I'm trying to use HSL MA97 for IPOPT on Google colab.
I succeeded to run IPOPT (and cyipopt) without HSL linear solver, but failed to run with HSL, for example ma97.
Thank you for your help.
The setting is as follows.
install IPOPT using
!apt install coinor-libipopt1v5 coinor-libipopt-dev
install cyipopt using
!pip install -q cyipopt
clone ThirdParty-HSL
!git clone https://github.com/coin-or-tools/ThirdParty-HSL.git
copy hsl to thirdParty-HSL and install
!cp -R /content/drive/MyDrive/solver/coinhsl/ /content/ThirdParty-HSL/
%cd /content/ThirdParty-HSL/
!./configure
!make
!make install
IPOPT works without HSL, but doesn't work with HSL. I want to find how to make it correct to IPOPT work with HSL MA97.
The following is the Colab notebook that I made.
https://colab.research.google.com/drive/1gFsHMlFUp6eVGEdf3W_t4DHZKhiE7xpx#scrollTo=-N_5KP7kIs8U
The hsllib option is available since Ipopt 3.14 only. So since you use an very old Ipopt version (3.11.9 is from 2014), you cannot use this option. But Ipopt can still try to load a HSL lib at runtime (if that hasn't been disabled in the Ipopt build). You just need to make sure that a libhsl.so can be found, e.g., by setting LD_LIBRARY_PATH. (You need to rename libcoinhsl.so to libhsl.so.)
Related
I want to use Google Colab in a research project using Kaldi ASR. Is it possible to install it? and Where Can I find Kaldi files after installation?
Here's a notebook demonstrating the install steps for a managed backend:
https://colab.research.google.com/drive/1rp2eZRHW9OYnA1WpRGeblG6fDSyyH-my
The install takes a while. You might want to do this once on your machine and use Colab's local runtimes support.
I have made it into my kora library.
Now you can install kaldi and pykaldi with just 2 lines of code.
!pip install kora -q
import kora.install.kaldi
I am trying to compile Tensorflow (tried both: full & lite) on Odroid XU4 (16GB eMMc, Ubuntu 16) but I am getting errors shown in figures: https://www.dropbox.com/sh/j86ysncze1q0eka/AAB8RZtUTkaytqfEGivbev_Ga?dl=0
I am using FlytOS as OS(http://docs.flytbase.com/docs/FlytOS/GettingStarted/OdroidGuide.html). Its customized Ubuntu 16 with OpenCV and ROS setup, makes 11GB after installation. So, I got only 2.4GB free. Therefore, I added 16GB USB as swap memory.
I have installed Bazel without using swap memory. Tried tensorflow full version and lite but failed to compile. However, I downloaded compiled tensorflow lite for Pi and successfully installed on Odroid. Since, Odroid is Octacore, therefore, to make best use of available processing power I need to compile tensorflow on Odroid.
Please let me know if any one has tensorflow compiled on Odroid XU4.
Regards,
Check this guide out. Build Tensorflow on Odroid
IT gives a detailed step by step guide and also has some troubleshooting procedures.
Summarizing the steps here:
Install prerequisites including g++, gcc-4.8, python-pip, python-dev, numpy and Oracle Java (not OpenJDK)
Use a USB/ Flash drive and add some swap memory
Build Bazel. In the compile.sh shell script, modify the run line to add memory flags
run “${JAVAC}” -J-Xms256m -J-Xmx384m -classpath “${classpath}” -sourcepath “${sourcepath}”
Get Tensorflow v1.4 specifically and run ./configure and select relevant options. Disable XLA as it's causing some problems.
Finally run Bazel command.
bazel build -c opt --copt="-funsafe-math-optimizations" --copt="-ftree-vectorize" --copt="-fomit-frame-pointer" --local_resources 8192,8.0,1.0 --verbose_failures tensorflow/tools/pip_package:build_pip_package
Now install it.
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
sudo pip2 install /tmp/tensorflow_pkg/tensorflow-1.4.0-cp27-cp27mu-linux_armv7l.whl --upgrade --ignore-installed
Test the install
python
import tensorflow
print(tensorflow.__version__)
1.4.0
I was able to compile it successfully by following the steps given there.
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
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.