I want to build tensorflow with python libraries. Currently I have tensorflow installed but I do not see python packages in /usr/local/lib/python3.6/dist-packages so when I try to import tensorflow module in python terminal, it fails. However, there is library in /usr/lib and C++ programs work.
What is flag/target needed in bazel build?
You can get TensorFlow in python package by:
Directly doing pip install tensorflow: It will install the precompiled version by directly downloading a wheel file.
Build from source code in GitHub using bazel build.
For the second approach, the following steps are needed:
Take the source code from GitHub.
Compile the code using bazel build. It will give the ".whl" file.
Do pip install /tmp/TensorFlow-version-tags.whl
For detailed installation, steps follow this.
I need to save my new sequential model but when I use the model.save(filename),it shows error like save_model requires hp5y.I tried installing h5py in conda by 'conda install -c anaconda h5py'command. And I also installed cython,but then the error exists .what should I do?
one should include the package in pycharm project interpreter after being downloaded in the conda environment.
I'm trying to follow this guide to test this new algorithm: https://github.com/lalonderodney/SegCaps
I can't do it in my PC, so i'm using another server with Putty. Now I'm connected with the other server.
First of all I installed TensorFlow as indicates in the guide with :
pip install -r requirements.txt
After I wrote this code: ./main.py segcaps.png
in which segcaps.png is the image that i want to use
Finally I wrote python main.py --data_root_dir data
that is the only required parameter with the directory containing imgs and masks folders.
Now it gives me an error:
ModuleNotFoundError: No module named 'tensorflow.python.framework'
I searched it in the directory tensorflow/python/framework and it exists.
So, i don't know how to solve it. Ideas?
If you have multiple Python versions installed, then you'll (most likely) have multiple pip versions installed too. Make sure that the pip command you use installs the package(s) into the Python version you want it to. It may so happen that the package got installed into python2 but you wanted it in python3.
Since using pip did not install the packages in python3, pip3 is most likely to the PyPI for python3. Try
pip3 install -r requirements.txt
and that should work.
In case you have an EnvironmentError you can try this (bad idea):
pip3 install -r requirements.txt --user
This solves the problem most of the times on standalone machines. I'm not sure about the server; insufficient permissions might block this.
Why is the --user flag a bad idea? Read: What is the purpose “pip install --user …”?
You can use pip show tensorflow to see if it is installed or not.
As for ModuleNotFoundError try uninstalling keras and reinstalling an earlier version by pip install keras==2.1.6
The github source for tensorflow contains a folder called inception under models.
https://github.com/tensorflow/models/tree/master/inception/inception
However, there is no such folder when I install using pip
The pip installation resides at:
/usr/lib/python2.7/site-packages/tensorflow/
Is this discrepancy because of the version I am using when installing with with pip? I used this link TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.9.0rc0-cp27-none-linux_x86_64.whl
when installing using pip. Is this correct?
Pleasec check
How do I install TensorFlow's tensorboard?
The steps to install Tensorflow are here: https://www.tensorflow.org/install/
For example, on Linux for CPU-only (no GPU), you would type this command:
pip install -U pip
pip install tensorflow
Since TensorFlow depends on TensorBoard, running the following command should not be necessary:
pip install tensorboard
Try typing which tensorboard in your terminal. It should exist if you installed with pip as mentioned in the tensorboard README (although the documentation doesn't tell you that you can now launch tensorboard without doing anything else).
You need to give it a log directory. If you are in the directory where you saved your graph, you can launch it from your terminal with something like:
tensorboard --logdir .
or more generally:
tensorboard --logdir /path/to/log/directory
for any log directory.
Then open your favorite web browser and type in localhost:6006 to connect.
That should get you started. As for logging anything useful in your training process, you need to use the TensorFlow Summary API. You can also use the TensorBoard callback in Keras.
If your Tensorflow install is located here:
/usr/local/lib/python2.7/dist-packages/tensorflow
then the python command to launch Tensorboard is:
$ python /usr/local/lib/python2.7/dist-packages/tensorflow/tensorboard/tensorboard.py --logdir=/home/user/Documents/.../logdir
The installation from pip allows you to use:
$ tensorboard --logdir=/home/user/Documents/.../logdir
It may be helpful to make an alias for it.
Install and find your tensorboard location:
pip install tensorboard
pip show tensorboard
Add the following alias in .bashrc:
alias tensorboard='python pathShownByPip/tensorboard/main.py'
Open another terminal or run exec bash.
For Windows users, cd into pathShownByPip\tensorboard and run python main.py from there.
For Python 3.x, use pip3 instead of pip, and don't forget to use python3 in the alias.
TensorBoard isn't a separate component. TensorBoard comes packaged with TensorFlow.
Adding this just for the sake of completeness of this question (some questions may get closed as duplicate of this one).
I usually use user mode for pip ie. pip install --user even if instructions assume root mode. That way, my tensorboard installation was in ~/.local/bin/tensorboard, and it was not in my path (which shouldn't be ideal either). So I was not able to access it.
In this case, running
sudo ln -s ~/.local/bin/tensorboard /usr/bin
should fix it.
pip install tensorflow.tensorboard # install tensorboard
pip show tensorflow.tensorboard
# Location: c:\users\<name>\appdata\roaming\python\python35\site-packages
# now just run tensorboard as:
python c:\users\<name>\appdata\roaming\python\python35\site-packages\tensorboard\main.py --logdir=<logidr>
If you're using the anaconda distribution of Python, then simply do:
$❯ conda install -c conda-forge tensorboard
or
$❯ conda install -c anaconda tensorboard
Also, you can have a look at various builds by search the packages repo by:
$❯ anaconda search -t conda tensorboard
which would list the channels and the corresponding builds, the supported OS, Python versions etc.,
The pip package you are looking for is tensorflow-tensorboard developed by Google.
If you installed TensorFlow using pip, then the location of TensorBoard can be retrieved by issuing the command which tensorboard on the terminal. You can then edit the TensorBoard file, if necessary.
It is better not to mix up the virtual environments or perform installation on the root directory. Steps I took for hassle free installation are as below. I used conda for installing all my dependencies instead of pip. I'm answering with extra details, because when I tried to install tensor board and tensor flow on my root env, it messed up.
Create a virtual env
conda create --name my_env python=3.6
Activate virtual environment
source activate my_env
Install basic required modules
conda install pandas
conda install tensorflow
Install tensor board
conda install -c condo-forge tensor board
Hope that helps
I have a local install of tensorflow 1.15.0 (with tensorboard obviously included) on MacOS.
For me, the path to the relevant file within my user directory is Library/Python/3.7/lib/python/site-packages/tensorboard/main.py. So, which does not work for me, but you have to look for the file named main.py, which is weird since it apparently is named something else for other users.