I want to run TensorFlow on my microserver. I'd like to install a non-systemd Linux if possible e.g. Alpine, but I am new to TensorFlow and I am not sure how much it relies on systemd or if it would run without it. Would it?
TensorFlow is a regular programming library, it's not a system library and not running as a service, thus it isn't dependent on systemd.
I've tested TensorFlow on Windows 10 Subsystem for Linux (WSL) which doesn't come with systemd and it's still working.
Related
I am trying to install "TensorFlow-Probability" for windows offline without going through internet so that I can avoid network firewall issue, but I could not find any instruction about how to. Any suggestion?
TensorFlow-Probability is pure python, there is no need for a windows build of it.
You should be able to download the file from: https://pypi.org/project/tensorflow-probability/#files
and pip install it in a conda or python environment.
I'm want to run tensorflow on a very standard machine setup (windows 64 bit) and have read that tensorflow has greater performance if built from source as it is optimised for your system. When installing tensorflow via pip for why does pip not select the optimal build for your system?
Also if you did install via pip is there a way or being able to tell whether the optimal build has been installed, or is the only way of knowing that simply remembering how you installed it?
Google has taken the position, that it is not reasonable to build TF for every possible instruction set out there. They only release generic builds for Linux, Mac and Windows. You must build from source if you want all the optimizations for your particular machine's instruction set.
I'm running a Windows computer with just a CPU (no GPU). When I run pip install tensorflow -vvv in order to see what pip is doing, it lists a lot of links, but for all of them, it says "Skipping link ... it is not compatible with this Python."
Does tensorflow support Python 3.6.4 on Windows? If so, what binary URL should I use to install it?
(I previously installed with this version due to reading this, but ran into this error without the DLL load failed message, so I'm wondering if there's a better version I should use.)
Also, I'm aware that Tensorflow says they support Python 3.x, but right now it hasn't been working for me.
You have probably installed Python 32bits, you need the 64bits version
Upon trying to install Tensorflow for conda environment, I encountered with the following error message, without any progress:
tensorflow-1.1.0-cp35-cp35mwin_amd64.whl is not a supported wheel on this platform
Have you tried uninstalling and re-installing TensorFlow using pip within your Conda environment? I.e.:
pip uninstall tensorflow
Followed by:
pip install tensorflow
If it doesn't work, the issue may be with your Python installation. TensorFlow only supports 64-bit Python 3.5+ on Windows (see more info here).
Perhaps you have Python's default installation, which comes in a 32-bit version. If that's the case, you can download the 64-bit Python 3.5 or later from here to run in your Conda environment and then you should be able to install/run TensorFlow without any issues.
Make sure that the Python version installed in the Environment is 3.5 not 3.6. Since 3.6 was released Conda automatically sets that version as default for python 3. However, it is still not supported by Tensorflow.
You can work using tensorflow library along with other essential libraries using the Dockerfile. Using Docker for environment are a good way to run experiments in reproducible manner as in this blog
You can also try using datmo in order setup environment and track machine learning projects for making it reproducible using datmo CLI tool.
I am looking into using Tensorflow for my research soon, and looked at the online documentation for installing with Conda https://www.tensorflow.org/versions/r0.11/get_started/os_setup.html#anaconda-installation.
It suggested creating a new environment, and installing Tensorflow in it, and the installing other python packages afterwards.
But I already have an existing environment with lots of packages I need, and I'm wondering if its safe to add Tensorflow into that environment?
Also, I have a question about how this installation with conda works. I know that Conda will create a distinct set of folders containing the libraries needed for each environment, but if I install Tensorflow, what happens to all the base low level C++ and CUDA libraries that get compiled? Do they reside in my Conda environment's folder, or are they in some system wide libraries closer to my root?
PS: I'm using Ubuntu 16.04, and have a GPU that I want to run Tensorflow on.
Thank you.
But I already have an existing environment with lots of packages I need, and I'm wondering if its safe to add Tensorflow into that environment?
conda has this awesome feature called "revisions". You can show your current environment with
conda list --revisions
which allows you to revert changes to your conda environment. This allows you to install new packages with confidence that if something breaks you can always revert it later. See this page for more info: https://www.continuum.io/blog/developer/advanced-features-conda-part-2. tl;dr: conda install --revisions <revision_number>
what happens to all the base low level C++ and CUDA libraries that get compiled
Are you talking about the libraries that get compiled when you are trying to run your code? Or the C++/CUDA libraries? If you're talking about the C++/CUDA libs then conda is not compiling them, but merely installing a pre-compiled binary into a specific location that gets picked up. If you're talking about your code, then where exactly those files live would seem to depend on where you put them.