.23.3          py310hbe9552e_1    conda-forge
conda-package-handling    2.0.2              pyh38be061_0    conda-forge
conda-package-streaming   0.7.0              pyhd8ed1ab_1    conda-forge
cryptography              38.0.4          py310hfc83b78_0    conda-forge
filelock                  3.9.0              pyhd8ed1ab_0    conda-forge
glob2                     0.7                        py_0    conda-forge
icu                       70.1                 h6b3803e_0    conda-forge
idna                      3.4                pyhd8ed1ab_0    conda-forge
jinja2                    3.1.2              pyhd8ed1ab_1    conda-forge
ld64                      609                 h619f069_11    conda-forge
ld64_osx-arm64            609                 h7167370_11    conda-forge
libarchive                3.6.2                h83f22c9_0    conda-forge
libcxx                    14.0.6               h2692d47_0    conda-forge
libffi                    3.4.2                h3422bc3_5    conda-forge
libiconv                  1.17                 he4db4b2_0    conda-forge
liblief                   0.12.3               hb7217d7_0    conda-forge
libllvm14                 14.0.6               hf6e71e7_1    conda-forge
libsqlite                 3.40.0               h76d750c_0    conda-forge
libxml2                   2.10.3               h87b0503_0    conda-forge
libzlib                   1.2.13               h03a7124_4    conda-forge
lz4-c                     1.9.3                hbdafb3b_1    conda-forge
lzo                       2.10              h642e427_1000    conda-forge
markupsafe                2.1.1           py310h8e9501a_2    conda-forge
ncurses                   6.3                  h07bb92c_1    conda-forge
openssl                   3.0.7                h03a7124_2    conda-forge
patch                     2.7.6             h27ca646_1002    conda-forge
pip                       22.3.1             pyhd8ed1ab_0    conda-forge
pkginfo                   1.9.2              pyhd8ed1ab_0    conda-forge
pluggy                    1.0.0              pyhd8ed1ab_5    conda-forge
psutil                    5.9.4           py310h8e9501a_0    conda-forge
py-lief                   0.12.3          py310h0f1eb42_0    conda-forge
pycosat                   0.6.4           py310h8e9501a_1    conda-forge
pycparser                 2.21               pyhd8ed1ab_0    conda-forge
pyopenssl                 22.1.0             pyhd8ed1ab_0    conda-forge
pysocks                   1.7.1              pyha2e5f31_6    conda-forge
python                    3.10.8          h3ba56d0_0_cpython    conda-forge
python-libarchive-c       4.0             py310hbe9552e_2    conda-forge
python_abi                3.10                    3_cp310    conda-forge
pytz                      2022.7             pyhd8ed1ab_0    conda-forge
pyyaml                    6.0             py310h8e9501a_5    conda-forge
readline                  8.1.2                h46ed386_0    conda-forge
requests                  2.28.1             pyhd8ed1ab_1    conda-forge
ripgrep                   13.0.0               h65448a5_2    conda-forge
ruamel.yaml               0.17.21         py310h8e9501a_2    conda-forge
ruamel.yaml.clib          0.2.7           py310h8e9501a_1    conda-forge
setuptools                65.6.3             pyhd8ed1ab_0    conda-forge
sigtool                   0.1.3                h44b9a77_0    conda-forge
six                       1.16.0             pyh6c4a22f_0    conda-forge
soupsieve                 2.3.2.post1        pyhd8ed1ab_0    conda-forge
tapi                      1100.0.11            he4954df_0    conda-forge
tk                        8.6.12               he1e0b03_0    conda-forge
toml                      0.10.2             pyhd8ed1ab_0    conda-forge
toolz                     0.12.0             pyhd8ed1ab_0    conda-forge
tqdm                      4.64.1             pyhd8ed1ab_0    conda-forge
tzdata                    2022g                h191b570_0    conda-forge
urllib3                   1.26.13            pyhd8ed1ab_0    conda-forge
wheel                     0.38.4             pyhd8ed1ab_0    conda-forge
xz                        5.2.6                h57fd34a_0    conda-forge
yaml                      0.2.5                h3422bc3_2    conda-forge
zstandard                 0.19.0          py310had9512b_1    conda-forge
zstd                      1.5.2                h8128057_4    conda-forge

