I am trying to install tensorflow-gpu 1.15 using Conda for an easy install of CUDA and cuDNN. The problem is that checking the compatibility chart of the official web I need python 3.6, CUDA 10.0 and cuDNN 7.4.
Searching the Conda rep via conda search cudnn it says that there isn't cuDNN 7.4. Is there any other way to install the required packages? Or maybe tensorflow 1.15 also works with other combinations of versions?
As a side note, python 3.6, tensorflow-gpu 1.15 and CUDA 10 install correctly, but it seems I can't use the GPU correctly without cuDNN. I just recently started using Conda, so maybe there is a straight forward way to do this that I don't realize. My Conda version is 4.9.1 (miniconda version).
---update---
Just in case I add the error while trying conda create -n myenv -c conda-forge tensorflow-gpu=1.15:
Collecting package metadata (current_repodata.json): done
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: -
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
failed
UnsatisfiableError: The following specifications were found to be incompatible with each other:
Output in format: Requested package -> Available versions
Package _tflow_select conflicts for:
_tflow_select==2.1.0=gpu
tensorflow==1.15.0 -> _tflow_select[version='2.1.0|2.3.0|2.2.0',build='gpu|mkl|eigen']
Note that strict channel priority may have removed packages required for satisfiability.