Is there a date for when Anaconda will support Cudnn > 7.3.1 along with Tensorflow 2.0

[00krishna]

Actual Behavior

My basic question is whether there is a date set for upgrading from Cudnn 7.3.1 to a newer version. Also, when will Anaconda move to a newer version of the cudatoolkit?

Most Tensorflow 2.0 stuff works in Anaconda. But I ran into one particular issue where I got an error like this.

Loaded runtime CuDNN library: 7.3.1 but source was
    compiled with: 7.4.2.  CuDNN library major and
    minor version needs to match or have higher minor
    version in case of CuDNN 7.0 or later version. If
    using a binary install, upgrade your CuDNN 
   library. If building from sources, make sure the
   library loaded at runtime is compatible with the version
 specified during compile configuration.

I opened an issue on the Conda repo, but the issue was closed with essentially no response--other than saying that Anaconda does not support Tensorflow 2.0

https://github.com/conda/conda/issues/8736

So I was just wondering when updated libraries would be available?

Expected Behavior

Steps to Reproduce

I created a conda environment with conda create -n tf2alpha tensorflow-gpu==2.0.0-alpha0 anaconda

Then I created a notebook and ran the code below.

    import tensorflow as tf
    import matplotlib.pyplot as plt
    import numpy as np
    from sklearn.datasets import load_sample_image

    # Load sample images
    china = load_sample_image("china.jpg") / 255
    flower = load_sample_image("flower.jpg") / 255
    images = np.array([china, flower])
    batch_size, height, width, channels = images.shape

    # Create 2 filters
    filters = np.zeros(shape=(7, 7, channels, 2), dtype=np.float32)
    filters[:, 3, :, 0] = 1  # vertical line
    filters[3, :, :, 1] = 1  # horizontal line

    outputs = tf.nn.conv2d(images, filters, strides=1, padding="SAME")

    plt.imshow(outputs[0, :, :, 1], cmap="gray") # plot 1st image's 2nd feature map
    plt.axis("off") # Not shown in the book
    plt.show()

Anaconda or Miniconda version:

Operating System:

conda info

``` PASTE OUTPUT HERE: conda info active environment : base active env location : /media/hayagriva/anaconda3 shell level : 1 user config file : /home/krishnab/.condarc populated config files : /home/krishnab/.condarc conda version : 4.6.14 conda-build version : 3.17.8 python version : 3.6.6.final.0 base environment : /media/hayagriva/anaconda3 (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 package cache : /media/hayagriva/anaconda3/pkgs /home/krishnab/.conda/pkgs envs directories : /media/hayagriva/anaconda3/envs /home/krishnab/.conda/envs platform : linux-64 user-agent : conda/4.6.14 requests/2.21.0 CPython/3.6.6 Linux/4.15.0-50-generic ubuntu/18.04.2 glibc/2.27 UID:GID : 1000:1000 netrc file : None offline mode : False ```

conda list --show-channel-urls

