MXConsole is a standalone TensorFlow's Tensorboard port intended for MxNet, but now is plotform netural. Now this project is in very early stage.
MXConsole use extracted TensorFlow's filesystem and record_reader and record_writer code
as a python extension. Thus we don't need to build the whole TensorFlow.
meanwhile, without TensorFlow's Tensor and ops. Platform relavant summary related code is needed .
Now we only provide api that generate summary from numpy.ndarray
. part of these api is merged from dmlc/tensorboard.
- bazel
- node.js and bower(actually we only need bower to do bower install, so just
npm install -g bower
should be fine`) - optional: gulp and other node.js module(for frontend build only)
-
normal installation
- clone this repo
git clone https://github.com/bravomikekilo/mxconsole --recursive
cd mxconsole/tensorflow_fs
./configure
to configure tensorflow_fs build, choose your python binary and default libs and choose only the jemalloc support.cd .. && ./update_native.sh
to build and update tensorflow_fspython setup.py setup.py bdist_wheel
to build python wheelpip install dist/MXConsole-0.0.1a1-py2.py3-none-any.whl
install the python wheel- You now can use the MXConsole like
python -m mxconsole --logdir path/of/your/logs
- clone this repo
-
refresh the native library
$ ./update_native.sh
some logs can be generated from carpedm20/DCGAN-tensorflow, just train that model on mnist is just fine. You also can try the example merged from dmlc/tensorboard, under the demo folder.