why not update tensorflow to latest version?

[ghmole]

Expected Behavior

tensorflow latest version is 1.8, but in the anaconda repository, still keep version 1.1, I try to install package downloading from PYPI, but many package conflict, making some issue in my program, do you have a plan to update tensorflow version?

Steps to Reproduce

Anaconda or Miniconda version:

Operating System:

conda info

conda list --show-channel-urls

[183amir]

Tensorflow till 1.7 is available in conda (the defaults channel) (at least for linux).

conda search tensorflow
Loading channels: ...working... done
# Name                  Version           Build  Channel             
tensorflow            0.10.0rc0     np111py27_0  pkgs/free           
tensorflow            0.10.0rc0     np111py34_0  pkgs/free           
tensorflow            0.10.0rc0     np111py35_0  pkgs/free           
tensorflow                1.0.1     np112py27_0  pkgs/free           
tensorflow                1.0.1     np112py35_0  pkgs/free           
tensorflow                1.0.1     np112py36_0  pkgs/free           
tensorflow                1.1.0     np111py27_0  pkgs/free           
tensorflow                1.1.0     np111py35_0  pkgs/free           
tensorflow                1.1.0     np111py36_0  pkgs/free           
tensorflow                1.1.0     np112py27_0  pkgs/free           
tensorflow                1.1.0     np112py35_0  pkgs/free           
tensorflow                1.1.0     np112py36_0  pkgs/free           
tensorflow                1.2.1          py27_0  pkgs/free           
tensorflow                1.2.1          py35_0  pkgs/free           
tensorflow                1.2.1          py36_0  pkgs/free           
tensorflow                1.3.0               0  pkgs/free           
tensorflow                1.4.1               0  pkgs/main           
tensorflow                1.5.0               0  pkgs/main           
tensorflow                1.6.0               0  pkgs/main           
tensorflow                1.7.0               0  pkgs/main        

still it would be good to have 1.8 too. I need it as well.

[uathena1991]

I am using OSX, when I do conda search tensorflow, there are only 1.1.0 available...

conda search tensorflow
Loading channels: done
# Name                  Version           Build  Channel             
tensorflow                1.1.0     np112py27_0  pkgs/free           
tensorflow                1.1.0     np112py35_0  pkgs/free           
tensorflow                1.1.0     np112py36_0  pkgs/free  

[jjhelmus]

Tensorflow 1.8.0 is available for the linux-64 and win-64 platforms. We are still working on creating packages for OSX.

[183amir]

@jjhelmus I could not find the recipe of tensorflow-gpu 1.8. Is it publicly avialable?

[jjhelmus]

I need to sync a few recipes, including tensorflow-gpu. Will be available later today.

[radzfoto]

Can you also let us know the status of TF 1.8 on Windows 10, esp. tensorflow-gpu?

[jjhelmus]

@183amir The recipes used to build tensorflow can be found at https://github.com/AnacondaRecipes/tensorflow_recipes. Sorry for not getting these out earlier.

@radzfoto Tensorflow 1.8.0 is available for the win-64 platform for both Python 3.5 and 3.6. Work is ongoing to get a GPU version of Tensorflow 1.8.0 available for Windows.

[subashgandyer]

@jjhelmus How to get the tensorflow==1.8.0 for MacOSX? I get only 1.1.0 version. Help required here.

[jjhelmus]

We do not yet provide a Tensorflow 1.8.0 package on macOS.

[msarahan]

We are working to make this available as soon as possible, but there are currently segmentation faults in our builds that are preventing us from releasing them.

[scheckley]

can either the cpu or gpu version 1.8.0 be made available for ppc64le? thanks.

[nehaljwani]

Tensorflow 1.8.0 (GPU) is available for win-64 now.

If you have the CPU version installed, first uninstall it:

conda uninstall tensorflow 

Then install the GPU version:

conda install tensorflow-gpu

[DanielLenz]

I find tensorflow-gpu 1.8 and can also install it via conda install tensorflow-gpu=1.8, but the default version is 1.0.1.

Is this the intended behavior?