``` PASTE OUTPUT HERE: ➜ conda list --show-channel-urls # packages in environment at /media/hayagriva/anaconda3: # # Name Version Build Channel _ipyw_jlab_nb_ext_conf 0.1.0 py36_0 defaults _r-mutex 1.0.0 mro_2 r _tflow_select 2.1.0 gpu defaults absl-py 0.7.1 pypi_0 pypi affine 2.2.0 pypi_0 pypi alabaster 0.7.12 py36_0 defaults anaconda custom py36hbbc8b67_0 defaults anaconda-client 1.7.2 py36_0 defaults anaconda-navigator 1.9.6 py36_0 defaults anaconda-project 0.8.2 py36_0 defaults appdirs 1.4.3 py36h28b3542_0 defaults arrow 0.13.1 pypi_0 pypi asn1crypto 0.24.0 py36_0 defaults astor 0.8.0 pypi_0 pypi astroid 2.1.0 py36_0 defaults astropy 3.1.2 py36h7b6447c_0 defaults atomicwrites 1.3.0 py_0 defaults attrs 18.2.0 py36h28b3542_0 defaults automat 0.7.0 py36_0 defaults awscli 1.16.142 pypi_0 pypi babel 2.6.0 py36_0 defaults backcall 0.1.0 py36_0 defaults backports 1.0 py36_1 defaults backports.os 0.1.1 py36_0 defaults backports.shutil_get_terminal_size 1.0.0 py36_2 defaults beautifulsoup4 4.7.1 py36_1 defaults binaryornot 0.4.4 pypi_0 pypi binutils_impl_linux-64 2.31.1 h6176602_1 defaults binutils_linux-64 2.31.1 h6176602_6 defaults bitarray 0.8.3 py36h14c3975_0 defaults bkcharts 0.2 py36_0 defaults blas 1.0 openblas defaults blaze 0.11.3 py36_0 defaults bleach 3.1.0 py36_0 defaults blosc 1.15.0 hd408876_0 defaults bokeh 1.0.4 py36_0 defaults boto 2.49.0 py36_0 defaults boto3 1.9.132 pypi_0 pypi botocore 1.12.132 pypi_0 pypi bottleneck 1.2.1 py36h035aef0_1 defaults bzip2 1.0.6 h14c3975_5 defaults c-ares 1.15.0 h7b6447c_1 defaults ca-certificates 2019.1.23 0 defaults cairo 1.14.12 h8948797_3 defaults certifi 2019.3.9 py36_0 defaults cffi 1.12.1 py36h2e261b9_0 defaults chardet 3.0.4 py36_1 defaults click 7.0 py36_0 defaults click-plugins 1.0.3 pypi_0 pypi cligj 0.4.0 pypi_0 pypi cloudpickle 0.8.0 py36_0 defaults clyent 1.2.2 py36_1 defaults cmake 3.13.1 pypi_0 pypi colorama 0.3.9 pypi_0 pypi conda 4.6.14 py36_0 defaults conda-build 3.17.8 py36_0 defaults conda-env 2.6.0 1 defaults conda-verify 3.1.1 py36_0 defaults condamagic 0.2.1 pypi_0 pypi constantly 15.1.0 py36h28b3542_0 defaults contextlib2 0.5.5 py36_0 defaults cookiecutter 1.6.0 pypi_0 pypi cryptography 2.3.1 py36hc365091_0 defaults cryptography-vectors 2.5 py_0 defaults cudatoolkit 9.2 0 defaults cudnn 7.3.1 cuda9.2_0 defaults cupti 9.2.148 0 defaults curl 7.61.0 h84994c4_0 defaults cycler 0.10.0 py36_0 defaults cython 0.29.5 py36he6710b0_0 defaults cytoolz 0.9.0.1 py36h14c3975_1 defaults dask 1.1.3 py_0 defaults dask-core 1.1.3 py_0 defaults datadog 0.28.0 pypi_0 pypi datashape 0.5.4 py36_1 defaults dbus 1.13.6 h746ee38_0 defaults decorator 4.3.2 py36_0 defaults defusedxml 0.5.0 py36_1 defaults distributed 1.26.0 py36_1 defaults docutils 0.14 py36_0 defaults entrypoints 0.3 py36_0 defaults