Environment info

active environment : feedstock
    active env location : /Users/user/.pyenv/versions/miniconda3-latest/envs/feedstock
            shell level : 1
       user config file : /Users/user/.condarc
 populated config files : /Users/user/.condarc
          conda version : 4.12.0
    conda-build version : not installed
         python version : 3.9.15.final.0
       virtual packages : __osx=13.1=0
                          __unix=0=0
                          __archspec=1=arm64
       base environment : /Users/user/.pyenv/versions/miniconda3-latest  (writable)
      conda av data dir : /Users/user/.pyenv/versions/miniconda3-latest/etc/conda
  conda av metadata url : None
           channel URLs : https://conda.anaconda.org/conda-forge/osx-arm64
                          https://conda.anaconda.org/conda-forge/noarch
                          https://repo.anaconda.com/pkgs/main/osx-arm64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/r/osx-arm64
                          https://repo.anaconda.com/pkgs/r/noarch
          package cache : /Users/user/.pyenv/versions/miniconda3-latest/pkgs
                          /Users/user/.conda/pkgs
       envs directories : /Users/user/.pyenv/versions/miniconda3-latest/envs
                          /Users/user/.conda/envs
               platform : osx-arm64
             user-agent : conda/4.12.0 requests/2.28.1 CPython/3.9.15 Darwin/22.2.0 OSX/13.1
                UID:GID : 502:20
             netrc file : None
           offline mode : False

keras-tuner 1.3.5 only claims compatibility with python >=3.8

Solution to issue cannot be found in the documentation.

I checked the documentation.

Issue

The conda-forge packages for keras-tuner v1.3.5 show python >=3.7 as dependencies. However, according to the keras-tuner README, v1.3.5 of keras-tuner claims to need python >=3.8.

Installed packages

N/A

Environment info

N/A

@conda-forge-admin, please add user @anselmoo

Additional comment:

The current keras-tuner version has been outdated for several months.

tensorflow=2.10.0 to 2.11.1 are incompatible with latest keras-tuner=1.3.4 (python 3.10) [protobuf version limit]

Solution to issue cannot be found in the documentation.

I checked the documentation.

Issue

Hello,
I tried to install keras-tuner=1.3.4 with tensorflow=2.10 to tensorflow=2.11.1 in linux-64 with python=3.10.
They are incompatible and the order of installation does not no matter.
tensorflow=2.9.1 works with python=3.10.8

install commands:

✓ mamba install tensorflow=2.9.1 keras-tuner=1.3.4 -c conda-forge (python=3.10.8)

✕ mamba install tensorflow=2.10 keras-tuner=1.3.4 -c conda-forge
✕ mamba install tensorflow=2.11.0 keras-tuner=1.3.4 -c conda-forge
✕ mamba install tensorflow=2.11.1 keras-tuner=1.3.4 -c conda-forge

Error outputs:

└─ tensorflow 2.10**  is installable with the potential options
   ├─ tensorflow 2.10.0 would require
   │  └─ tensorflow-base 2.10.0 cpu_py310hc537a0e_0, which requires
   │     └─ libprotobuf >=3.21.6,<3.22.0a0 , which conflicts with any installable versions previously reported;

└─ tensorflow 2.11.0**  is installable with the potential options
   ├─ tensorflow 2.11.0 would require
   │  └─ tensorflow-base [2.11.0 cpu_py310*_0|2.11.0 cuda112py310*_0], which requires
   │     └─ libprotobuf >=3.21.11,<3.22.0a0 , which conflicts with any installable versions previously reported;

└─ tensorflow 2.11.1**  is installable with the potential options
   ├─ tensorflow 2.11.1 would require
   │  └─ tensorflow-base [2.11.1 cpu_py310h335d60c_0|2.11.1 cuda112py310h4c92a00_0], which requires
   │     └─ libprotobuf >=3.21.12,<3.22.0a0 , which conflicts with any installable versions previously reported;

keras-tuner=1.3.4 on python 3.10 requires protobuf=3.20.3 which requiers libprotobuf=3.20.3. They are all available on conda-forge.