~$ conda search tensorflow-gpu
Loading channels: done

Name Version Build Channel

tensorflow-gpu 1.0.1 py27_4 pkgs/free
tensorflow-gpu 1.0.1 py35_4 pkgs/free
tensorflow-gpu 1.0.1 py36_4 pkgs/free
tensorflow-gpu 1.1.0 np111py27_0 pkgs/free
tensorflow-gpu 1.1.0 np111py35_0 pkgs/free
tensorflow-gpu 1.1.0 np111py36_0 pkgs/free
tensorflow-gpu 1.1.0 np112py27_0 pkgs/free
tensorflow-gpu 1.1.0 np112py35_0 pkgs/free
tensorflow-gpu 1.1.0 np112py36_0 pkgs/free
tensorflow-gpu 1.2.1 py27cuda7.5cudnn5.1_0 pkgs/free
tensorflow-gpu 1.2.1 py27cuda7.5cudnn6.0_0 pkgs/free
tensorflow-gpu 1.2.1 py27cuda8.0cudnn5.1_0 pkgs/free
tensorflow-gpu 1.2.1 py27cuda8.0cudnn6.0_0 pkgs/free
tensorflow-gpu 1.2.1 py35cuda7.5cudnn5.1_0 pkgs/free
tensorflow-gpu 1.2.1 py35cuda7.5cudnn6.0_0 pkgs/free
tensorflow-gpu 1.2.1 py35cuda8.0cudnn5.1_0 pkgs/free
tensorflow-gpu 1.2.1 py35cuda8.0cudnn6.0_0 pkgs/free
tensorflow-gpu 1.2.1 py36cuda7.5cudnn5.1_0 pkgs/free
tensorflow-gpu 1.2.1 py36cuda7.5cudnn6.0_0 pkgs/free
tensorflow-gpu 1.2.1 py36cuda8.0cudnn5.1_0 pkgs/free
tensorflow-gpu 1.2.1 py36cuda8.0cudnn6.0_0 pkgs/free
tensorflow-gpu 1.3.0 0 pkgs/free
tensorflow-gpu 1.4.1 0 pkgs/main
tensorflow-gpu 1.5.0 0 pkgs/main
tensorflow-gpu 1.6.0 0 pkgs/main
tensorflow-gpu 1.7.0 0 pkgs/main
tensorflow-gpu 1.8.0 h7b35bdc_0 pkgs/main
~$ conda install tensorflow-gpu
Solving environment: done

Package Plan

environment location: /home/dlenz/anaconda

added / updated specs:
- tensorflow-gpu

The following packages will be downloaded:

package                    |            build
---------------------------|-----------------
libprotobuf-3.5.2          |       h6f1eeef_0         4.2 MB
cudatoolkit-7.5            |                2       235.6 MB
cudnn-5.1                  |                0        77.2 MB
tensorflow-gpu-1.0.1       |           py36_4        77.6 MB
protobuf-3.5.2             |   py36hf484d3e_0         610 KB
------------------------------------------------------------
                                       Total:       395.1 MB

The following NEW packages will be INSTALLED:

cudatoolkit:    7.5-2
cudnn:          5.1-0
libprotobuf:    3.5.2-h6f1eeef_0
protobuf:       3.5.2-py36hf484d3e_0
tensorflow-gpu: 1.0.1-py36_4

~$ conda info

 active environment : None
        shell level : 0
   user config file : /home/dlenz/.condarc

populated config files :
conda version : 4.5.4
conda-build version : 3.10.5
python version : 3.6.5.final.0
base environment : /home/dlenz/anaconda (writable)
channel URLs : https://repo.anaconda.com/pkgs/main/linux-64
https://repo.anaconda.com/pkgs/main/noarch
https://repo.anaconda.com/pkgs/free/linux-64
https://repo.anaconda.com/pkgs/free/noarch
https://repo.anaconda.com/pkgs/r/linux-64
https://repo.anaconda.com/pkgs/r/noarch
https://repo.anaconda.com/pkgs/pro/linux-64
https://repo.anaconda.com/pkgs/pro/noarch
package cache : /home/dlenz/anaconda/pkgs
/home/dlenz/.conda/pkgs
envs directories : /home/dlenz/anaconda/envs
/home/dlenz/.conda/envs
platform : linux-64
user-agent : conda/4.5.4 requests/2.18.4 CPython/3.6.5 Linux/2.6.32-358.14.1.el6.x86_64 rhel/6.4 glibc/2.12
UID:GID : 6355:7580
netrc file : None
offline mode : False

[jjhelmus]

@DanielLenz

I'm not sure why conda is choosing that version of tensorflow-gpu. Can you provide the output of conda list? I suspect something already installed the environment is causing the solver to prefer the older version.