et_xmlfile 1.0.1 py36_0 defaults expat 2.2.6 he6710b0_0 defaults fastcache 1.0.2 py36h14c3975_2 defaults fftw 3.3.8 h7b6447c_3 defaults filelock 3.0.10 py36_0 defaults fiona 1.7.13 pypi_0 pypi flask 1.0.2 py36_1 defaults flask-cors 3.0.7 py36_0 defaults fontconfig 2.13.0 h9420a91_0 defaults freetype 2.9.1 h8a8886c_1 defaults fribidi 1.0.5 h7b6447c_0 defaults future 0.17.1 py36_0 defaults gast 0.2.2 pypi_0 pypi gcc_impl_linux-64 7.3.0 habb00fd_1 defaults gcc_linux-64 7.3.0 h553295d_6 defaults geopandas 0.4.0 pypi_0 pypi get_terminal_size 1.0.0 haa9412d_0 defaults gevent 1.4.0 py36h7b6447c_0 defaults gfortran_impl_linux-64 7.3.0 hdf63c60_1 defaults gfortran_linux-64 7.3.0 h553295d_6 defaults glib 2.56.2 hd408876_0 defaults glob2 0.6 py36_1 defaults gmp 6.1.2 h6c8ec71_1 defaults gmpy2 2.0.8 py36h10f8cd9_2 defaults google-pasta 0.1.7 pypi_0 pypi gradient-statsd 1.0.1 pypi_0 pypi graphite2 1.3.13 h23475e2_0 defaults greenlet 0.4.15 py36h7b6447c_0 defaults grpcio 1.21.1 pypi_0 pypi gst-plugins-base 1.14.0 hbbd80ab_1 defaults gstreamer 1.14.0 hb453b48_1 defaults gxx_impl_linux-64 7.3.0 hdf63c60_1 defaults gxx_linux-64 7.3.0 h553295d_6 defaults h5py 2.9.0 py36h7918eee_0 defaults harfbuzz 1.8.8 hffaf4a1_0 defaults hdf5 1.10.4 hb1b8bf9_0 defaults heapdict 1.0.0 py36_2 defaults hide-code 0.5.2 pypi_0 pypi html5lib 1.0.1 py36_0 defaults hyperlink 18.0.0 py36_0 defaults icu 58.2 h9c2bf20_1 defaults idna 2.8 py36_0 defaults imageio 2.5.0 py36_0 defaults imagesize 1.1.0 py36_0 defaults importlib_metadata 0.7 py36_0 defaults incremental 17.5.0 py36_0 defaults intel-openmp 2019.1 144 defaults ipykernel 5.1.0 py36h39e3cac_0 defaults ipython 7.3.0 py36h39e3cac_0 defaults ipython_genutils 0.2.0 py36_0 defaults ipywidgets 7.4.2 py36_0 defaults isort 4.3.8 py36_0 defaults itsdangerous 1.1.0 py36_0 defaults jbig 2.1 hdba287a_0 defaults jdcal 1.4 py36_0 defaults jedi 0.13.3 py36_0 defaults jeepney 0.4 py36_0 defaults jinja2 2.10 py36_0 defaults jinja2-time 0.2.0 pypi_0 pypi jmespath 0.9.4 pypi_0 pypi jpeg 9b h024ee3a_2 defaults jsonschema 2.6.0 py36_0 defaults jupyter 1.0.0 py36_7 defaults jupyter_client 5.2.4 py36_0 defaults jupyter_console 6.0.0 py36_0 defaults jupyter_core 4.4.0 py36_0 defaults jupyterlab 0.35.3 py36_0 defaults jupyterlab_launcher 0.13.1 py36_0 defaults jupyterlab_server 0.2.0 py36_0 defaults kaggle 1.4.7.1 pypi_0 pypi keras-applications 1.0.8 pypi_0 pypi keras-preprocessing 1.1.0 pypi_0 pypi keyring 18.0.0 py36_0 defaults kiwisolver 1.0.1 py36hf484d3e_0 defaults lazy-object-proxy 1.3.1 py36h14c3975_2 defaults libarchive 3.3.3 h7d0bbab_0 defaults libcurl 7.61.0 h1ad7b7a_0 defaults libedit 3.1.20181209 hc058e9b_0 defaults libffi 3.2.1 hd88cf55_4 defaults libgcc 7.2.0 h69d50b8_2 defaults libgcc-ng 8.2.0 hdf63c60_1 defaults libgfortran 3.0.0 1 