I am trying to setup CUDA enabled Python & TensorFlow environment on OSx 10.11.6
Everything went quite smoothly. First I installed following:
CUDA - 7.5
cuDNN - 5.1
I ensured that the LD_LIBRARY_PATH and CUDA_HOME are set properly by adding following into my ~/.bash_profile file:
export CUDA_HOME=/usr/local/cuda
export DYLD_LIBRARY_PATH="$CUDA_HOME/lib:$DYLD_LIBRARY_PATH"
export LD_LIBRARY_PATH="$CUDA_HOME/lib:$LD_LIBRARY_PATH"
export PATH="$CUDA_HOME/bin:$PATH"
Then I used Brew to install following:
python - 2.7.12_2
bazel - 0.3.2
protobuf - 3.1.0
Then I used Pip to install CPU only TensorFlow from:
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.11.0rc0-py2-none-any.whl
I checked out the Magenta project from: https://github.com/tensorflow/magenta
and run all the test using:
bazel test //magenta/...
And all of them have passed.
So far so good. So I decided to give the GPU enabled version of TensorFlow a shot and installed it from:
https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow-0.11.0rc0-py2-none-any.whl
Now all the tests fail with the following error:
import tensorflow as tf
File "/usr/local/lib/python2.7/site-packages/tensorflow/__init__.py", line 23, in <module>
from tensorflow.python import *
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/__init__.py", line 49, in <module>
from tensorflow.python import pywrap_tensorflow
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 28, in <module>
_pywrap_tensorflow = swig_import_helper()
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow', fp, pathname, description)
ImportError: dlopen(/usr/local/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow.so, 10): Library not loaded: #rpath/libcudart.7.5.dylib
Referenced from: /usr/local/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow.so
Reason: image not found
So obviously the script run from Bazel has trouble locating the libcudart.7.5.dylib library.
I did try running GPU computations from Python without Bazel and everything seems to be fine.
I also did create a test script and run it using Bazel and it seems that the directory containing libcudart.7.5.dylib library is reachable, however the LD_LIBRARY_PATH is not set.
I searched the documentation and found --action_env and --test_env flags, but none of them actually seems to set the LD_LIBRARY_PATH for the execution.
These are the options from loaded from .bazelrc files.
Inherited 'common' options: --isatty=1 --terminal_columns=80
Inherited 'build' options: --define=allow_oversize_protos=true --copt -funsigned-char -c opt --spawn_strategy=standalone
'run' options: --spawn_strategy=standalone
What is the correct way to let Bazel know about the runtime dependencies?
UPDATE
The trouble seems to be caused by the fact that "env" command is part of the execution chain and it does seem to clear both LD_LIBRARY_PATH and DYLD_LIBRARY_PATH environmental variables. Is there a workaround different than disabling the SIP?
It looks like SIP affects the behavior of how the DYLD_LIBRARY_PATH gets propagated to the child processes. I found a similar problem and another similar problem.
I didn't want to turn the SIP off, so I just created symlinks for the CUDA library into a standard location.
ln -s /usr/local/cuda/lib/* /usr/local/lib
Not sure if this is the best solution, but it does work and it does not require the SIP to be disabled.
Use
export LD_LIBRARY_PATH=/usr/local/cuda/lib64/
before launching bazel. Double check in the directory above if there is such a file.
ls /usr/local/cuda/lib64/libcudart.7.5.dylib
Note that in Macosx the name is different:
export DYLD_LIBRARY_PATH=/usr/local/cuda/lib/
See this answer for more information on SuperUser
The problem is indeed SIP, and the solution is to pass --action_env DYLD_LIBRARY_PATH=$CUDA_HOME/lib to the bazel command, e.g.:
bazel build -c opt --config=cuda --action_env DYLD_LIBRARY_PATH=$CUDA_HOME/lib //tensorflow/tools/pip_package:build_pip_package
Related
I am attempting to build tensorflow from source with MKL optimizations on an Intel CPU setup. I have followed the official instructions here up until the command bazel build --config=mkl --config=opt //tensorflow/tools/pip_package:build_pip_package.
