I wrote python image recognition system based on tensorflow, but can't install tensorflow on hosting. My hosting is mydevil.net. Tried using pip install tensorflow but it didn't work. I would like to add that the hosting works on a FreeBSD system.
TensowFlow is a complex piece of software that isn't easy to port/package. At the moment there is a package for TensorFlow v1 only: https://www.freshports.org/science/py-tensorflow/
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.
How come we need to install tensorflow as a separate environment?
If we do it this way, many common libraries are not available when tensorflow is activated.
Most of the common libraries such as matplotlib, panda, etc. are not within tensorflow environment. So we have to install again to use them.
So why not just install under root so we don't have to re-install all those libraries under the new environment?
Thanks.
So I started to build tensorflow in Mac and the thing is that it doesn't seem possible to build tensorflow in Mac OS platform.
After following instructions in here, I get this package directory.
It seems like the build settings for bazel is only for linux distro. The reason why I thought so is because there is a .so file in package directory that is needed to be linked after importing tensorflow using python binary.
This is the result I get after importing tensorflow using python.
Is there any other way I can build tensorflow on Mac OS?
It seems like there are no options but to install tensorflow with pip. So I just created a new virtual machine and installed ubuntu 16.04 to use it as my docker host. By doing so, I can create a new docker container which can now link and execute the linux library.
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 have installed TensorFlow using Anaconda Installation.
During the installation, after sourcing into the 'tensorflow' environment (create by conda), I used pip in my anaconda(i.e. $HOME/anaconda/bin/pip3) instead of pip or pip3 in the tensorflow environment(i.e. $HOME/anaconda/envs/tensorflow/bin/pip) to install TensorFlow.
When I test my installation, I find that I can still import tensorflow even if I am not in the 'tensorflow' environment(after source deactivate). So I think I am actually using tensorflow without an isolated python environment. Does it harm?
If it works well for you, that's good, but in general this isn't an approach we test extensively or support, so your mileage may vary!