conda-forge libgfortran-ng 7.3.0 hdf63c60_0 defaults libgit2 0.27.5 h5ee2e84_0 conda-forge liblief 0.9.0 h7725739_2 defaults libopenblas 0.3.3 h5a2b251_3 defaults libpng 1.6.36 hbc83047_0 defaults libprotobuf 3.6.1 hd408876_0 defaults libsodium 1.0.16 h1bed415_0 defaults libssh2 1.8.0 h9cfc8f7_4 defaults libstdcxx-ng 8.2.0 hdf63c60_1 defaults libtiff 4.0.10 h2733197_2 defaults libtool 2.4.6 h7b6447c_5 defaults libuuid 1.0.3 h1bed415_2 defaults libxcb 1.13 h1bed415_1 defaults libxml2 2.9.9 he19cac6_0 defaults libxslt 1.1.33 h7d1a2b0_0 defaults llvmlite 0.27.0 py36hd408876_0 defaults locket 0.2.0 py36_1 defaults lxml 4.3.1 py36hefd8a0e_0 defaults lz4-c 1.8.1.2 h14c3975_0 defaults lzo 2.10 h49e0be7_2 defaults make 4.2.1 h1bed415_1 defaults markdown 3.1.1 pypi_0 pypi markupsafe 1.1.1 py36h7b6447c_0 defaults matplotlib 3.0.2 py36h5429711_0 defaults mccabe 0.6.1 py36_1 defaults metis 5.1.0 hf484d3e_4 defaults mistune 0.8.4 py36h7b6447c_0 defaults mkl 2018.0.3 1 defaults mkl-service 1.1.2 py36h651fb7a_4 defaults mkl_fft 1.0.1 py36h3010b51_0 defaults mkl_random 1.0.1 py36h629b387_0 defaults more-itertools 5.0.0 py36_0 defaults mpc 1.1.0 h10f8cd9_1 defaults mpfr 4.0.1 hdf1c602_3 defaults mpmath 1.1.0 py36_0 defaults mro-base 3.5.1 3 r mro-base_impl 3.5.1 h9a62091_0 r mro-basics 3.5.1 0 r msgpack-python 0.6.1 py36hfd86e86_1 defaults multipledispatch 0.6.0 py36_0 defaults munch 2.3.2 pypi_0 pypi mypy 0.620 pypi_0 pypi navigator-updater 0.2.1 py36_0 defaults nbconvert 5.3.1 py36_0 defaults nbformat 4.4.0 py36_0 defaults ncurses 6.1 he6710b0_1 defaults networkx 2.2 py36_1 defaults nltk 3.4 py36_1 defaults nomkl 3.0 0 defaults nose 1.3.7 py36_2 defaults notebook 5.7.4 py36_0 defaults numba 0.42.0 py36h962f231_0 defaults numexpr 2.6.9 py36h2ffa06c_0 defaults numpy 1.16.4 pypi_0 pypi numpy-base 1.16.2 py36h2f8d375_0 defaults numpydoc 0.8.0 py36_0 defaults odo 0.5.1 py36_0 defaults olefile 0.46 py36_0 defaults openblas 0.3.3 3 defaults openblas-devel 0.3.3 3 defaults openlibm 0.5.4 0 conda-forge openpyxl 2.6.0 py36_0 defaults openspecfun 0.5.3 h26a2512_0 conda-forge openssl 1.0.2r h7b6447c_0 defaults packaging 19.0 py36_0 defaults pandas 0.24.1 py36he6710b0_0 defaults pandoc 2.2.3.2 0 defaults pandocfilters 1.4.2 py36_1 defaults pango 1.42.4 h049681c_0 defaults paperspace 0.0.19 pypi_0 pypi parso 0.3.4 py36_0 defaults partd 0.3.9 py36_0 defaults patchelf 0.9 he6710b0_3 defaults path.py 11.5.0 py36_0 defaults pathlib2 2.3.3 py36_0 defaults patsy 0.5.1 py36_0 defaults pcre 8.42 h439df22_0 defaults pcre2 10.23 2 conda-forge pdfkit 0.6.1 pypi_0 pypi pep8 1.7.1 py36_0 defaults pexpect 4.6.0 py36_0 defaults pickleshare 0.7.5 py36_0 defaults pillow 5.4.1 py36h34e0f95_0 defaults pip 18.1 pypi_0 pypi pixman 0.36.0 h7b6447c_0 defaults pkginfo 1.5.0.1 py36_0 defaults plotly 