Installed packages

# packages in environment at /home/me/software/mambaforge/envs/img:
#
# Name                    Version                   Build  Channel
_libgcc_mutex             0.1                 conda_forge    conda-forge
_openmp_mutex             4.5                       2_gnu    conda-forge
bzip2                     1.0.8                h7f98852_4    conda-forge
ca-certificates           2022.12.7            ha878542_0    conda-forge
ld_impl_linux-64          2.40                 h41732ed_0    conda-forge
libffi                    3.4.2                h7f98852_5    conda-forge
libgcc-ng                 12.2.0              h65d4601_19    conda-forge
libgomp                   12.2.0              h65d4601_19    conda-forge
libnsl                    2.0.0                h7f98852_0    conda-forge
libsqlite                 3.40.0               h753d276_0    conda-forge
libuuid                   2.38.1               h0b41bf4_0    conda-forge
libzlib                   1.2.13               h166bdaf_4    conda-forge
ncurses                   6.3                  h27087fc_1    conda-forge
openssl                   3.1.0                h0b41bf4_0    conda-forge
pip                       23.0.1             pyhd8ed1ab_0    conda-forge
python                    3.10.10         he550d4f_0_cpython    conda-forge
readline                  8.2                  h8228510_1    conda-forge
setuptools                67.6.1             pyhd8ed1ab_0    conda-forge
tk                        8.6.12               h27826a3_0    conda-forge
tzdata                    2023c                h71feb2d_0    conda-forge
wheel                     0.40.0             pyhd8ed1ab_0    conda-forge
xz                        5.2.6                h166bdaf_0    conda-forge

Environment info

active environment : img
    active env location : /home/me/software/mambaforge/envs/img
            shell level : 10
       user config file : /home/me/.condarc
 populated config files : /home/me/software/mambaforge/.condarc
                          /home/me/.condarc
          conda version : 23.3.1
    conda-build version : not installed
         python version : 3.10.10.final.0
       virtual packages : __archspec=1=x86_64
                          __cuda=12.1=0
                          __glibc=2.37=0
                          __linux=5.15.90.1=0
                          __unix=0=0
       base environment : /home/me/software/mambaforge  (writable)
      conda av data dir : /home/me/software/mambaforge/etc/conda
  conda av metadata url : None
           channel URLs : https://conda.anaconda.org/conda-forge/linux-64
                          https://conda.anaconda.org/conda-forge/noarch
          package cache : /home/me/software/mambaforge/pkgs
                          /home/me/.conda/pkgs
       envs directories : /home/me/software/mambaforge/envs
                          /home/me/.conda/envs
               platform : linux-64
             user-agent : conda/23.3.1 requests/2.28.2 CPython/3.10.10 Linux/5.15.90.1-microsoft-standard-WSL2 opensuse-tumbleweed/20230407 glibc/2.37
                UID:GID : 1000:1000
             netrc file : None
           offline mode : False

conda-forge / keras-tuner-feedstock Goto Github PK

keras-tuner-feedstock's Introduction

About keras-tuner-feedstock

Current build status

Current release info

Installing keras-tuner

About conda-forge

Terminology

Updating keras-tuner-feedstock

Feedstock Maintainers

keras-tuner-feedstock's People

Contributors

Stargazers

Watchers

Forkers

keras-tuner-feedstock's Issues

Solution to issue cannot be found in the documentation.

Issue

Installed packages

Environment info

Solution to issue cannot be found in the documentation.

Issue

Installed packages

Environment info

Additional comment:

Solution to issue cannot be found in the documentation.

Issue

Installed packages

Environment info

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