Unfortunately, the compilation runs for some period of time and then fails. I'd appreciate any help with this matter.
Updated Output log (using bazel --verbose_failures):
ERROR: /home/jok/build/tensorflow/tensorflow/BUILD:584:1: Executing genrule //tensorflow:tensorflow_python_api_gen failed (Exit 1): bash failed: error executing command
(cd /home/jok/.cache/bazel/_bazel_jok120/737f8d6dbadde71050b1e0783c31ea62/execroot/org_tensorflow && \
exec env - \
LD_LIBRARY_PATH=LD_LIBRARY_PATH:/usr/local/cuda-9.0/lib64/:/usr/local/cuda-9.0/extras/CUPTI/lib64 \
PATH=/home/jok/.conda/envs/tf_mkl/bin:/home/jok/bin:/opt/anaconda3/bin:/usr/local/bin:/bin:/usr/bin:/snap/bin:/home/jok/bin \
/bin/bash -c 'source external/bazel_tools/tools/genrule/genrule-setup.sh; bazel-out/host/bin/tensorflow/create_tensorflow.python_api --root_init_template=tensorflow/api_template.__init__.py --apidir=bazel-out/host/genfiles/tensorflow --apiname=tensorflow --apiversion=1 --package=tensorflow.python --output_package=tensorflow bazel-out/host/genfiles/tensorflow/__init__.py bazel-out/host/genfiles/tensorflow/app/__init__.py bazel-out/host/genfiles/tensorflow/bitwise/__init__.py bazel-out/host/genfiles/tensorflow/compat/__init__.py bazel-out/host/genfiles/tensorflow/data/__init__.py bazel-out/host/genfiles/tensorflow/debugging/__init__.py bazel-out/host/genfiles/tensorflow/distributions/__init__.py bazel-out/host/genfiles/tensorflow/dtypes/__init__.py bazel-out/host/genfiles/tensorflow/errors/__init__.py bazel-out/host/genfiles/tensorflow/feature_column/__init__.py bazel-out/host/genfiles/tensorflow/gfile/__init__.py bazel-out/host/genfiles/tensorflow/graph_util/__init__.py bazel-out/host/genfiles/tensorflow/image/__init__.py bazel-out/host/genfiles/tensorflow/io/__init__.py bazel-out/host/genfiles/tensorflow/initializers/__init__.py bazel-out/host/genfiles/tensorflow/keras/__init__.py bazel-out/host/genfiles/tensorflow/keras/activations/__init__.py bazel-out/host/genfiles/tensorflow/keras/applications/__init__.py bazel-out/host/genfiles/tensorflow/keras/applications/densenet/__init__.py bazel-out/host/genfiles/tensorflow/keras/applications/inception_resnet_v2/__init__.py bazel-out/host/genfiles/tensorflow/keras/applications/inception_v3/__init__.py bazel-out/host/genfiles/tensorflow/keras/applications/mobilenet/__init__.py bazel-out/host/genfiles/tensorflow/keras/applications/mobilenet_v2/__init__.py bazel-out/host/genfiles/tensorflow/keras/applications/nasnet/__init__.py bazel-out/host/genfiles/tensorflow/keras/applications/resnet50/__init__.py bazel-out/host/genfiles/tensorflow/keras/applications/vgg16/__init__.py bazel-out/host/genfiles/tensorflow/keras/applications/vgg19/__init__.py bazel-out/host/genfiles/tensorflow/keras/applications/xception/__init__.py bazel-out/host/genfiles/tensorflow/keras/backend/__init__.py bazel-out/host/genfiles/tensorflow/keras/callbacks/__init__.py bazel-out/host/genfiles/tensorflow/keras/constraints/__init__.py bazel-out/host/genfiles/tensorflow/keras/datasets/__init__.py bazel-out/host/genfiles/tensorflow/keras/datasets/boston_housing/__init__.py bazel-out/host/genfiles/tensorflow/keras/datasets/cifar10/__init__.py bazel-out/host/genfiles/tensorflow/keras/datasets/cifar100/__init__.py bazel-out/host/genfiles/tensorflow/keras/datasets/fashion_mnist/__init__.py bazel-out/host/genfiles/tensorflow/keras/datasets/imdb/__init__.py