3.4.1 pypi_0 pypi pluggy 0.9.0 py36_0 defaults ply 3.11 py36_0 defaults powerline-status 2.7 pypi_0 pypi poyo 0.4.2 pypi_0 pypi prometheus_client 0.6.0 py36_0 defaults prompt_toolkit 2.0.9 py36_0 defaults protobuf 3.8.0 pypi_0 pypi psutil 5.5.0 py36h7b6447c_0 defaults ptyprocess 0.6.0 py36_0 defaults py 1.8.0 py36_0 defaults py-lief 0.9.0 py36h7725739_2 defaults pyasn1 0.4.5 py_0 defaults pyasn1-modules 0.2.4 py36_0 defaults pycodestyle 2.5.0 py36_0 defaults pycosat 0.6.3 py36h14c3975_0 defaults pycparser 2.19 py36_0 defaults pycrypto 2.6.1 py36h14c3975_9 defaults pycurl 7.43.0.2 py36hb7f436b_0 defaults pyflakes 2.1.0 py36_0 defaults pygments 2.3.1 py36_0 defaults pyhamcrest 1.9.0 py36_2 defaults pylint 2.2.2 py36_0 defaults pyodbc 4.0.26 py36he6710b0_0 defaults pyopenssl 19.0.0 py36_0 defaults pyparsing 2.3.1 py36_0 defaults pyproj 1.9.5.1 pypi_0 pypi pyqt 5.9.2 py36h05f1152_2 defaults pysocks 1.6.8 py36_0 defaults pytables 3.4.4 py36h71ec239_0 defaults pytest 4.3.0 py36_0 defaults pytest-arraydiff 0.3 py36h39e3cac_0 defaults pytest-astropy 0.5.0 py36_0 defaults pytest-doctestplus 0.2.0 py36_0 defaults pytest-openfiles 0.3.2 py36_0 defaults pytest-remotedata 0.3.1 py36_0 defaults python 3.6.6 h6e4f718_2 defaults python-dateutil 2.8.0 py36_0 defaults python-libarchive-c 2.8 py36_6 defaults python-slugify 1.2.6 pypi_0 pypi pytz 2018.9 py36_0 defaults pyugend2 0.1.0 pypi_0 pypi pywavelets 1.0.1 py36hdd07704_0 defaults pyyaml 3.13 py36h14c3975_0 defaults pyzmq 17.1.2 py36h14c3975_0 defaults qt 5.9.6 h8703b6f_2 defaults qtawesome 0.5.6 py_0 defaults qtconsole 4.4.3 py36_0 defaults qtpy 1.6.0 py_0 defaults r-abind 1.4_5 mro351hf348343_0 r r-assertthat 0.2.0 mro351hf348343_0 r r-backports 1.1.2 mro351hd10c6a6_0 r r-base64enc 0.1_3 mro351hd10c6a6_0 r r-bh 1.66.0_1 mro351hf348343_0 r r-bindr 0.1.1 mro351hf348343_0 r r-bindrcpp 0.2.2 mro351hebc1506_0 r r-boot 1.3_20 mro351_0 r r-broom 0.5.0 mro351hf348343_0 r r-callr 2.0.4 mro351hf348343_0 r r-caret 6.0_80 mro351hd10c6a6_0 r r-cellranger 1.1.0 mro351hf348343_0 r r-checkpoint 0.4.4 mro351_0 r r-class 7.3_14 mro351hd10c6a6_0 r r-cli 1.0.0 mro351hf348343_0 r r-clipr 0.4.1 mro351hf348343_0 r r-cluster 2.0.7_1 mro351hac1494b_0 r r-codetools 0.2_15 mro351hf348343_0 r r-colorspace 1.3_2 mro351hd10c6a6_0 r r-crayon 1.3.4 mro351hf348343_0 r r-curl 3.2 mro351hd10c6a6_0 r r-cvst 0.2_2 mro351hf348343_0 r r-data.table 1.11.4 mro351hd10c6a6_0 r r-dbi 1.0.0 mro351hf348343_0 r r-dbplyr 1.2.2 mro351hf348343_0 r r-ddalpha 1.3.4 mro351h2efac65_0 r r-deoptimr 1.0_8 mro351hf348343_0 r r-deployrrserve 9.0.0 mro351_0 r r-dichromat 2.0_0 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r r-withr 2.1.2 mro351hf348343_0 r r-xfun 0.3 mro351hf348343_0 r r-xml2 1.2.0 mro351hebc1506_0 r r-xtable 1.8_2 mro351hf348343_0 r r-xts 