I installed TensorFlow on my MacBook Pro 10.12.5 from source code by steps described here.
https://www.tensorflow.org/install/install_sources
TensorFlow itself works well but I cannot run TensorBoard.
It seems tensorboard is not installed properly.
When I try running tensorboard --logdir=... it says -bash: tensorboard: command not found. And locate tensorboard returns empty.
Do I need any additional step to install tensorboard?
You could call tensorboard as a python module like this:
python3 -m tensorboard.main --logdir=~/my/training/dir
or add this to your .profile
alias tensorboard='python3 -m tensorboard.main'
If no other methods work then try this one. It may help you.
1. check the location of Tensorflow
pip show tensorflow
It will show output something like this.
...
Name: tensorflow
Version: 1.4.0
Location: /home/abc/xy/.local/lib/python2.7/site-packages
...
2. Go to that location you get from the above output.
cd /home/abc/xy/.local/lib/python2.7/site-packages
There you can see a directory named tensorboard.
cd tensorboard
3. There must be a file named 'main.py'.
4. Execute the following command to launch the tensorboard.
python main.py --logdir=/path/to/log_file/
If you installed Tensorflow with Virtualenv, then first Check whether you have activated the tensorflow envirnoment or not
If you have activated the tensorflow session then your command prompt will look like this :
If not, Write the below command and try running tensorboard again.
source ~/tensorflow/bin/activate
Run this command:
python3 -m tensorboard.main --logdir=logdir
To run directory you can use,
Change =logdir to ="dir/TensorFlow"
(Directory path)
What version of Tensorflow are you running? Older versions don't include Tensorboard.
If you do have a newer version, I see you are using OSX, which apparently caused some problems for other people: https://github.com/tensorflow/tensorflow/issues/2115 Check this page to fix it!
As a MacPorts user, I'm used to running things from out of the path
/opt/local/bin. When you install a python package via MacPorts, that's
where the executables go --- even if they're just symbolic links to
files to a main python repository in
/opt/local/Library/Frameworks/Python.framework/Versions/2.7/bin/
pip installs things into the latter directory, but apparently does NOT
add the symbolic link to /opt/local/bin
This has never been an issue (or even come up) for me before, because
I've only used pip to install (non-executable) packages which load
from within python. In conclusion, there is a
/opt/local/Library/Frameworks/Python.framework/Versions/2.7/bin/tensorboard
This is a pip / MacPorts-SOP mismatch / user error*, and nothing to do
with tensorboard in particular. Please close this issue. Thanks for
your help.
*my 'locate' database was in the process of updating but hadn't completed
Quickest solution -
echo "alias tensorboard='python3 -m tensorboard.main'" >> ~/.bash_profile
After adding this to your .bash_profile you can use
tensorboard --logdir=/path
If you are using pycharm in windows environment this may help:
python -m tensorboard.main --logdir=logs
Related
I have been trying to install tensorflow via Conda for a couple days now with no luck.
I made a fresh install of anaconda3/miniconda3 followed the steps to fix the .bash_profile issue. Then
$ conda create -n tensorflow pip python=3.6
seems to work. However
$ source activate tensorflow
does nothing. I tried conda activate tensorflow and nothing. If I type conda info I can see that the tensorflow env is running. But I have no ability to type within it?
Welcome to Python and Tensorflow.
This bit really takes a long time to figure out unless somebody told you how to do so.
Follow this. Assume you installed Miniconda (then python is automatically installed) and you are using linux (cuz you mentioned 'source')
You want to make an conda environment named 'ai3' and you wanna install many packages like tensorflow within 'ai3' env.
In your command line,
1) Create ai3 env: see https://conda.io/docs/user-guide/tasks/manage-environments.html for details
$ conda create -n ai3 python=3.6
2) Log your current command window into the ai3 env
$ source activate ai3
3) Install packages, for example tensorflow: details in https://www.tensorflow.org/install/install_linux but that does not really help FOBs
$ pip install tensorflow
4) Enter yes whenever your command window asks sth. Once it's done, then you wish to use tensorflow (TF) in python. Do this
$ python
$ >> import tensorflow as tf
$ >> hello = tf.constant('Hello, TensorFlow!')
$ >> with tf.Session() as sess:
$ >> sess.run(hello)
4-1-0) Obviously you don't wanna do this all the time. Download Pycharm community edition (in https://www.jetbrains.com/pycharm/download/#section=linux) and install.
4-1-1) Create a new project in any location you like with interpreter 'ai3'. Interpreter is the env you just prepared in step 1,2,3): click 'add local' by clicking a button at the right end of the 'Interpreter' line -> a python file at '/miniconda3/envs/ai3/bin/python'
5) Now work with many tutorials out there on this setup
First you need to check the naming convention you are using. I know that's how documentation suggests, but I think it's misleading.
Name your environment according to what you want to be doing inside of it. Tensorflow is a package (that can be a python package) that you will use inside of the environment so you can name it something like:
$ conda create --name 'machinelearning-env' pip python=3.6
Also if you just installed Anaconda you do not need to specify the python designation.