bazel-out/host/genfiles/tensorflow/keras/datasets/mnist/__init__.py bazel-out/host/genfiles/tensorflow/keras/datasets/reuters/__init__.py bazel-out/host/genfiles/tensorflow/keras/estimator/__init__.py bazel-out/host/genfiles/tensorflow/keras/initializers/__init__.py bazel-out/host/genfiles/tensorflow/keras/layers/__init__.py bazel-out/host/genfiles/tensorflow/keras/losses/__init__.py bazel-out/host/genfiles/tensorflow/keras/metrics/__init__.py bazel-out/host/genfiles/tensorflow/keras/models/__init__.py bazel-out/host/genfiles/tensorflow/keras/optimizers/__init__.py bazel-out/host/genfiles/tensorflow/keras/preprocessing/__init__.py bazel-out/host/genfiles/tensorflow/keras/preprocessing/image/__init__.py bazel-out/host/genfiles/tensorflow/keras/preprocessing/sequence/__init__.py bazel-out/host/genfiles/tensorflow/keras/preprocessing/text/__init__.py bazel-out/host/genfiles/tensorflow/keras/regularizers/__init__.py bazel-out/host/genfiles/tensorflow/keras/utils/__init__.py bazel-out/host/genfiles/tensorflow/keras/wrappers/__init__.py bazel-out/host/genfiles/tensorflow/keras/wrappers/scikit_learn/__init__.py bazel-out/host/genfiles/tensorflow/layers/__init__.py bazel-out/host/genfiles/tensorflow/linalg/__init__.py bazel-out/host/genfiles/tensorflow/logging/__init__.py bazel-out/host/genfiles/tensorflow/losses/__init__.py bazel-out/host/genfiles/tensorflow/manip/__init__.py bazel-out/host/genfiles/tensorflow/math/__init__.py bazel-out/host/genfiles/tensorflow/metrics/__init__.py bazel-out/host/genfiles/tensorflow/nn/__init__.py bazel-out/host/genfiles/tensorflow/nn/rnn_cell/__init__.py bazel-out/host/genfiles/tensorflow/profiler/__init__.py bazel-out/host/genfiles/tensorflow/python_io/__init__.py bazel-out/host/genfiles/tensorflow/quantization/__init__.py bazel-out/host/genfiles/tensorflow/resource_loader/__init__.py bazel-out/host/genfiles/tensorflow/strings/__init__.py bazel-out/host/genfiles/tensorflow/saved_model/__init__.py bazel-out/host/genfiles/tensorflow/saved_model/builder/__init__.py bazel-out/host/genfiles/tensorflow/saved_model/constants/__init__.py bazel-out/host/genfiles/tensorflow/saved_model/loader/__init__.py bazel-out/host/genfiles/tensorflow/saved_model/main_op/__init__.py bazel-out/host/genfiles/tensorflow/saved_model/signature_constants/__init__.py bazel-out/host/genfiles/tensorflow/saved_model/signature_def_utils/__init__.py bazel-out/host/genfiles/tensorflow/saved_model/tag_constants/__init__.py bazel-out/host/genfiles/tensorflow/saved_model/utils/__init__.py bazel-out/host/genfiles/tensorflow/sets/__init__.py bazel-out/host/genfiles/tensorflow/sparse/__init__.py bazel-out/host/genfiles/tensorflow/spectral/__init__.py bazel-out/host/genfiles/tensorflow/summary/__init__.py bazel-out/host/genfiles/tensorflow/sysconfig/__init__.py bazel-out/host/genfiles/tensorflow/test/__init__.py bazel-out/host/genfiles/tensorflow/train/__init__.py bazel-out/host/genfiles/tensorflow/train/queue_runner/__init__.py bazel-out/host/genfiles/tensorflow/user_ops/__init__.py')
Traceback (most recent call last):
File "/home/jok/.cache/bazel/_bazel_jok120/737f8d6dbadde71050b1e0783c31ea62/execroot/org_tensorflow/bazel-out/host/bin/tensorflow/create_tensorflow.python_api.runfiles/org_tensorflow/tensorflow/python/tools/api/generator/create_python_api.py", line 27, in <module>
from tensorflow.python.tools.api.generator import doc_srcs