0.11_0 mro351hd10c6a6_0 r r-yaml 2.2.0 mro351hd10c6a6_0 r r-zoo 1.8_3 mro351hd10c6a6_0 r readline 7.0 h7b6447c_5 defaults requests 2.21.0 py36_0 defaults retrying 1.3.3 pypi_0 pypi rope 0.12.0 py36_0 defaults rsa 3.4.2 pypi_0 pypi ruamel_yaml 0.15.46 py36h14c3975_0 defaults s3transfer 0.2.0 pypi_0 pypi scikit-image 0.14.1 py36he6710b0_0 defaults scikit-learn 0.20.2 py36h22eb022_0 defaults scipy 1.2.1 py36he2b7bc3_0 defaults seaborn 0.9.0 py36_0 defaults secretstorage 3.1.0 py36_0 defaults send2trash 1.5.0 py36_0 defaults service_identity 18.1.0 py36h28b3542_0 defaults setuptools 41.0.1 pypi_0 pypi shapely 1.6.4.post2 pypi_0 pypi simplegeneric 0.8.1 py36_2 defaults singledispatch 3.4.0.3 py36h7a266c3_0 defaults sip 4.19.8 py36hf484d3e_0 defaults six 1.12.0 pypi_0 pypi snappy 1.1.7 hbae5bb6_3 defaults snowballstemmer 1.2.1 py36_0 defaults snuggs 1.4.1 pypi_0 pypi sortedcollections 1.1.2 py36_0 defaults sortedcontainers 2.1.0 py36_0 defaults soupsieve 1.7.1 py36_0 defaults sphinx 1.8.4 py36_0 defaults sphinxcontrib 1.0 py36_1 defaults sphinxcontrib-websupport 1.1.0 py36_1 defaults spyder 3.3.3 py36_0 defaults spyder-kernels 0.4.2 py36_0 defaults sqlalchemy 1.2.18 py36h7b6447c_0 defaults sqlite 3.26.0 h7b6447c_0 defaults statsmodels 0.9.0 py36h035aef0_0 defaults suitesparse 5.2.0 h2ffa06c_0 defaults sympy 1.3 py36_0 defaults tb-nightly 1.14.0a20190301 pypi_0 pypi tbb 2019.1 hfd86e86_0 defaults tblib 1.3.2 py36_0 defaults tensorboard 1.12.2 py36he6710b0_0 defaults tensorflow 1.12.0 gpu_py36he74679b_0 defaults tensorflow-base 1.12.0 gpu_py36had579c0_0 defaults tensorflow-gpu 2.0.0a0 pypi_0 pypi termcolor 1.1.0 pypi_0 pypi terminado 0.8.1 py36_1 defaults terminaltables 3.1.0 pypi_0 pypi testpath 0.4.2 py36_0 defaults tf-estimator-nightly 1.14.0.dev2019030115 pypi_0 pypi tk 8.6.8 hbc83047_0 defaults toolz 0.9.0 py36_0 defaults tornado 5.1.1 py36h7b6447c_0 defaults tqdm 4.31.1 py_0 defaults traitlets 4.3.2 py36_0 defaults twisted 18.9.0 py36h7b6447c_0 defaults typed-ast 1.1.2 pypi_0 pypi typing 3.6.4 py36_0 defaults unicodecsv 0.14.1 py36_0 defaults unidecode 1.0.22 pypi_0 pypi unixodbc 2.3.7 h14c3975_0 defaults urllib3 1.22 pypi_0 pypi wand 0.4.4 pypi_0 pypi wcwidth 0.1.7 py36_0 defaults webencodings 0.5.1 py36_1 defaults werkzeug 0.15.4 pypi_0 pypi wheel 0.33.4 pypi_0 pypi whichcraft 0.5.2 pypi_0 pypi widgetsnbextension 3.4.2 py36_0 defaults wrapt 1.11.1 py36h7b6447c_0 defaults wurlitzer 1.0.2 py36_0 defaults xlrd 1.2.0 py36_0 defaults xlsxwriter 1.1.5 py36_0 defaults xlwt 1.3.0 py36_0 defaults xz 5.2.4 h14c3975_4 defaults yaml 0.1.7 had09818_2 defaults zeromq 4.2.5 hf484d3e_1 defaults zict 0.1.3 py36_0 defaults zlib 1.2.11 h7b6447c_3 defaults zope 1.0 py36_1 defaults zope.interface 4.6.0 py36h7b6447c_0 defaults zstd 1.3.7 h0b5b093_0 defaults ```