[DanielLenz]

Here you go:

/home/dlenz$ conda list
packages in environment at /home/dlenz/anaconda:

Name Version Build Channel
_ipyw_jlab_nb_ext_conf 0.1.0 py36he11e457_0
alabaster 0.7.10 py36h306e16b_0
anaconda 5.2.0 py36_3
anaconda-client 1.6.14 py36_0
anaconda-navigator 1.8.7 py36_0
anaconda-project 0.8.2 py36h44fb852_0
asn1crypto 0.24.0 py36_0
astroid 1.6.3 py36_0
astropy 3.0.2 py36h3010b51_1
attrs 18.1.0 py36_0
babel 2.5.3 py36_0
backcall 0.1.0 py36_0
backports 1.0 py36hfa02d7e_1
backports.shutil_get_terminal_size 1.0.0 py36hfea85ff_2
beautifulsoup4 4.6.0 py36h49b8c8c_1
bitarray 0.8.1 py36h14c3975_1
bkcharts 0.2 py36h735825a_0
blas 1.0 mkl
blaze 0.11.3 py36h4e06776_0
bleach 2.1.3 py36_0
blosc 1.14.3 hdbcaa40_0
bokeh 0.12.16 py36_0
boto 2.48.0 py36h6e4cd66_1
bottleneck 1.2.1 py36haac1ea0_0
bzip2 1.0.6 h14c3975_5
ca-certificates 2018.03.07 0
cairo 1.14.12 h7636065_2
certifi 2018.4.16 py36_0
cffi 1.11.5 py36h9745a5d_0
chardet 3.0.4 py36h0f667ec_1
click 6.7 py36h5253387_0
cloudpickle 0.5.3 py36_0
clyent 1.2.2 py36h7e57e65_1
colorama 0.3.9 py36h489cec4_0
conda 4.5.4 py36_0
conda-build 3.10.5 py36_0
conda-env 2.6.0 h36134e3_1
conda-verify 2.0.0 py36h98955d8_0
contextlib2 0.5.5 py36h6c84a62_0
cryptography 2.2.2 py36h14c3975_0
curl 7.60.0 h84994c4_0
cycler 0.10.0 py36h93f1223_0
cython 0.28.2 py36h14c3975_0
cytoolz 0.9.0.1 py36h14c3975_0
dask 0.17.5 py36_0
dask-core 0.17.5 py36_0
datashape 0.5.4 py36h3ad6b5c_0
dbus 1.13.2 h714fa37_1
decorator 4.3.0 py36_0
distributed 1.21.8 py36_0
docutils 0.14 py36hb0f60f5_0
entrypoints 0.2.3 py36h1aec115_2
et_xmlfile 1.0.1 py36hd6bccc3_0
expat 2.2.5 he0dffb1_0
fastcache 1.0.2 py36h14c3975_2
filelock 3.0.4 py36_0
flask 1.0.2 py36_1
flask-cors 3.0.4 py36_0
fontconfig 2.12.6 h49f89f6_0
freetype 2.8 hab7d2ae_1
get_terminal_size 1.0.0 haa9412d_0
gevent 1.3.0 py36h14c3975_0
glib 2.56.1 h000015b_0
glob2 0.6 py36he249c77_0
gmp 6.1.2 h6c8ec71_1
gmpy2 2.0.8 py36hc8893dd_2
graphite2 1.3.11 h16798f4_2
greenlet 0.4.13 py36h14c3975_0
gst-plugins-base 1.14.0 hbbd80ab_1
gstreamer 1.14.0 hb453b48_1
h5py 2.7.1 py36ha1f6525_2
harfbuzz 1.7.6 h5f0a787_1
hdf5 1.10.2 hba1933b_1
heapdict 1.0.0 py36_2
html5lib 1.0.1 py36h2f9c1c0_0
icu 58.2 h9c2bf20_1
idna 2.6 py36h82fb2a8_1
imageio 2.3.0 py36_0
imagesize 1.0.0 py36_0
intel-openmp 2018.0.0 8
ipykernel 4.8.2 py36_0
ipython 6.4.0 py36_0
ipython_genutils 0.2.0 py36hb52b0d5_0
ipywidgets 7.2.1 py36_0
isort 4.3.4 py36_0
itsdangerous 0.24 py36h93cc618_1
jbig 2.1 hdba287a_0
jdcal 1.4 py36_0
jedi 0.12.0 py36_1
jinja2 2.10 py36ha16c418_0
jpeg 9b h024ee3a_2
jsonschema 2.6.0 py36h006f8b5_0
jupyter 1.0.0 py36_4
jupyter_client 5.2.3 py36_0
jupyter_console 5.2.0 py36he59e554_1
jupyter_core 4.4.0 py36h7c827e3_0
jupyterlab 0.32.1 py36_0
jupyterlab_launcher 0.10.5 py36_0
kiwisolver 1.0.1 py36h764f252_0
lazy-object-proxy 1.3.1 py36h10fcdad_0
libcurl 7.60.0 h1ad7b7a_0
libedit 3.1.20170329 h6b74fdf_2
libffi 3.2.1 hd88cf55_4
libgcc-ng 7.2.0 hdf63c60_3
libgfortran-ng 7.2.0 hdf63c60_3
libpng 1.6.34 hb9fc6fc_0
libsodium 1.0.16 h1bed415_0
libssh2 1.8.0 h9cfc8f7_4
libstdcxx-ng 7.2.0 hdf63c60_3
libtiff 4.0.9 he85c1e1_1
libtool 2.4.6 h544aabb_3
libxcb 1.13 h1bed415_1
libxml2 2.9.8 h26e45fe_1
libxslt 1.1.32 h1312cb7_0
llvmlite 0.23.1 py36hdbcaa40_0
locket 0.2.0 py36h787c0ad_1
lxml 4.2.1 py36h23eabaa_0
lzo 2.10 h49e0be7_2
markupsafe 1.0 py36hd9260cd_1
matplotlib 2.2.2 py36h0e671d2_1
mccabe 0.6.1 py36h5ad9710_1
mistune 0.8.3 py36h14c3975_1
mkl 2018.0.2 1
mkl-service 1.1.2 py36h17a0993_4