File "/home/jok/.cache/bazel/_bazel_jok120/737f8d6dbadde71050b1e0783c31ea62/execroot/org_tensorflow/bazel-out/host/bin/tensorflow/create_tensorflow.python_api.runfiles/org_tensorflow/tensorflow/python/__init__.py", line 81, in <module>
from tensorflow.python import keras
File "/home/jok/.cache/bazel/_bazel_jok120/737f8d6dbadde71050b1e0783c31ea62/execroot/org_tensorflow/bazel-out/host/bin/tensorflow/create_tensorflow.python_api.runfiles/org_tensorflow/tensorflow/python/keras/__init__.py", line 25, in <module>
from tensorflow.python.keras import applications
File "/home/jok/.cache/bazel/_bazel_jok120/737f8d6dbadde71050b1e0783c31ea62/execroot/org_tensorflow/bazel-out/host/bin/tensorflow/create_tensorflow.python_api.runfiles/org_tensorflow/tensorflow/python/keras/applications/__init__.py", line 21, in <module>
import keras_applications
ModuleNotFoundError: No module named 'keras_applications'
Target //tensorflow/tools/pip_package:build_pip_package failed to build
INFO: Elapsed time: 695.098s, Critical Path: 152.03s
INFO: 7029 processes: 7029 local.
FAILED: Build did NOT complete successfully
This appears to be a problem with Tensorflow 1.10 build. I recommend you check out the r1.9 branch as it builds totally fine. Either the dependency list needs to be updated or Tensorflow will fix this. If you are determined to run the r.1.10 api then run the following in terminal:
pip install keras_applications==1.0.4 --no-deps
pip install keras_preprocessing==1.0.2 --no-deps
pip install h5py==2.8.0
If you're just interested in the release version (git tag will show you all available releases), run git checkout v1.10.1 before the ./configure step. Then you can follow the official instructions without installing additional dependencies.
Currently, a master branch build will give me the following error in Keras code that worked previously (this is after calling model.fit_generator() from the stand alone version of Keras):
`steps_per_epoch=None` is only valid for a generator based on the `keras.utils.Sequence` class. Please specify `steps_per_epoch` or use the `keras.utils.Sequence` class.
Builds based on the 1.10.1 release version of TensorFlow don't cause this error.
I want to profile my tensorflow application using tfprof. I have a running tensorflow 1.3 installation where the the tfprof command line tool is missing. I also tried the provided pip packages locally, but there I also can't find tfprof.
Is there a way to compile and link the tfprof command line tool agains my running tensorflow application?
I already git-cloned the tensorflow repository and tried to build it with bazel 0.5.2
$ bazel build --config opt tensorflow/core/profiler/...
WARNING: Output base '/home/USERNAME/.cache/bazel/_bazel_USERNAME/e5cce820cc082410b4fcc604db349066' is on NFS. This may lead to surprising failures and undetermined behavior.
WARNING: Config values are not defined in any .rc file: opt
ERROR: /tmp/tensorflow/tensorflow/core/BUILD:1416:1: no such target '//tensorflow/tools/git:gen/spec.json': target 'gen/spec.json' not declared in package 'tensorflow/tools/git' defined by /tmp/tensorflow/tensorflow/tools/git/BUILD and referenced by '//tensorflow/core:version_info_gen'.
ERROR: /tmp/tensorflow/tensorflow/core/BUILD:1416:1: no such target '//tensorflow/tools/git:gen/head': target 'gen/head' not declared in package 'tensorflow/tools/git' defined by /tmp/tensorflow/tensorflow/tools/git/BUILD and referenced by '//tensorflow/core:version_info_gen'.