[csoja]

It looks like Cudnn and cudatoolkit were both updated recently. Date: Mon Jun 3 2019: cudnn 7.6.0 for cuda 9.0, 10.0, 10.1 & cudatoolkit 10.1.168

Tensorflow 2.0 will not be available from Anaconda while it is tagged as pre-release (alpha/beta). Tensorflow is still listed as being pre-release here: https://github.com/tensorflow/tensorflow/releases

[00krishna]

@csoja thanks for the info. I appreciate your post. Yes, I just happened to do an update on conda environment and saw that the cudnn version went to 7.6.0 and the cudatoolkit version was also upgraded. So that is good. I had found some hacky way around this before, but now that the regular conda environment is updated I can use that.

Was there any kind of announcement about this update? I did not see any tweet or message on the README about this. I mean I posted this issue 10 days ago, so the Anaconda folks must have already been testing the updated cudnn and cudatoolkit versions when that message was posted. I also posted this issue at https://github.com/conda/conda/issues/8736 because I was not sure the appropriate location to post the issue.

I think the only message I received on this issue was that Anaconda does not support unreleased software and Tensorflow-2.0 alpha was not released. I know that you were not personally on that issue chain, but hopefully you can understand my own frustration a bit. I mean, the commentor could have just said that "we are testing updated cudnn and cudatoolkit and it will be released in 5 days."

Don't worry I am not trying to rant or anything. But I think that the Anaconda teams still have really big communications issues with the users. I am sorry to say that, but it really does affect us trying to use Anaconda.

Once again, I appreciate your getting back to me.

[csoja]

@00krishna Are you aware of the RSS feed? https://repo.anaconda.com/pkgs/rss.xml This lists the most recent package updates to repo.anaconda.com This is the current method for announcing package updates. There are too many to tweet about every update. Also, if you want to browse what is available in the repositories, you can do so from here: https://repo.anaconda.com/pkgs/

It is a very small team and they do the best they can to keep up, but with millions of users and many, many public repositories and mailing lists they are responsible for - it is an uphill battle. Thanks for your patience and for using Anaconda.

[00krishna]

@csoja I really appreciate your getting back to me. I did not know about the RSS feed, so I will keep any eye on that in the future. I know that you guys are working hard and it is quite amazing how well the Anaconda environment works considering the number of packages that are integrated into the ecosystem. I remember the challenges of the previous Enthought ecosystem, and then before that trying to install and compile all of the packages myself, haha. So glad that those days are behind us.

Keep up the good work. And definitely anything you can do to help we users to understand the Anaconda plans for the future, or dealing with different challenges, etc., is really helpful. This Tensorflow 2.0 thing was a really great example where Google is pushing everyone to start using Tensorflow 2.0. All of the tutorials and communications are geared towards users migrating early so that they can avoid a last minute scramble when Tensorflow 2.0 is finally an official release. So in parallel, communications from Anaconda/ContinuuumIO are helpful to understand how Anaconda will respond to the challenge posed by TF 2.0.

But I think that this is just an example of upcoming challenges to the ecosystem that are on the horizon. I think Python 2.7 will End-of-Life on Jan 1, 2020. Anaconda has already been communicating about that transition and that has been an example of very proactive communications. I think those communications prompted me to retire some docker containers that were still lingering in my repos, etc.

Thanks again and best of luck.