mkl_fft 1.0.1 py36h3010b51_0
mkl_random 1.0.1 py36h629b387_0
more-itertools 4.1.0 py36_0
mpc 1.0.3 hec55b23_5
mpfr 3.1.5 h11a74b3_2
mpmath 1.0.0 py36hfeacd6b_2
msgpack-python 0.5.6 py36h6bb024c_0
multipledispatch 0.5.0 py36_0
navigator-updater 0.2.1 py36_0
nbconvert 5.3.1 py36hb41ffb7_0
nbformat 4.4.0 py36h31c9010_0
ncurses 6.1 hf484d3e_0
networkx 2.1 py36_0
nltk 3.3.0 py36_0
nose 1.3.7 py36hcdf7029_2
notebook 5.5.0 py36_0
numba 0.38.0 py36h637b7d7_0
numexpr 2.6.5 py36h7bf3b9c_0
numpy 1.14.3 py36hcd700cb_1
numpy-base 1.14.3 py36h9be14a7_1
numpydoc 0.8.0 py36_0
odo 0.5.1 py36h90ed295_0
olefile 0.45.1 py36_0
openpyxl 2.5.3 py36_0
openssl 1.0.2o h20670df_0
packaging 17.1 py36_0
pandas 0.23.0 py36h637b7d7_0
pandoc 1.19.2.1 hea2e7c5_1
pandocfilters 1.4.2 py36ha6701b7_1
pango 1.41.0 hd475d92_0
parso 0.2.0 py36_0
partd 0.3.8 py36h36fd896_0
patchelf 0.9 hf79760b_2
path.py 11.0.1 py36_0
pathlib2 2.3.2 py36_0
patsy 0.5.0 py36_0
pcre 8.42 h439df22_0
pep8 1.7.1 py36_0
pexpect 4.5.0 py36_0
pickleshare 0.7.4 py36h63277f8_0
pillow 5.1.0 py36h3deb7b8_0
pip 10.0.1 py36_0
pixman 0.34.0 hceecf20_3
pkginfo 1.4.2 py36_1
pluggy 0.6.0 py36hb689045_0
ply 3.11 py36_0
prompt_toolkit 1.0.15 py36h17d85b1_0
psutil 5.4.5 py36h14c3975_0
ptyprocess 0.5.2 py36h69acd42_0
py 1.5.3 py36_0
pycodestyle 2.4.0 py36_0
pycosat 0.6.3 py36h0a5515d_0
pycparser 2.18 py36hf9f622e_1
pycrypto 2.6.1 py36h14c3975_8
pycurl 7.43.0.1 py36hb7f436b_0
pyflakes 1.6.0 py36h7bd6a15_0
pygments 2.2.0 py36h0d3125c_0
pylint 1.8.4 py36_0
pyodbc 4.0.23 py36hf484d3e_0
pyopenssl 18.0.0 py36_0
pyparsing 2.2.0 py36hee85983_1
pyqt 5.9.2 py36h751905a_0
pysocks 1.6.8 py36_0
pytables 3.4.3 py36h02b9ad4_2
pytest 3.5.1 py36_0
pytest-arraydiff 0.2 py36_0
pytest-astropy 0.3.0 py36_0
pytest-doctestplus 0.1.3 py36_0
pytest-openfiles 0.3.0 py36_0
pytest-remotedata 0.2.1 py36_0
python 3.6.5 hc3d631a_2
python-dateutil 2.7.3 py36_0
pytz 2018.4 py36_0
pywavelets 0.5.2 py36he602eb0_0
pyyaml 3.12 py36hafb9ca4_1
pyzmq 17.0.0 py36h14c3975_0
qt 5.9.5 h7e424d6_0
qtawesome 0.4.4 py36h609ed8c_0
qtconsole 4.3.1 py36h8f73b5b_0
qtpy 1.4.1 py36_0
readline 7.0 ha6073c6_4
requests 2.18.4 py36he2e5f8d_1
rope 0.10.7 py36h147e2ec_0
ruamel_yaml 0.15.35 py36h14c3975_1
scikit-image 0.13.1 py36h14c3975_1
scikit-learn 0.19.1 py36h7aa7ec6_0
scipy 1.1.0 py36hfc37229_0
seaborn 0.8.1 py36hfad7ec4_0
send2trash 1.5.0 py36_0
setuptools 39.1.0 py36_0
simplegeneric 0.8.1 py36_2
singledispatch 3.4.0.3 py36h7a266c3_0
sip 4.19.8 py36hf484d3e_0
six 1.11.0 py36h372c433_1
snappy 1.1.7 hbae5bb6_3
snowballstemmer 1.2.1 py36h6febd40_0
sortedcollections 0.6.1 py36_0
sortedcontainers 1.5.10 py36_0
sphinx 1.7.4 py36_0
sphinxcontrib 1.0 py36h6d0f590_1
sphinxcontrib-websupport 1.0.1 py36hb5cb234_1
spyder 3.2.8 py36_0
sqlalchemy 1.2.7 py36h6b74fdf_0
sqlite 3.23.1 he433501_0
statsmodels 0.9.0 py36h3010b51_0
sympy 1.1.1 py36hc6d1c1c_0
tblib 1.3.2 py36h34cf8b6_0
terminado 0.8.1 py36_1
testpath 0.3.1 py36h8cadb63_0
tk 8.6.7 hc745277_3
toolz 0.9.0 py36_0
tornado 5.0.2 py36_0
traitlets 4.3.2 py36h674d592_0
typing 3.6.4 py36_0
unicodecsv 0.14.1 py36ha668878_0
unixodbc 2.3.6 h1bed415_0
urllib3 1.22 py36hbe7ace6_0
wcwidth 0.1.7 py36hdf4376a_0
webencodings 0.5.1 py36h800622e_1
werkzeug 0.14.1 py36_0
wheel 0.31.1 py36_0
widgetsnbextension 3.2.1 py36_0
wrapt 1.10.11 py36h28b7045_0
xlrd 1.1.0 py36h1db9f0c_1
xlsxwriter 1.0.4 py36_0
xlwt 1.3.0 py36h7b00a1f_0
xz 5.2.4 h14c3975_4
yaml 0.1.7 had09818_2
zeromq 4.2.5 h439df22_0
zict 0.1.3 py36h3a3bf81_0
zlib 1.2.11 ha838bed_2