ERROR: /tmp/tensorflow/tensorflow/core/BUILD:1416:1: no such target '//tensorflow/tools/git:gen/branch_ref': target 'gen/branch_ref' not declared in package 'tensorflow/tools/git' defined by /tmp/tensorflow/tensorflow/tools/git/BUILD and referenced by '//tensorflow/core:version_info_gen'.
ERROR: Analysis of target '//tensorflow/core/profiler:profiler' failed; build aborted.
INFO: Elapsed time: 167.083s
or just copy the command mentioned here
bazel build --config opt third_party/tensorflow/core/profiler/...
WARNING: Output base '/home/USERNAME/.cache/bazel/_bazel_USERNAME/e5cce820cc082410b4fcc604db349066' is on NFS. This may lead to surprising failures and undetermined behavior.
WARNING: Config values are not defined in any .rc file: opt
ERROR: no targets found beneath 'third_party/tensorflow/core/profiler'.
I think the path is not right. You should use pathtensorflow/core/profiler/, if your current directory is the cloned tensorflow repository.
Run ./configure script from your tensorflow directory to set the environment variables.
There seems to be a problem with recent TensorFlow build. The TensorBoard visualization tool would not run when it is compiled from sources to use with GPU. The error is as follows:
$ tensorboard
Traceback (most recent call last):
File "/home/gpu/anaconda3/envs/tensorflow/bin/tensorboard", line 7, in <module>
from tensorflow.tensorboard.tensorboard import main
ModuleNotFoundError: No module named 'tensorflow.tensorboard.tensorboard'
Specs of system: Ubuntu 16.04, NVIDIA GTX 1070, cuda-8.0, cudnn 6.0.
Installed using Bazel from sources as described here:
https://www.tensorflow.org/install/install_sources
Installed into fresh anaconda3 environment 'tensorflow', environment is activated when performing command.
Would appreciate any help!
An easy fix:
python -m tensorboard.main --logdir=/path/to/logs
After some trial and error, I have solved this issue by adapting the file tensorboard-script.py in path/to/conda/envs/myenv/Scripts (Windows) as follows:
if __name__ == '__main__':
import sys
#import tensorflow.tensorboard.tensorboard
import tensorboard.main
#sys.exit(tensorflow.tensorboard.tensorboard.main())
sys.exit(tensorboard.main.main())
Now I can invoke tensorboard as expected:
tensorboard --logdir=log/ --port 6006
Okay, I've found a solution that works and also received some explanation from tensorflower on github.
There might be an issue with tensorboard when compiling tensorflow from sources because tensorboard is now removed to a separate repo and is not a part of tensorflow. The tensorflower said the docs will be updated eventually, but I figured a workaround for the impatient (like myself).
Edit tensorboard file inside tensorflow/bin (/home/gpu/anaconda3/envs/tensorflow/bin/tensorboard in my case) and replace
from tensorflow.tensorboard.tensorboard import main
by
from tensorflow.tensorboard.main import *
Now tensorboard should run from console as usual.
Tensorboard ships with tensorflow. If you are unable to run using tensorboard command, try below approach. tensorboard.py might have been moved to different directory.