Then you need to activate your environment with
source activate (whatever you named your conda env)
Next you can install with :
:~/anaconda3/envs$ pip install --ignore-installed --upgrade (the tensorflow url found here: https://www.tensorflow.org/install/install_linux#the_url_of_the_tensorflow_python_package )
Finally instantiate python and then you can import tensorflow with :
import tensorflow as tf
I suggest you refer back to the tensorflow documentation as it's all there. Good luck!
You should first give a name to your environment then give package names that you want to install ie.
conda create -n tensorflow_env tensorflow
Easiest way for me at least.
I'm trying to install TensorFlow Object Detection on my PC which is Windows10, after finished all the installation steps, I tied to run tutorial program, but I told me there is a import problem
ImportError: cannot import name 'string_int_label_map_pb2'
I have run the
protoc object_detection/protos/*.proto --python_out=.
My python is 3.6.2, protoc version is 3.4.0
Well, I have run the command in CMD without "python" at front, after I add python it works
You need to set the PYTHONPATH variables and point them to the object_detection folder. You can run the below command:
set PYTHONPATH=path\to\object_detection\models;path\to\object_detection\models\research;path\to\object_detection\models\research\slim;path\to\object_detection\models\research\object_detection
replace the "path\to\" with your actual path. After you have done the path setting, restart the jupyter notebook and try runnning again. You should not see the error. Hope it helps.
I used the spyder or terminal to run the mnist_deep.py program , it can run normally, but when i run the program using pycharm, it will cause an error.The Project Interpreter is 2.7.12(~/anaconda2/bin/python).
Error Type:
ImportError:libcudart.so.8.0:cannot open shared object file:No such file or directory
Error importing tensorflow.Unless you are using bazel,you should not try to import tensorflow from its source directory;please exit the tensorflow source tree,and relaunch your python interpreter from there
It's preferable to do a system-wide configuration instead of editing ~/.bashrc. Create a .conf file in /etc/ld.so.conf.d/:
sudo nano /etc/ld.so.conf.d/nvidia.conf
Add this:
/usr/local/cuda-8.0/lib64
/usr/local/cuda-8.0/lib # you probably don't need this line; check
# if the directory exists
Then run sudo ldconfig. Hope this brings you joy.
In my case, I had installed tensorflow-gpu on a machine without a GPU.
Uninstalling it fixed the problem
pip uninstall tensorflow-gpu
pip install tensorflow --ignore-installed
Without the 2nd step, I was getting an error No module named tensorflow (ref)
I've been trying to install tensorflow with GPU support using these steps:
http://www.nvidia.com/object/gpu-accelerated-applications-tensorflow-installation.html
and also using:
http://thelazylog.com/install-tensorflow-with-gpu-support-on-sandbox-redhat/
This is the error message that I'm getting when I try to run the bazel build command for building the tensorflow pip package (with the --config-cuda flag set):
The specified --crosstool_top '//third_party/gpus/crosstool:crosstool' is not a valid cc_toolchain_suite rule.
What's strange is that if i remove the --config=cuda flag, I don't get the error message while building and I'm able to install tensorflow successfully - but without GPU support.
I experienced the same issue, using the nvidia instructions. What I did was to drop the git reset line in the instructions, and it works.
Details (from the error message):
Close, reopen terminal
Run git clone (again), and cd tensorflow
Run ./configure
Bazel build, etc
This may be unrelated, but I experienced an issue with the .whl line, the error message was that the wheel cannot be found or something along those lines. This is the "And finally install the TensorFlow pip package" section. To resolve it in my case, I typed in the terminal all the way to "..._pkg/tensorflow", and then pressed tab for auto-completion. The file name that popped up was significantly longer than that in the guide, but it worked. Also, if anyone face a numpy not installed message based on the nvidia instructions, replace the python-pip and dev with python-numpy and run that line again to install.
Configuration: Fresh Ubuntu 16.04, GTX970M, running driver 367.48 (from CUDA installation), CUDA 8.0, CuDNN 5.1
Full setup path:
Fresh Ubuntu, with downloads and 3rd party apps selected during installation.
Control panel => Software and updates => Other Software => Canonical ticked
Install CUDA using nvidia instructions in CUDA documentation, .deb format
CuDNN 5.1 installed, the rest from the nvidia link.
I hope everything works out for you!
(I'm sorry for the poor formatting)
I was going through same problem and recently found the solution. The problem is with the installation of Bazel which leads to this kind of error.
After installation of bazel from installer, make sure that you would give the correct path to ~./bashrc and also activate the path using
source "path-to-your-bin-directory-for-bazel"
Please change the git source version slightly as shown below
$ git clone https://github.com/tensorflow/tensorflow
$ cd tensorflow
// $ git reset --hard 70de76e
$ git reset --hard 287db3a
And please refer the below l
https://github.com/tensorflow/tensorflow/issues/4944
Also, zlib has been updated since this TF build. You need to check http://www.zlib.net/ to get the latest version and SHA-256, then update tensorflow/workspace.bzl with that information (lines 254-266 in this build). At this time, the correct version info would include the following:
url = "http://zlib.net/zlib-1.2.11.tar.gz",
sha256 = "c3e5e9fdd5004dcb542feda5ee4f0ff0744628baf8ed2dd5d66f8ca1197cb1a1",
strip_prefix = "zlib-1.2.11",
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.