[nehaljwani]

@DanielLenz This is happening because of the anaconda meta package. Try: conda uninstall anaconda and then conda install tensorflow-gpu or just create a new environment with only tensorflow-gpu

[DanielLenz]

That worked, thank you!

[nehaljwani]

xref: #4298

[hpeiyan]

Hi, there. Are you have the plan about TF's upgrading into 1.8 in Mac? Urgently require.

[csoja]

@huangpeiyan Currently, Tensorflow on macOS v 1.9, 1.10 & 1.11 are available in https://repo.anaconda.com/pkgs/main/osx-64/ As there are more recent versions available, we will not be adding an the older v1.8 for MacOS at this time. I'm going to go ahead and close this issue - as tensorflow is up to date in the Anaconda default repositories at this time.

[tessavdheiden]

Hi,

Tensorflow on macOS v 1.9, 1.10 & 1.11 are available, but we need 1.7!

[msarahan]

Sorry, but we can't provide old versions like that for free. The effort required is too great. You can:

• update your code to run on the newer versions (this is probably easiest)
• Try to build tensorflow yourself. This is very hard and very time consuming. Make sure you have a very powerful machine to build on, as running out of memory on bazel back then meant an infinite loop.
• consider having your employer contact sales@anaconda.com for options. Tensorflow builds take many hours for our team to work out. This would be a time & materials kind of thing.