Try searching for tensorboard.py in the tensorbard directory where tensorflow is installed. Go to the path and use following line for visualization:
python tensorboard.py --logdir=path
You should priorly launch
pip install tensorflow.tensorboard
Compiled the libjpeg v8, PIL 1.1.7 and and import for _imaging works on the system Python, but spouts this error inside the virtualenv:
libjpeg.so.8: cannot open shared object file: No such file or directory
here is the error run with a python -v interpreter inside the virtualenv
>>> import _imaging
dlopen("/home/ygamretuta/dev/py/django/lib/python2.6/site-packages/PIL/_imaging.so", 2);
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ImportError: libjpeg.so.8: cannot open shared object file: No such file or directory
and here are the paths:
/home/ygamretuta/dev/py/django/lib/python2.6/site-packages/distribute-0.6.14-py2.6.egg
/home/ygamretuta/dev/py/django/lib/python2.6/site-packages/pip-0.8.1-py2.6.egg
/home/ygamretuta/dev/py/django/lib/python2.6
/home/ygamretuta/dev/py/django/lib/python2.6/plat-linux2
/home/ygamretuta/dev/py/django/lib/python2.6/lib-tk
/home/ygamretuta/dev/py/django/lib/python2.6/lib-old
/home/ygamretuta/dev/py/django/lib/python2.6/lib-dynload
/usr/lib/python2.6
/usr/lib/python2.6/plat-linux2
/usr/lib/python2.6/lib-tk
/home/ygamretuta/dev/py/django/lib/python2.6/site-packages
/home/ygamretuta/dev/py/django/lib/python2.6/site-packages/PIL
I am using Ubuntu 10.10 and this is the uname-a output:
Linux ygam-desktop 2.6.35-28-generic #49-Ubuntu SMP Tue Mar 1 14:40:58 UTC 2011 i686 GNU/Linux
I am using Python 2.6
I followed the following guides already:
http://appelfreelance.com/2010/06/libjpeg-pil-snow-leopard-python2-6-_jpeg_resync_to_restart/
http://www.jooncode.com/2010/12/02/python-pil-jpeg-resync-restart-error-imaging-module-solve/
http://djangodays.com/2008/09/03/django-imagefield-validation-error-caused-by-incorrect-pil-installation-on-mac/
See an explanation here: Why can't Python find shared objects that are in directories in sys.path?
A quick fix is to add the directory that contains libjpeg.so.8 to your /etc/ld.so.conf file, and then run ldconfig
Also if you are doing local Python installations you can also control dynamic linking on the session level using LD_LIBRARY_PATH environment variable::
export LD_LIBRARY_PATH=/srv/plone/python/python-2.6/lib
python
import _imaging
...
This way you cannot break your OS itself, even accidentally. (It happens: http://opensourcehacker.com/2011/08/31/zend-server-installation-potentially-kills-your-ssh/)
Compiling the library from source works too: http://www.ijg.org/files/
Make sure to use jpegsrc.v8.tar.gz if you're on a Unix like system though. jpegsr8.zip appears to be the MS version, and throws all the standard formatting issues while building.
maybe just install libjpeg
conda install -c conda-forge libjpeg-turbo
I downloaded and installed libjingle-0.5.2.zip, and according to the README also downloaded and installed swtoolkit.0.9.1.zip, scons-local-2.1.0.alpha.20101125.tar.gz, and expat-2.0.1.tar.gz, and got nrtp by cvs download. After overwriting my Makefile twice, attempting to follow the rather poorly-written README, I came up with the following Makefile that almost works:
# First, make sure the SCONS_DIR environment variable is set correctly.
SCONS_DIR ?= /usr/src/scons-local/scons-local-2.1.0.alpha.20101125/
#SCONS_DIR ?= /usr/src/scons-local/
export
default: build
# Second, run talk/third_party/expat-2.0.1/configure...
talk/third_party/expat-2.0.1/Makefile:
cd talk/third_party/expat-2.0.1 && ./configure
# ...and talk/third_party/srtp/configure.
talk/third_party/srtp/Makefile:
cd talk/third_party/srtp && ./configure
# Third, go to the talk/ directory and run $path_to_swtoolkit/hammer.sh. Run
# $path_to_swtoolkit/hammer.sh --help for information on how to build for
# different modes.
build: talk/third_party/expat-2.0.1/Makefile talk/third_party/srtp/Makefile
cd talk && ../../swtoolkit/hammer.sh
help:
../swtoolkit/hammer.sh --help
However, make gives me the following errors:
jcomeau#intrepid:/usr/src/libjingle-0.5.2$ make
cd talk && ../../swtoolkit/hammer.sh
*** Error loading site_init file './../../swtoolkit/site_scons/site_init.py':
AttributeError: 'Dir' object has no attribute 'endswith':
File "/usr/src/scons-local/scons-local-2.1.0.alpha.20101125/SCons/Script/Main.py", line 1338:
_exec_main(parser, values)
File "/usr/src/scons-local/scons-local-2.1.0.alpha.20101125/SCons/Script/Main.py", line 1302:
_main(parser)
File "/usr/src/scons-local/scons-local-2.1.0.alpha.20101125/SCons/Script/Main.py", line 929:
_load_site_scons_dir(d.path, options.site_dir)
File "/usr/src/scons-local/scons-local-2.1.0.alpha.20101125/SCons/Script/Main.py", line 719:
exec fp in site_m
File "./../../swtoolkit/site_scons/site_init.py", line 455:
SiteInitMain()
File "./../../swtoolkit/site_scons/site_init.py", line 451:
SCons.Node.FS.get_default_fs().SConstruct_dir, None)
File "/usr/src/scons-local/scons-local-2.1.0.alpha.20101125/SCons/Script/Main.py", line 677:
site_dir = os.path.join(topdir, site_dir_name)
File "/usr/lib/python2.6/posixpath.py", line 67:
elif path == '' or path.endswith('/'):
make: *** [build] Error 2
I'm guessing that something new (a 'Dir' object being where a POSIX path string is expected) in one of the packages is breaking the build process, but which one? There are just too many layers of cruft here for me to follow. For sure I could just keep trying older packages, particularly for swtoolkit and scons, but if anyone here has successfully compiled libjingle and could prod me in the right direction, I'd appreciate it.
I'm not familiar with the project, but think I have a fix to get you past that point. You need to cast those Dir instances using str() in swtoolkit/site_scons/site_init.py. That way they can safely be evaluated by path.endswith('/'). Odd that such an issue would exist for very long in the main part of the build infrastructure:
Line 330:
SCons.Script.Main._load_site_scons_dir(
str(SCons.Node.FS.get_default_fs().SConstruct_dir), site_dir)
Line 450:
SCons.Script.Main._load_site_scons_dir(
str(SCons.Node.FS.get_default_fs().SConstruct_dir), None)
I did following to build libjingle :
Building LibJingle for Linux
How to Build
Libjingle is built with swtoolkit ( http://code.google.com/p/swtoolkit/), which
is a set of extensions to the open-source SCons build tool ( http://www.scons.org).
First, install Python 2.4 or later from http://www.python.org/.
Please note that since swtoolkit only works with Python 2.x, you will
not be able to use Python 3.x.
Second, install the stand alone scons-local package 2.0.0 or later from
http://www.scons.org/download.php and set an environment variable,
SCONS_DIR, to point to the directory containing SCons, for example,
/src/libjingle/scons-local/scons-local-2.0.0.final.0/.
Third, install swtoolkit from http://code.google.com/p/swtoolkit/.
Finally, Libjingle depends on two open-source projects, expat and srtp.
Download expat from http://sourceforge.net/projects/expat/ to
talk/third_party/expat-2.0.1/. Follow the instructions at
http://sourceforge.net/projects/srtp/develop to download latest srtp to
talk/third_party/srtp. Note that srtp-1.4.4 does not work since it misses
the extensions used by Libjingle.
If you put expat or srtp in a different directory, you need to edit
talk/libjingle.scons correspondingly.
2.1 Build Libjingle under Linux or OS X
First, make sure the SCONS_DIR environment variable is set correctly.
Second, run talk/third_party/expat-2.0.1/configure and
talk/third_party/srtp/configure.
Third, go to the talk/ directory and run $path_to_swtoolkit/hammer.sh. Run
$path_to_swtoolkit/hammer.sh --help for information on how to build for
different modes.
Other than above given steps, See following as reference
Set SCONS_DIR Path
export SCONS_DIR=/home/esumit/libjingle/libjingle-0.5.2/talk/third_party/scons-local/scons-local-2.0.1
Install libasound2-dev Lib to compile libJingle, otherwise you will encounter errors.
sudo apt-get install libasound2-dev
Download SRTP using the following command. If it asks for a passowrd, just hit Enter.
cvs -z3 -d:pserver:anonymous#srtp.cvs.sourceforge.net:/cvsroot/srtp co -P srtp
Possible components in LibJingle Directory
libjingle-0.5.2/talk/third_party$ ls
expat-2.0.1 libudev scons-local srtp swtoolkit
Execute following command to build LibJingle
libjingle-0.5.2/talk$ ./third_party/swtoolkit/hammer.sh